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Author: Liya Ding
Publisher: World Scientific
ISBN: 9789812794604
Category : Computers
Languages : en
Pages : 396
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Book Description
Soft computing (SC) consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as genetic algorithms. The integration of those constituent methodologies forms the core of SC. In addition, the synergy allows SC to incorporate human knowledge effectively, deal with imprecision and uncertainty, and learn to adapt to unknown or changing environments for better performance. Together with other modern technologies, SC and its applications exert unprecedented influence on intelligent systems that mimic human intelligence in thinking, learning, reasoning, and many other aspects. Knowledge engineering (KE), which deals with knowledge acquisition, representation, validation, inferencing, explanation, and maintenance, has made significant progress recently, owing to the indefatigable efforts of researchers. Undoubtedly, the hot topics of data mining and knowledge/data discovery have injected new life into the classical AI world. This book tells readers how KE has been influenced and extended by SC and how SC will be helpful in pushing the frontier of KE further. It is intended for researchers and graduate students to use as a reference in the study of knowledge engineering and intelligent systems. The reader is expected to have a basic knowledge of fuzzy logic, neural networks, genetic algorithms, and knowledge-based systems. Contents: Knowledge Engineering and Soft Computing OCo An Introduction (L-Y Ding); Fuzzy Knowledge-Based Systems: Linguistic Integrity: A Framework for Fuzzy Modeling OCo AFRELI Algorithm (J Espinosa & J Vandewalle); A New Approach to Acquisition of Comprehensible Fuzzy Rules (H Ohno & T Furuhashi); Fuzzy Rule Generation with Fuzzy Singleton-Type Reasoning Method (Y Shi & M Mizumoto); Antecedent Validity Adaptation Principle for Table Look-Up Scheme (P-T Chan & A B Rad); Fuzzy Spline Interpolation in Sparse Fuzzy Rule Bases (M F Kawaguchi & M Miyakoshi); Revision Principle Applied for Approximate Reasoning (L-Y Ding et al.); Handling Null Queries with Compound Fuzzy Attributes (S-L Wang & Y-J Tsai); Fuzzy System Description Language (K Otsuka et al.); Knowledge Representation, Integration, and Discovery by Soft Computing: Knowledge Representation and Similarity Measure in Learning a Vague Legal Concept (M Q Xu et al.); Trend Fuzzy Sets and Recurrent Fuzzy Rules for Ordered Dataset Modelling (J F Baldwin et al.); Approaches to the Design of Classification Systems from Numerical Data and Linguistic Knowledge (H Ishibuchi et al.); A Clustering Based on Self-Organizing Map and Knowledge Discovery by Neural Network (K Nakagawa et al.); Probabilistic Rough Induction (J-Z Dong et al.); Data Mining via Linguistic Summaries of Databases: An Interactive Approach (J Kacprzyk & S Zadrozny); and other papers. Readership: Graduate students, researchers and lecturers in knowledge engineering and soft computing."
Author: Liya Ding
Publisher: World Scientific
ISBN: 9789812794604
Category : Computers
Languages : en
Pages : 396
Get Book Here
Book Description
Soft computing (SC) consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as genetic algorithms. The integration of those constituent methodologies forms the core of SC. In addition, the synergy allows SC to incorporate human knowledge effectively, deal with imprecision and uncertainty, and learn to adapt to unknown or changing environments for better performance. Together with other modern technologies, SC and its applications exert unprecedented influence on intelligent systems that mimic human intelligence in thinking, learning, reasoning, and many other aspects. Knowledge engineering (KE), which deals with knowledge acquisition, representation, validation, inferencing, explanation, and maintenance, has made significant progress recently, owing to the indefatigable efforts of researchers. Undoubtedly, the hot topics of data mining and knowledge/data discovery have injected new life into the classical AI world. This book tells readers how KE has been influenced and extended by SC and how SC will be helpful in pushing the frontier of KE further. It is intended for researchers and graduate students to use as a reference in the study of knowledge engineering and intelligent systems. The reader is expected to have a basic knowledge of fuzzy logic, neural networks, genetic algorithms, and knowledge-based systems. Contents: Knowledge Engineering and Soft Computing OCo An Introduction (L-Y Ding); Fuzzy Knowledge-Based Systems: Linguistic Integrity: A Framework for Fuzzy Modeling OCo AFRELI Algorithm (J Espinosa & J Vandewalle); A New Approach to Acquisition of Comprehensible Fuzzy Rules (H Ohno & T Furuhashi); Fuzzy Rule Generation with Fuzzy Singleton-Type Reasoning Method (Y Shi & M Mizumoto); Antecedent Validity Adaptation Principle for Table Look-Up Scheme (P-T Chan & A B Rad); Fuzzy Spline Interpolation in Sparse Fuzzy Rule Bases (M F Kawaguchi & M Miyakoshi); Revision Principle Applied for Approximate Reasoning (L-Y Ding et al.); Handling Null Queries with Compound Fuzzy Attributes (S-L Wang & Y-J Tsai); Fuzzy System Description Language (K Otsuka et al.); Knowledge Representation, Integration, and Discovery by Soft Computing: Knowledge Representation and Similarity Measure in Learning a Vague Legal Concept (M Q Xu et al.); Trend Fuzzy Sets and Recurrent Fuzzy Rules for Ordered Dataset Modelling (J F Baldwin et al.); Approaches to the Design of Classification Systems from Numerical Data and Linguistic Knowledge (H Ishibuchi et al.); A Clustering Based on Self-Organizing Map and Knowledge Discovery by Neural Network (K Nakagawa et al.); Probabilistic Rough Induction (J-Z Dong et al.); Data Mining via Linguistic Summaries of Databases: An Interactive Approach (J Kacprzyk & S Zadrozny); and other papers. Readership: Graduate students, researchers and lecturers in knowledge engineering and soft computing."
Author: Liya Ding
Publisher: World Scientific
ISBN: 9814491764
Category : Computers
Languages : en
Pages : 392
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Book Description
Soft computing (SC) consists of several computing paradigms, including neural networks, fuzzy set theory, approximate reasoning, and derivative-free optimization methods such as genetic algorithms. The integration of those constituent methodologies forms the core of SC. In addition, the synergy allows SC to incorporate human knowledge effectively, deal with imprecision and uncertainty, and learn to adapt to unknown or changing environments for better performance. Together with other modern technologies, SC and its applications exert unprecedented influence on intelligent systems that mimic human intelligence in thinking, learning, reasoning, and many other aspects.Knowledge engineering (KE), which deals with knowledge acquisition, representation, validation, inferencing, explanation, and maintenance, has made significant progress recently, owing to the indefatigable efforts of researchers. Undoubtedly, the hot topics of data mining and knowledge/data discovery have injected new life into the classical AI world.This book tells readers how KE has been influenced and extended by SC and how SC will be helpful in pushing the frontier of KE further. It is intended for researchers and graduate students to use as a reference in the study of knowledge engineering and intelligent systems. The reader is expected to have a basic knowledge of fuzzy logic, neural networks, genetic algorithms, and knowledge-based systems.
Author: Lakhmi C. Jain
Publisher: Physica
ISBN: 3790818038
Category : Computers
Languages : en
Pages : 477
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Book Description
Learning is a key issue in the analysis and design of all kinds of intelligent systems. In recent time many new paradigms of automated (machine) learning have been proposed in the literature. Soft computing, that has proved to be an effective and efficient tool in so many areas of science and technology, seems to offer new qualities in the realm of machine learning too. The purpose of this volume is to present some new learning paradigms that have been triggered, or at least strongly influenced by soft computing tools and techniques, mainly related to neural networks, fuzzy logic, rough sets, and evolutionary computations.
Author: Nikhil R. Pal
Publisher: World Scientific
ISBN: 9812811699
Category : Computers
Languages : en
Pages : 411
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Book Description
Pattern recognition (PR) consists of three important tasks: feature analysis, clustering and classification. Image analysis can also be viewed as a PR task. Feature analysis is a very important step in designing any useful PR system because its effectiveness depends heavily on the set of features used to realise the system. A distinguishing feature of this volume is that it deals with all three aspects of PR, namely feature analysis, clustering and classifier design. It also encompasses image processing methodologies and image retrieval with subjective information. The other interesting aspect of the volume is that it covers all three major facets of soft computing: fuzzy logic, neural networks and evolutionary computing. Contents: Dimensionality Reduction Techniques for Interactive Visualization, Exploratory Data Analysis, and Classification (A KAnig); Feature Selection by Artificial Neural Network for Pattern Classification (B Chakraborty); A New Clustering with Estimation of Cluster Number Based on Genetic Algorithm (K Imai et al.); Minimizing the Measurement Cost in the Classification of New Samples by Neural-Network-Based Classifiers (H Ishibuchi & M Nii); Extraction of Fuzzy Rules from Numerical Data for Classifiers (N R Pal & A Sarkar); A Texture Image Segmentation Method Using Neural Networks and Binary Features (J Zhang & S Oe); Image Retrieval System Based on Subjective Information (K Yoshida et al.); and other papers. Readership: Graduate students, researchers and lecturers in pattern recognition and image analysis."
