This book presents the state-of-the-art in theory and practice regarding similarity and distance measures for intuitionistic fuzzy sets. Quantifying similarity and distances is crucial for many applications, e.g. data mining, machine learning, decision making, and control. The work provides readers with a comprehensive set of theoretical...

Chapters...

The support vector machine (SVM) is a supervised learning method that generates input-output mapping functions from a set of labeled training data. The mapping function can be either a classification function, i.e., the category of the input data, or a regression function. For classification, nonlinear kernel functions are often used to...

Recognizing patterns is at the core of man's attempts to understand the universe that we inhabit. Through the development of sensors and instruments, we have extended our ability to gather data far beyond the range and scale of man's natural senses. As a result we are now able to gather data on phenomena occurring in the far reaches...

Nowadays, real-time applications of Fuzzy Logic in different domains are being increasingly reported. ASIC-based analog hardware becomes an interesting solution for these kinds of applications because it benefits from: savings on silicon surface and power consumption, readily accomplishment with strict timing constraints and cost-effective...

Principles for constructing intelligent systems
Design of Logic-based Intelligent Systems develops principles andmethods for constructing intelligent systems for complex tasks thatare readily done by humans but are difficult for machines. CurrentArtificial Intelligence (AI) approaches rely on various constructsand methods (production...

This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips...