This volume constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Fuzzy Logic and Applications held in Naples, Italy, in October 2003. The 40 revised full papers presented have gone through two rounds of reviewing and revision. All current issues of theoretical, experimental and applied fuzzy logic and related techniques are addressed with special attention to rough set theory, neural networks, genetic algorithms and soft computing. The papers are organized in topical section (...) on fuzzy sets and systems, fuzzy control, neuro-fuzzy systems, fuzzy decision theory and application, and soft computing in image processing. (shrink)

part 1. Fuzzy logic theory 1 -- part 2. Applications and advanced topics of fuzzy logic.

This hands-on guide offers clear explanations of fuzzy logic along with practical uses and detailed examples. Written by an award-winning engineer and experienced author, Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning is aimed at improving competence and skills in students and professionals alike. Inside, you will discover how to apply fuzzy logic and migrate to a new man-machine relationship in the context of pervasive digitization and big data across emerging (...) technologies. The book lays out real-world applications in intelligent energy systems with demand response, smart homes, electrification of transportation, supply chain efficiencies, smart cities, e-commerce, education, healthcare, and decarbonization. (shrink)

The main purpose of this article is to bring Ragin’s recent methodological contributions, which build on ideas borrowed from fuzzy logic, to the attention of management scholars. To demonstrate the possible use of the techniques developed by Ragin in management research, three specific examples for their likely applications are presented: the replications of Porter’s diamond framework for Turkey, Greece and Canada. The article concludes that Ragin’s systematic techniques prove helpful in making explicit the process of comparing qualitative (...) evidence derived from case study research, and thus they deserve greater attention in the management literature. (shrink)

Fuzzy logic has become an important tool for a number of different applications ranging from the control of engineering systems to artificial intelligence. In this concise introduction, the author presents a succinct guide to the basic ideas of fuzzy logic, fuzzy sets, fuzzy relations, and fuzzy reasoning, and shows how they may be applied. The book culminates in a chapter which describes fuzzy logic control: the design of intelligent control systems (...) using fuzzy if-then rules which make use of human knowledge and experience to behave in a manner similar to a human controller. Throughout, the level of mathematical knowledge required is kept basic and the concepts are illustrated with numerous diagrams to aid in comprehension. As a result, all those curious to know more about fuzzy concepts and their real-world application will find this a good place to start. (shrink)

One of the major problems in the implementation of the precautionary principle in environmental cases is the estimation of the weight of evidence. In this paper we propose a formal method that determines the weight of evidence based on the specific parameters of a given case. The proposed method is based on an artificial intelligence approach called fuzzy logic, which is commonly used as an interface between logic and human perception, and often applied to computer-based complex decision (...) making. We use one fuzzy expert system that provides a quantification of the estimated environmental damage, and a second fuzzy expert system that computes the weight of evidence in a given case. The proposed expert system can be easily defined and adjusted by regulators and environmental science and policy experts. (shrink)

The term "fuzzy logic," as it is understood in this book, stands for all aspects of representing and manipulating knowledge based on the rejection of the most fundamental principle of classical logic---the principle of bivalence. According to this principle, each declarative sentence is required to be either true or false. In fuzzy logic, these classical truth values are not abandoned. However, additional, intermediate truth values between true and false are allowed, which are interpreted as degrees (...) of truth. This opens a new way of thinking---thinking in terms of degrees rather than absolutes. For example, it leads to the definition of a new kind of sets, referred to as fuzzy sets, in which membership is a matter of degree. The book examines the genesis and development of fuzzy logic. It surveys the prehistory of fuzzy logic and inspects circumstances that eventually lead to the emergence of fuzzy logic. The book explores in detail the development of propositional, predicate, and other calculi that admit degrees of truth, which are known as fuzzy logic in the narrow sense. Fuzzy logic in the broad sense, whose primary aim is to utilize degrees of truth for emulating common-sense human reasoning in natural language, is scrutinized as well. The book also examines principles for developing mathematics based on fuzzy logic and provides overviews of areas in which this has been done most effectively. It also presents a detailed survey of established and prospective applications of fuzzy logic in various areas of human affairs, and provides an assessment of the significance of fuzzy logic as a new paradigm. (shrink)