Author: Nikhil R Pal
Publisher: World Scientific
ISBN: 9814491926
Category : Computers
Languages : en
Pages : 411
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Book Description
Pattern recognition (PR) consists of three important tasks: feature analysis, clustering and classification. Image analysis can also be viewed as a PR task. Feature analysis is a very important step in designing any useful PR system because its effectiveness depends heavily on the set of features used to realise the system.A distinguishing feature of this volume is that it deals with all three aspects of PR, namely feature analysis, clustering and classifier design. It also encompasses image processing methodologies and image retrieval with subjective information. The other interesting aspect of the volume is that it covers all three major facets of soft computing: fuzzy logic, neural networks and evolutionary computing.
Author: Ahmad Lotfi
Publisher: Springer Science & Business Media
ISBN: 3540452400
Category : Computers
Languages : en
Pages : 351
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Book Description
Soft computing techniques have reached a significant level of recognition and - ceptance from both the academic and industrial communities. The papers collected in this volume illustrate the depth of the current theoretical research trends and the breadth of the application areas in which soft computing methods are making c- tributions. This volume consists of forty six selected papers presented at the Fourth Inter- tional Conference on Recent Advances in Soft Computing, which was held in N- th th tingham, United Kingdom on 12 and 13 December 2002 at Nottingham Trent University. This volume is organized in five parts. The first four parts address mainly the f- damental and theoretical advances in soft computing, namely Artificial Neural Networks, Evolutionary Computing, Fuzzy Systems and Hybrid Systems. The fifth part of this volume presents papers that deal with practical issues and ind- trial applications of soft computing techniques. We would like to express our sincere gratitude to all the authors who submitted contributions for inclusion. We are also indebted to Janusz Kacprzyk for his - vices related to this volume. We hope you find the volume an interesting refl- tion of current theoretical and application based soft computing research.
Author: Masoud Nikravesh
Publisher: Springer
ISBN: 3540323651
Category : Computers
Languages : en
Pages : 461
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Book Description
Search engines, with Google at the top, have become the most heavily used online service, with millions of searches performed every day and many remarkable capabilities. Soft Computing for Information Processing and Analysis includes reports from the front of soft computing in the internet industry and imparts knowledge and understanding of the significance of the field's accomplishments, new developments and future directions. This carefully edited book has evolved from presentations made by the participants of a meeting entitled "Fuzzy Logic and the Internet: Enhancing the Power of the Internet", organized by the Berkeley Initiative in Soft Computing (BISC), University of California, Berkeley. It addresses the important topics of modern search engines such as fuzzy query, decision analysis and support systems, including articles about topics such as Web Intelligence, World Knowledge and Fuzzy Logic (by Lotfi A. Zadeh), perception based information processing, or web intelligence.
Author: Pradip Debnath
Publisher: CRC Press
ISBN: 1000830845
Category : Computers
Languages : en
Pages : 247
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Book Description
This book explores soft computing techniques in a systematic manner starting from their initial stage to recent developments in this area. The book presents a survey of the existing knowledge and the current state-of-the-art development through cutting-edge original new contributions from the researchers. Soft Computing: Recent Advances and Applications in Engineering and Mathematical Sciences presents a survey of the existing knowledge and the current state-of-the-art development through cutting-edge original new contributions from the researchers. As suggested by the title, this book particularly focuses on the recent advances and applications of soft computing techniques in engineering and mathematical sciences. Chapter 1 describes the contribution of soft computing techniques towards a new paradigm shift. The subsequent chapters present a systematic application of fuzzy logic in mathematical sciences and decision-making. New research directions are also provided at the end of each chapter. The application of soft computing in health sciences and in the modeling of epidemics including the effects of vaccination are also examined. Sustainability of green product development, optimum design of 3D steel frame, digitalization investment analysis in the maritime industry, forecasting return rates of individual pension funds are among some of the topics where engineering and industrial applications of soft computing have been studied in the book. The readers of this book will require minimum prerequisites of undergraduate studies in computation and mathematics. This book is meant for graduate students, faculty, and researchers who are applying soft computing in engineering and mathematics. New research directions are also provided at the end of each chapter.
Author: Charles Hsu
Publisher: World Scientific
ISBN: 9810244614
Category : Computers
Languages : en
Pages : 310
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Book Description
This book presents worldwide outstanding research and recent progress in the applications of neural networks, fuzzy logic, chaos, independent component analysis, etc to fields related to speech recognition enhancement, supervised Fourier demixing noise elimination, acoustic databases, the human hearing system, cancer detection, image processing, and visual communications.
Author: Christian Borgelt
Publisher: Springer
ISBN: 3642302785
Category : Technology & Engineering
Languages : en
Pages : 378
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Book Description
Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty. Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance. Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.
