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Fuzzy Logic and Intelligent Systems (International Series in Intelligent Technologies)
Fuzzy Logic and Intelligent Systems (International Series in Intelligent Technologies)
One of the attractions of fuzzy logic is its utility in solving many real engineering problems. As many have realised, the major obstacles in building a real intelligent machine involve dealing with random disturbances, processing large amounts of imprecise data, interacting with a dynamically changing environment, and coping with uncertainty....
Design and Control of Intelligent Robotic Systems (Studies in Computational Intelligence)
Design and Control of Intelligent Robotic Systems (Studies in Computational Intelligence)

With the increasing applications of intelligent robotic systems in various fields, the design and control of these systems have increasingly attracted interest from researchers. This edited book entitled Design and Control of Intelligent Robotic Systems in the book series of Studies in Computational Intelligence is a collection of some...

Advances in Fuzzy Implication Functions (Studies in Fuzziness and Soft Computing)
Advances in Fuzzy Implication Functions (Studies in Fuzziness and Soft Computing)

Fuzzy implication functions are one of the main operations in fuzzy logic. They generalize the classical implication, which takes values in the set {0,1}, to fuzzy logic, where the truth values belong to the unit interval [0,1]. These functions are not only fundamental for fuzzy logic systems, fuzzy control, approximate reasoning and expert...

Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering (Water Science and Technology Library)
Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering (Water Science and Technology Library)

“Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering” provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important...

Cluster Analysis for Data Mining and System Identification
Cluster Analysis for Data Mining and System Identification

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the classification of similar objects into different groups, or more precisely, the partitioning of a data set into subsets...

Fundamentals of the Fuzzy Logic-Based Generalized Theory of Decisions (Studies in Fuzziness and Soft Computing)
Fundamentals of the Fuzzy Logic-Based Generalized Theory of Decisions (Studies in Fuzziness and Soft Computing)

Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision...

Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)
Meta-Learning in Computational Intelligence (Studies in Computational Intelligence)

In the early days of pattern recognition and statistical data analysis life was rather simple: datasets were relatively small, collected from well-designed experiments, analyzed using a few methods that had good theoretical background. Explosive growth of the use of computers led to the creation of huge amounts of data of all kinds,...

Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)
Data Mining with Computational Intelligence (Advanced Information and Knowledge Processing)
Nowadays data accumulate at an alarming speed in various storage devices,
and so does valuable information. However, it is difficult to understand information
hidden in data without the aid of data analysis techniques, which
has provoked extensive interest in developing a field separate from machine
learning. This new field is
...
Jess in Action: Java Rule-Based Systems
Jess in Action: Java Rule-Based Systems
A practical handbook for anyone interested in programming rule-based systems and written by the creator of the popular Java rule engine, Jess, this book is structured around a series of large, fully developed practical examples of rule-based programming in Java. After the topic of rule-based systems is introduced, software developers and...
Computational Intelligence: Engineering of Hybrid Systems
Computational Intelligence: Engineering of Hybrid Systems

Hybrid Intelligent Systems has become an important research topic in computer science and a key application field in science and engineering. This book offers a gentle introduction to the engineering aspects of hybrid intelligent systems, also emphasizing the interrelation with the main intelligent technologies such as genetic algorithms –...

HTML & XHTML: The Definitive Guide (6th Edition)
HTML & XHTML: The Definitive Guide (6th Edition)

Put everthing you need to know about HTML & XHTML at your fingertips. For nearly a decade, hundreds of thousands of web developers have turned to HTML & XHTML: The Definitive Guide to master standards-based web development. Truly a definitive guide, the book combines a unique balance of...

Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems
Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems
We describe in this book, new methods for intelligent pattern recognition using soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems for pattern recognition. Hybrid intelligent systems...
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