Medical knowledge as well as clinical practice are characterized by inescapable uncertainty. There are many reasons this is the case, but foremost among them is that almost everything in medicine is inevitably vague, be it something linguistic such as the term “illness”, or something extra-linguistic such as the condition referred to as illness. If we ask ourselves, then, what the term “illness” means exactly, on the one hand; and how we may precisely delimit the condition illness, on the other; we (...) shall realize that to answer these and similar questions requires specific methods that enable us to adequately cope with vagueness. As we shall see below, fuzzy logic provides us with just such methods. (shrink)

This unique compendium presents a comprehensive and self-contained theory of material development under imperfect information and its applications. The book describes new approaches to synthesis and selection of materials with desirable characteristics. Such approaches provide the ability of systematic and computationally effective analysis in order to predict composition, structure and related properties of new materials. The volume will be a useful advanced textbook for graduate students. It is also suitable for academicians and practitioners who wish to have fundamental models (...) in new material synthesis and selection. (shrink)

Fuzzy logics are many-valued logics that are well suited to reasoning in the context of vagueness. They provide the basis for the wider field of Fuzzy Logic, encompassing diverse areas such as fuzzy control, fuzzy databases, and fuzzy mathematics. This book provides an accessible and up-to-date introduction to this fast-growing and increasingly popular area. It focuses in particular on the development and applications of "proof-theoretic" presentations of fuzzy logics; the result of more (...) than ten years of intensive work by researchers in the area, including the authors. In addition to providing alternative elegant presentations of fuzzy logics, proof-theoretic methods are useful for addressing theoretical problems and developing efficient deduction and decision algorithms. Proof-theoretic presentations also place fuzzy logics in the broader landscape of non-classical logics, revealing deep relations with other logics studied in Computer Science, Mathematics, and Philosophy. The book builds methodically from the semantic origins of fuzzy logics to proof-theoretic presentations such as Hilbert and Gentzen systems, introducing both theoretical and practical applications of these presentations. (shrink)

Fuzzy logic is finding increased application in the control of real-world processes and in the work with and the manipulation of inexact knowledge. Two of the major attractions of fuzzy logic are: it permits one to express problems in (familiar) linguistic terms and it can be applied where the numerical mathematical model of a system may be too complex or impossible to build using conventional techniques. This book, written in an easily accessible style, assumes that students (...) have a solid background in embedded systems including basic logic design and C/C programming. (shrink)

The article presents several adaptive fuzzy hedge logics. These logics are designed to perform a specific kind of hedge detection. Given a premise set Γ that represents a series of communicated statements, the logics can check whether some predicate occurring in Γ may be interpreted as being (implicitly) hedged by technically, strictly speaking or loosely speaking, or simply non-hedged. The logics take into account both the logical constraints of the premise set as well as conceptual information concerning the meaning (...) of potentially hedged predicates (stored in the memory of the interpreter in question). The proof theory of the logics is non-monotonic in order to enable the logics to deal with possible non-monotonic interpretation dynamics (this is illustrated by means of several concrete proofs). All the adaptive fuzzy hedge logics are also sound and strongly complete with respect to their [0,1]-semantics. (shrink)

Formal systems of fuzzy logic are well-established logical systems and respected members of the broad family of the so-called substructural logics closely related to the famous logic BCK. The study of fragments of logical systems is an important issue of research in any class of non-classical logics. Here we study the fragments of nine prominent fuzzy logics to all sublanguages containing implication. However, the results achieved in the paper for those nine logics are usually corollaries of (...) theorems with much wider scope of applicability. In particular, we show how many of these fragments are really distinct and we find axiomatic systems for most of them. In fact, we construct strongly separable axiomatic systems for eight of our nine logics. We also fully answer the question for which of the studied fragments the corresponding class of algebras forms a variety. Finally, we solve the problem how to axiomatize predicate versions of logics without the lattice disjunction. (shrink)

Fuzzy logics are systems of logic with infinitely many truth values. Such logics have been claimed to have an extremely wide range of applications in linguistics, computer technology, psychology, etc. In this note, we canvass the known results concerning infinitely many valued logics; make some suggestions for alterations of the known systems in order to accommodate what modern devotees of fuzzy logic claim to desire; and we prove some theorems to the effect that there can (...) be no fuzzy logic which will do what its advocates want. Finally, we suggest ways to accommodate these desires in finitely many valued logics. (shrink)

The dynamic nature and increasing complexity of the construction industry have led to increased conflicts in construction projects. An accurate prediction of the outcome of a dispute resolution in courts could effectively reduce the number of disputes that would otherwise conclude by spending more money through litigation. This study aims to introduce a two-layered fuzzy logic model for predicting court decisions in construction contract disputes. 100 cases of construction contract disputes are selected from the courts of Iran. A (...) questionnaire survey is then conducted to extract a set of fuzzy rules for identifying important decision parameters and expert knowledge. Accordingly, a two-layered fuzzy logic-based decision-making architecture is proposed for the prediction model. Furthermore, the fuzzy system is trained based on 10-fold cross-validation. Analysis of results indicates that 51 out of the 100 cases are filed after the dissolution and termination of the contract show a significant impact of these clauses as the root cause in construction contract disputes. Our results present a proposed hierarchical fuzzy system that can correctly predict nearly 60% of the test data. Also, we demonstrate a methodology of using argument before ML to establish interpretable AI models. Based on our findings, a fuzzy model with a hierarchical structure may be used as a simple and efficient method for predicting court decisions in construction contract disputes. (shrink)

As a generation of fuzzy set, the notion of complex fuzzy set which is an innovative concept is introduced by Ramot, Milo, Friedman and Kandel. The purpose of this article is to apply complex fuzzy set to BCK/BCI-algebras. The notions of a complex subalgebra and a complex left reduced ideal in a BCK/BCI- algebra are introduced, and related properties are investigated. Characterizations of a complex subalgebra are provided, and the homomorphic image of a complex subalgebra and a (...) complex left reduced ideal. (shrink)

In this research article, we presented the idea of intuitionistic fuzzy incidence graphs along with their certain properties. The number of operations including Cartesian product, composition, tensor product, and normal product in an IFIGs are also investigated. The method to compute the degree of IFIGs obtained by CP, composition, tensor product, and the normal product is discussed. Some important theorems to calculate the degree of the vertices of IFIGs acquired by CP, composition, tensor product, and normal product are elaborated. (...) An application of CP and composition of two IFIGs in the textile industry to find the best combinations of departments expressing the highest percentage of progress and the lowest percentage of nonprogress is provided. A comparative analysis of our study with the existing study is discussed. Our study will be beneficial to comprehend and understand the further characteristics of IFIGs in detail. Another advantage of our study is that it will be helpful to find the maximum percentage of progress and minimum percentage of nonprogress in different departments of universities, garment factories, and hospitals. (shrink)

The theory of concept lattices is approached from the point of view of fuzzy logic. The notions of partial order, lattice order, and formal concept are generalized for fuzzy setting. Presented is a theorem characterizing the hierarchical structure of formal fuzzy concepts arising in a given formal fuzzy context. Also, as an application of the present approach, Dedekind–MacNeille completion of a partial fuzzy order is described. The approach and results provide foundations for formal concept (...) analysis of vague data—the propositions “object x has attribute y”, which form the input data to formal concept analysis, are now allowed to have also intermediate truth values, meeting reality better. (shrink)

Interval type-2 fuzzy logic systems have favorable abilities to cope with uncertainties in many applications. While the block type-reduction under the guidance of inference plays the central role in the systems, Karnik-Mendel iterative algorithms are standard algorithms to perform the type-reduction; however, the high computational cost of type-reduction process may hinder them from real applications. The comparison between the KM algorithms and other alternative algorithms is still an open problem. This paper introduces the related theory of (...) interval type-2 fuzzy sets and discusses the blocks of fuzzy reasoning, type-reduction, and defuzzification of interval type-2 fuzzy logic systems by combining the Nagar-Bardini and Nie-Tan noniterative algorithms for solving the centroids of output interval type-2 fuzzy sets. Moreover, the continuous version of NT algorithms is proved to be accurate algorithms for performing the type-reduction. Four computer simulation examples are provided to illustrate and analyze the performances of two kinds of noniterative algorithms. The NB and NT algorithms are superior to the KM algorithms on both calculation accuracy and time, which afford the potential application value for designer and adopters of type-2 fuzzy logic systems. (shrink)

