Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Introduction to Genetic Algorithms
This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.
PRINCIPLES OF SOFT COMPUTING (With CD )
Market_Desc: · B. Tech (UG) students of CSE, IT, ECE· College Libraries· Research Scholars· Operational Research· Management Sector Special Features: Dr. S. N. Sivanandam has published 12 books· He has delivered around 150 special lectures of different specialization in Summer/Winter school and also in various Engineering colleges· He has guided and co guided 30 PhD research works and at present 9 PhD research scholars are working under him· The total number of technical publications in International/National Journals/Conferences is around 700· He has also received Certificate of Merit 2005-2006 for his paper from The Institution of Engineers (India)· He has chaired 7 International...
Introduction to Fuzzy Logic using MATLAB
This book provides a broad-ranging, but detailed overview of the basics of Fuzzy Logic. The fundamentals of Fuzzy Logic are discussed in detail, and illustrated with various solved examples. The book also deals with applications of Fuzzy Logic, to help readers more fully understand the concepts involved. Solutions to the problems are programmed using MATLAB 6.0, with simulated results. The MATLAB Fuzzy Logic toolbox is provided for easy reference.
Control Systems Engineering Using Matlab
Control Systems Engineering using MATLAB provides students with a concise introduction to the basic concepts in automatic control systems and the various methods of solving its problems. Designed to comfortably cover two academic semesters, the style and form of the book makes it easily comprehensible for all engineering disciplines that have control system courses in their curricula. The solutions to the problems are programmed using MATLAB 6.0 for which the simulated results are provided. The MATLAB Control Systems Toolbox is provided in the Appendix for easy reference. The book would be useful as a textbook to undergraduate students and as quick reference for higher studies.
Problems & Solutions In Control System Engineering
This text provides problems and solutions of the basic control system concepts. It gives a broad and in-depth overview of solving control system problems.There are sixteen chapters in the book. Chapter 1 introduces the reader to automatic control systems. Chapters 2 to 12 contain problems involving feedback control theory and the frequency domain tools of control system design. Problems on non-linear systems and state space analysis are solved in chapters 13 and 14 respectively. Chapter 15 covers the discrete control system concept. The MATLAB based control system design toolbox and the solutions to the problems programmed in MATLAB environment are discussed in chapter 16.This book will be useful for all engineering disciplines that have control system courses in their curriculum. The topics included can be covered in two academic semesters. The main objective of the book is to enable the students to clearly understand the method of solving control system problems.
PRINCIPLES OF SOFT COMPUTING, 2ND ED (With CD )
Market_Desc: · B. Tech (UG) students ofü CSEü ITü ECE· College Libraries· Research Scholars· Operational Research· Management Sector Special Features: · Detailed explanation of soft computing concepts.· Study on various artificial neural network architecture.· Description on fuzzy logic techniques.· Introduction to genetic algorithm and its types for solving optimization problems.· Numerous artificial neural network, fuzzy logic and genetic algorithm problems.· Implementation of soft computing techniques using C and C++.· Simulated solutions for soft computing concepts using MATLAB package.· Application case studies on soft computing techniques on emerging fields.· Various h...
NEURAL NETWORKS, FUZZY LOGIC AND GENETIC ALGORITHM
This book provides comprehensive introduction to a consortium of technologies underlying soft computing, an evolving branch of computational intelligence. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. The hybridization of the technologies is demonstrated on architectures such as Fuzzy-Back-propagation Networks (NN-FL), Simplified Fuzzy ARTMAP (NN-FL), and Fuzzy Associative Memories. The book also gives an exhaustive discussion of FL-GA hybridization. Every architecture has been discussed in detail through illustrative examples...
Deterministic Artificial Intelligence
Kirchhoff’s laws give a mathematical description of electromechanics. Similarly, translational motion mechanics obey Newton’s laws, while rotational motion mechanics comply with Euler’s moment equations, a set of three nonlinear, coupled differential equations. Nonlinearities complicate the mathematical treatment of the seemingly simple action of rotating, and these complications lead to a robust lineage of research culminating here with a text on the ability to make rigid bodies in rotation become self-aware, and even learn. This book is meant for basic scientifically inclined readers commencing with a first chapter on the basics of stochastic artificial intelligence to bridge readers...
Concepts of Soft Computing
This book discusses soft computing, which provides an efficient platform to deal with imprecision, uncertainty, vagueness and approximation in order to attain robustness and reliable computing. It explores two major concepts of soft computing: fuzzy set theory and neural networks, which relate to uncertainty handling and machine learning techniques respectively. Generally, fuzzy sets are considered as vague or uncertain sets having membership function lying between 0 and 1, and ANN is a type of artificial intelligence that attempts to imitate the way a human brain works by configuring specific applications, for instance pattern recognition or data classification, through learning processes. The book also presents C/MATLAB programming codes related to the basics of fuzzy set, interval arithmetic and ANN in a concise, practical and adaptable manner along, with simple examples and self-validation unsolved practice questions in few cases
