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....
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...
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” 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...
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...
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...
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,...
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...
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...
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 –...
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...
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...