Spiritual Intelligence (S-Intelligence) introduced to achieve higher levels of knowledge and applying hidden knowledge. This intelligence is various in different people. When people work together in a team or set, these diverse influence on their performance. Facilitate the application of spiritual capacities by using abilities of S- intelligence is important to increase productivity teamwork. For this purpose, we provided a model of communication for individuals with different S-intelligence in performing team tasks. First, with the basics S-intelligence analysis and interviews with (...) experts, S-intelligence was divided in five categories. Each person according to their S-Intelligence and the role that play in teamwork (individualist, thinkist and pragmatist) from this aspect that he/she can by what kind of S-intelligences and what kind of role, has an effective team relationship, has been measured. With the 690 questionnaires among individuals with experience in teamwork and group communication, we have addressed to the measurement of their communication model. After derivation the data by fuzzy logic, we analyzed and presented an effective model of teamwork based on S-intelligence. (shrink)

Huge losses and serious threats to ecosystems are common consequences of forest fires. This work describes a forest fire controller based on fuzzy logic and decision-making methods aiming at enhancing forest fire prevention, detection, and fighting systems. In the proposal, the environmental monitoring of several dynamic risk factors is performed with wireless sensor networks and analysed with the proposed fuzzy-based controller. With respect to this, meteorological variables, polluting gases and the oxygen level are measured in real time (...) to estimate the existence of forest fire risks in the short-term and to detect the recent occurrence of fire outbreaks over different forest areas. Besides, the Analytic Hierarchy Process method is used to determine the level of fire spread, and, when necessary, environmental alerts are sent by a Web service and received by a mobile application. For this purpose, integrity, confidentiality, and authenticity of environmental information and alerts are protected with implementations of Lamport’s authentication scheme, Diffie-Lamport signature, and AES-CBC block cipher. (shrink)

This book is a collection of contributions written by philosophers and scientists active in different fields, such as mathematics, logics, social sciences, computer sciences and linguistics. They comment on and discuss various parts of and subjects and propositions introduced in the Handbook of Analytical Philosophy of Medicine from Kadem Sadegh-Zadeh, published by Springer in 2012. This volume reports on the fruitful exchange and debate that arose in the fuzzy community upon the publication of the Handbook. This was not only (...) very much appreciated by the community but also seen as a critical starting point for beginning a new discussion. The results of this discussion, which involved many different perspectives from science and the humanities and was warmly encouraged by Kadem Sadegh-Zadeh himself, are accurately reported in this volume, which is intended to be a critical companion to Kadem Sadegh-Zadeh ́s handbook. Rudolf Seising is currently an adjunct researcher at the European Centre for Soft Computing in Mieres, Asturias (Spain) and a college lecturer at the Faculty of History and Arts, at the Ludwig Maximilians University of Munich (Germany). Marco Elio Tabacchi is currently the Scientific Director of the Italian National Research & Survey Organization Demopolis, and a research assistant in the Soft Computing Group at University of Palermo (Italy). (shrink)

Analogy making from examples is a central task in intelligent system behavior. A lot of real world problems involve analogy making and generalization. Research investigates these questions by building computer models of human thinking concepts. These concepts can be divided into high level approaches as used in cognitive science and low level models as used in neural networks. Applications range over the spectrum of recognition, categorization and analogy reasoning. A major part of legal reasoning could be formally interpreted as (...) an analogy making process. Because it is not the same as reasoning in mathematics or the physical sciences, it is necessary to use a method, which incorporates first the ability to specify likelihood and second the opportunity of including known court decisions. We use for modelling the analogy making process in legal reasoning neural networks and fuzzy systems. In the first part of the paper a neural network is described to identify precedents of immaterial damages. The second application presents a fuzzy system for determining the required waiting period after traffic accidents. Both examples demonstrate how to model reasoning in legal applications analogous to recent decisions: first, by learning a system with court decisions, and second, by analyzing, modelling and testing the decision making with a fuzzy system. (shrink)

As an introduction to our work, we emphasize the parallel interpretation of abstract tools and the concepts of undetermined and vague information. Imprecision, uncertainty and their relationships are inspected. Suitable interpretations of the fuzzy sets theory are applied to legal phenomena in an attempt to clearly circumscribe the possible applications of the theory. The fundamental notion of reference sets is examined in detail, hence highlighting their importance. A systematic and combinatorial classification of the relevant subsets of the legal (...) field is supplied for practical application. Although the use of the fuzzy sets theory is sometimes suggested as a palliative measure (no competition exists), it can also be complementary (serve as a building block to improve modelisation). An Appendix gives a brief recall of the key-concepts of the axiomatic theory of fuzziness and its developments: fuzzy sets, fuzzy logic, fuzzy control and theory of possibility. (shrink)

Monoidal t-norm based logic $\mathbf {MTL}$ is the weakest t-norm based residuated fuzzy logic, which is a $[0,1]$ -valued propositional logical system having a t-norm and its residuum as truth function for conjunction and implication. Monadic fuzzy predicate logic $\mathbf {mMTL\forall }$ that consists of the formulas with unary predicates and just one object variable, is the monadic fragment of fuzzy predicate logic $\mathbf {MTL\forall }$, which is indeed the predicate version of monoidal (...) t-norm based logic $\mathbf {MTL}$. The main aim of this paper is to give an algebraic proof of the completeness theorem for monadic fuzzy predicate logic $\mathbf {mMTL\forall }$ and some of its axiomatic extensions. Firstly, we survey the axiomatic system of monadic algebras for t-norm based residuated fuzzy logic and amend some of them, thus showing that the relationships for these monadic algebras completely inherit those for corresponding algebras. Subsequently, using the equivalence between monadic fuzzy predicate logic $\mathbf {mMTL\forall }$ and S5-like fuzzy modal logic $\mathbf {S5(MTL)}$, we prove that the variety of monadic MTL-algebras is actually the equivalent algebraic semantics of the logic $\mathbf {mMTL\forall }$, giving an algebraic proof of the completeness theorem for this logic via functional monadic MTL-algebras. Finally, we further obtain the completeness theorem of some axiomatic extensions for the logic $\mathbf {mMTL\forall }$, and thus give a major application, namely, proving the strong completeness theorem for monadic fuzzy predicate logic based on involutive monoidal t-norm logic $\mathbf {mIMTL\forall }$ via functional representation of finitely subdirectly irreducible monadic IMTL-algebras. (shrink)

Development of decision-support and intelligent agent systems necessitates mathematical descriptions of uncertainty and fuzziness in order to model vagueness. This paper seeks to present an outline of Peirce’s triadic logic as a practical new way to model vagueness in the context of artificial intelligence. Charles Sanders Peirce was an American scientist–philosopher and a great logician whose triadic logic is a culmination of the study of semiotics and the mathematical study of anti-Cantorean model of continuity and infinitesimals. After presenting (...) Peircean semiotics within AI perspective, a mathematical formulation of a Peircean triadic set is given in relationship with classical and fuzzy sets. Using basic logical operators, all possible respective implication operators, bi-equivalence operators, valid rules of inference, and associative, distributive and commutative logical properties are derived and verified through the truth function approach. In order to suggest practical directions, aggregation operators for Peirce’s triadic logic have been formulated. A mathematical formulation of a medical diagnostic problem and ER diagram of a library management system using Peirce’s triadic relation show potential for further applications of the proposed triadic set and triadic logic. Alongside, a classical AI game—The Wumpus World—is implemented to show practical efficacy in comparison with binary implementation. Besides giving some preliminary formulations for trichotomous set theory and definition of finite automaton, development of hybrid architectures for intelligent agents and evolutionary computations are discussed as potential practical avenues for Peirce’s triadic logic. (shrink)

In many applications we have a set of objects together with their properties. Since the available information is usually incomplete and/or imprecise, the true knowledge about subsets of objects can be determined approximately only. In this paper, we discuss a fuzzy generalisation of two pairs of relation-based operators suitable for fuzzy set approximations, which have been recently investigated by Düntsch and Gediga. Double residuated lattices, introduced by Orlowska and Radzikowska, are taken as basic algebraic structures. Main properties (...) of these operators are presented. (shrink)

The study of weighted structures is one of the important trends in recent computer science. The aim of the article is to provide a weighted, many-valued version of classical intensional semantics formalised in the framework of higher-order fuzzy logics. We illustrate the apparatus on several variants of fuzzy S5-style modalities. The formalism is applicable to a broad array of weighted intensional notions, including alethic, epistemic, or probabilistic modalities, generalised quantifiers, counterfactual conditionals, dynamic and non-monotonic logics, and some more.

Continuous environmental concerns regarding construction industry have been driving general constructors of mega infrastructure projects to incorporate green contractors. Although conventional multiple attributes decision-making methodologies have provided feasible ways to select contractor, high complexity in scenarios of megaprojects still challenges existing MADM methods in concurrently accommodating three key issues of decision hesitancy, attributes interdependency, and group attitudinal character. To elicit decision-makers’ hesitant fuzzy assessments more objectively and comprehensively, we define an expression tool called interval-valued dual hesitant fuzzy uncertain (...) unbalanced linguistic set and develop aggregation operators through its operations. To exploit attributes interdependency, we establish a synthesized attributes’ weighting model to fuse an attributes interdependency-based weighting vector and an argument-dependent weighting vector, which are, respectively, derived through Decision-Making and Trial Evaluation Laboratory technique and maximizing deviation method. To effectively utilize decision-makers’ group attitudinal characters, we also develop a TOPSIS-based method to rationally transform group ideal attitudes into order-inducing vectors. On the strength of the above methods, an integrated MADM approach is then constructed. Finally, illustrative case study and experiments are conducted to validate our approach. (shrink)

In a legal expert system based on CBR (Case-Based Reasoning), legal statute rules are interpreted on the basis of precedents. This interpretation, because of its vagueness and uncertainty of the interpretation cannot be handled with the means used for crisp cases. In our legal expert system, on the basis of the facts of precedents, the statute rule is interpreted as a form of case rule, the application of which involves the concepts of membership and vagueness. The case rule is stored (...) in a data base by means of fuzzy frames. The inference based on a case rule is made by fuzzy YES and fuzzy NO, and the degree of similarity of cases. The system proposed here will be used for legal education; its main area of application is contract, especially in relation to the United Nations Convention on Contracts for the International Sale of Goods (CISG). (shrink)

In this introduction to Part 1 of the Common Knowledge symposium, “Fuzzy Studies,” the journal's editor discusses four essays from the 1980s by Richard Rorty, in which Rorty chose to associate himself with various neopragmatists, Continental thinkers, and “left-wing Kuhnians” under the rubric of the “new fuzziness.” The term had been introduced as an insult by a philosopher of science with positivist leanings, but Rorty took it up as an “endearing” compliment, arguing that “to be less fuzzy” was (...) also to be “less genial, tolerant, open-minded, and fallibilist.” He defined the “new fuzziness” as “an attempt to blur just those distinctions between the objective and subjective and between fact and value which the critical conception of rationality has developed.” This introduction also examines W. V. Quine's essay “Speaking of Objects” (1957), which describes objects as fuzzy “half-entities”; Clifford Geertz's essay “Blurred Genres” (1980), which advises social scientists that being “taxonomically upstanding” is futile; and Lofti Zadeh's article “The Concept of a Linguistic Variable and Its Application to Approximate Reasoning” (1975), which abandons “Aristotelian, bivalent logic” in favor of a “fuzzy logic” based on Zadeh's “fuzzy set theory.” This introductory piece relates these theoretical works of the past half-century to the sorites paradox and to classical issues of vagueness raised and still unresolved in Western philosophy. Returning then to Rorty, the author questions how Rorty expected his endorsement of the “new fuzziness” to be applied, as proposed, to theology and politics. Suggesting that such applications are the natural work of historians, the author, having asked the historian Natalie Zemon Davis for comment, then quotes her response—which associates fuzzy studies, “common knowledge,” and peacemaking—at length. (shrink)

The generation of the pitch control signal in a wind turbine (WT) is not straightforward due to the nonlinear dynamics of the system and the coupling of its internal variables; in addition, they are subjected to the uncertainty that comes from the random nature of the wind. Fuzzy logic has proved useful in applications with changing system parameters or where uncertainty is relevant as in this one, but the tuning of the fuzzy logic controller (FLC) (...) parameters is neither straightforward nor an easy task. On the other hand, reinforcement learning (RL) allows systems to automatically learn, and this capability can be exploited to tune the FLC. In this work, a WT pitch control architecture that uses RL to tune the membership functions and scale the output of a fuzzy controller is proposed. The RL strategy calculates the fuzzy controller gains in order to reduce the output power error of the WT according to the wind speed. Different reward mechanisms based on the output power error have been considered. Simulation results with different wind profiles show that this architecture performs better (123.7 W) in terms of power errors than an FLC without RL (133.2 W) or a simpler PID (208.8 W). Even more, it provides a smooth response and outperforms other hybrid controllers such as RL-PID and radial basis function neural network control. (shrink)

This book brings together the latest technological research in computational intelligence and fuzzy logic as a way to care for our environment, highlighting current advances and future trends in environmental sustainability using the principles of soft computing.

This paper is a contribution to the general study of consequence relations which contain (definable) connective of “disjunction”. Our work is centered around the “proof by cases property”, we present several of its equivalent definitions, and show some interesting applications, namely in constructing axiomatic systems for intersections of logics and recognizing weakly implicative fuzzy logics among the weakly implicative ones.

This commentary on Sadegh-Zadeh's article 'Fuzzy health, illness and disease,' has its focus on the philosophical background for applying fuzzy logic to medical theory. I concentrate on four issues. First, I contest some of Sadegh-Zadeh's statements on the present state of the theory of medicine, in particular with regard to assumptions ascribed to contemporary theorists. Second, I consider Sadegh-Zadeh's interesting idea that a person can have a disease to varying degrees, from not having it at all to (...) having it completely. I argue that there are difficulties pertaining to the definition of particular diseases, which obstruct the application of this idea. The following two points concern medical semantics and principles for definition in general. I take issue with Sadegh-Zadeh's description of the correct procedure for definition. I also contest his unconditional proposal for a social definition of health, illness and disease. (shrink)

Aiming at the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, an English teaching ability evaluation algorithm based on big data fuzzy K-means clustering and information fusion is proposed. Firstly, the author uses the idea of K-means clustering to analyze the collected original error data, such as teacher level, teaching facility investment, and policy relevance level, removes the data that the algorithm considers unreliable, uses the remaining valid data to calculate the weighting (...) factor of the modified fuzzy logic algorithm, and evaluates the weighted average with the node measurement data and gets the final fusion value. Secondly, the author integrates the big data information fusion and K-means clustering algorithm, realizes the clustering and integration of the index parameters of English teaching ability, compiles the corresponding English teaching resource allocation plan, and realizes the evaluation of English teaching ability. Finally, the results show that using this method to evaluate English teaching ability has better information fusion analysis ability, which improves the accuracy of teaching ability evaluation and the efficiency of teaching resources application. (shrink)

Automated Guided Vehicles (AGV) are an essential element of transport in industry 4.0. Although they may seem simple systems in terms of their kinemat.

Robot manipulators have been extensively used in complex environments to complete diverse tasks. The teleoperation control based on human-like adaptivity in the robot manipulator is a growing and challenging field. This paper developed a disturbance-observer-based fuzzy control framework for a robot manipulator using an electromyography- driven neuromusculoskeletal model. The motion intention was estimated by the EMG-driven NMS model with EMG signals and joint angles from the user. The desired torque was transmitted into the desired velocity for the robot manipulator (...) system through an admittance filter. In the robot manipulator system, a fuzzy logic system, utilizing an integral Lyapunov function, was applied for robot manipulator systems subject to model uncertainties and external disturbances. To compensate for the external disturbances, fuzzy approximation errors, and nonlinear dynamics, a disturbance observer was integrated into the controller. The developed control algorithm was validated with a 2-DOFs robot manipulator in simulation. The results indicate the proposed control framework is effective and crucial for the applications in robot manipulator control. (shrink)

In the last decade, formal concept analysis in a fuzzy setting has received more attention for knowledge processing tasks in various fields. The hierarchical order visualisation of generated formal concepts is a major concern for the practical application of FCA. In this process, a major issue is the huge number of formal concepts generated from ‘a large context’, and another problem is their ‘storage’ complexity. To deal with these issues a method is proposed in this paper based on Shannon (...) entropy and Huffman coding. The proposed method is illustrated using crisply generated concepts such that the changes between obtained concepts can be measured using Levenshtein distance. The analysis derived from the proposed method is illustrated with an example for FCA in a fuzzy setting. (shrink)

Purpose The developing academic field of machine ethics seeks to make artificial agents safer as they become more pervasive throughout society. In contrast to computer ethics, machine ethics is concerned with the behavior of machines toward human users and other machines. This study aims to use an action-based ethical theory founded on the combinational aspects of deontological and teleological theories of ethics in the construction of an artificial moral agent. Design/methodology/approach The decision results derived by the AMA are acquired via (...) fuzzy logic interpretation of the relative values of the steady-state simulations of the corresponding rule-based fuzzy cognitive map. Findings Through the use of RBFCMs, the following paper illustrates the possibility of incorporating ethical components into machines, where latent semantic analysis and RBFCMs can be used to model dynamic and complex situations, and to provide abilities in acquiring causal knowledge. Research limitations/implications This approach is especially appropriate for data-poor and uncertain situations common in ethics. Nonetheless, to ensure that a machine with an ethical component can function autonomously in the world, research in artificial intelligence will need to further investigate the representation and determination of ethical principles, the incorporation of these ethical principles into a system’s decision procedure, ethical decision-making with incomplete and uncertain knowledge, the explanation for decisions made using ethical principles and the evaluation of systems that act based upon ethical principles. Practical implications To date, the conducted research has contributed to a theoretical foundation for machine ethics through exploration of the rationale and the feasibility of adding an ethical dimension to machines. Further, the constructed AMA illustrates the possibility of utilizing an action-based ethical theory that provides guidance in ethical decision-making according to the precepts of its respective duties. The use of LSA illustrates their powerful capabilities in understanding text and their potential application as information retrieval systems in AMAs. The use of cognitive maps provides an approach and a decision procedure for resolving conflicts between different duties. Originality/value This paper suggests that cognitive maps could be used in AMAs as tools for meta-analysis, where comparisons regarding multiple ethical principles and duties can be examined and considered. With cognitive mapping, complex and abstract variables that cannot easily be measured but are important to decision-making can be modeled. This approach is especially appropriate for data-poor and uncertain situations common in ethics. (shrink)

The Joint International Conference on Logic Programming, sponsored by the Association for Logic Programming, is a major forum for presentations of research, applications, and implementations in this important area of computer science. Logic programming is one of the most promising steps toward declarative programming and forms the theoretical basis of the programming language Prolog and its various extensions. Logic programming is also fundamental to work in artificial intelligence, where it has been used for nonmonotonic and (...) commonsense reasoning, expert systems implementation, deductive databases, and applications such as computer-aided manufacturing. Krzysztof R. Apt is project leader at the Centre for Mathematics and Computer Science in Amsterdam and part-time Professor in Computer Science at the University of Amsterdam. Topics covered: Theory Foundations. Programming Languages. Implementation. Programming Methodologies and Tools. Applications. Deductive Databases. Artificial Intelligence. Parallelism. (shrink)

Artificial neural networks, in interaction with fuzzy logic, genetic algorithms, and fuzzy neural networks, represent an example of a modern interdisciplinary field, especially when it comes to solving certain types of engineering problems that could not be solved using traditional modeling methods and statistical methods. They represent a modern trend in practical developments within the prognostic modeling field and, with acceptable limitations, enjoy a generally recognized perspective for application in construction. Results obtained from numerical analysis, which includes (...) analysis of the behavior of reinforced concrete elements and linear structures exposed to actions of standard fire, were used for the development of a prognostic model with the application of fuzzy neural networks. As fire resistance directly affects the functionality and safety of structures, the significance which new methods and computational tools have on enabling quick, easy, and simple prognosis of the same is quite clear. This paper will consider the application of fuzzy neural networks by creating prognostic models for determining fire resistance of eccentrically loaded reinforced concrete columns. (shrink)

This book constitutes the strictly refereed post-workshop proceedings of the 11th International Workshop on Computer Science Logic, CSL '97, held as the 1997 Annual Conference of the European Association on Computer Science Logic, EACSL, in Aarhus, Denmark, in August 1997. The volume presents 26 revised full papers selected after two rounds of refereeing from initially 92 submissions; also included are four invited papers. The book addresses all current aspects of computer science logics and its applications and thus (...) presents the state of the art in the area. (shrink)