Learn IT - Books tags genetic

Data Mining Using Grammar Based Genetic Programming and Applications

Springer, 2000

Data mining involves the non-trivial extraction of implicit, previously unknown, and potentially useful information from databases. Genetic Programming (GP) and Inductive Logic Programming (ILP) are two of the approaches for data mining. This book first sets the necessary backgrounds for the reader, including an overview of data mining,...

Algorithms (4th Edition)

Addison Wesley, 2011

This book is intended to survey the most important computer algorithms in use today, and to teach fundamental techniques to the growing number of people in need of knowing them. It is intended for use as a textbook for a second course in computer science, after students have acquired basic programming skills and familiarity with computer...

$Genetics For Dummies (Math & Science)$

Genetics For Dummies (Math & Science)

For Dummies, 2005

Reveals the connections between genetics and specific diseases

Understand the science and the ethics behind genetics

Want to know more about genetics? This non-intimidating guide gets you up to speed on all the fundamentals. From dominant and recessive inherited traits to the DNA double-helix, you get clear explanations in...

Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems

Springer, 2006

This book presents a unique combination of mobile robots and embedded systems, from introductory to intermediate level. It is structured in three parts, dealing with embedded systems (hardware and software design, actuators, sensors, PID control, multitasking), mobile robot design (driving, balancing, walking, and flying robots), and mobile...

Machine Learning in Computer Vision (Computational Imaging and Vision)

Springer, 2005

The goal of computer vision research is to provide computers with humanlike
perception capabilities so that they can sense the environment, understand
the sensed data, take appropriate actions, and learn from this experience in
order to enhance future performance. The field has evolved from the application
of classical pattern...

Adaptive Business Intelligence

Springer, 2006

From the reviews of the first edition:

"In this book the authors explain the science and application of numerous prediction and optimization techniques as well as how these concepts can be used to develop adaptive decision-making systems. The book is suitable for business and IT managers who make decisions in complex industrial and...

Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)

Springer, 2007

Solving multi-objective problems is an evolving effort, and computer science and other related disciplines have given rise to many powerful deterministic and stochastic techniques for addressing these large-dimensional optimization problems. Evolutionary algorithms are one such generic stochastic approach that has proven to be successful and widely...

Probability Theory: A Comprehensive Course (Universitext)

Springer, 2013

This second edition of the popular textbook contains a comprehensive course in modern probability theory. Overall, probabilistic concepts play an increasingly important role in mathematics, physics, biology, financial engineering and computer science. They help us in understanding magnetism, amorphous media, genetic diversity and the perils...

Pattern Recognition, Second Edition

Academic Press, 2003

Pattern recognition is becoming increasingly important in the age of automation and information handling and retrieval.
This book provides the most comprehensive treatment available of pattern recognition, from an engineering perspective. Developed through more than ten years of teaching experience, Pattern Recognition is appropriate for both...

Introduction to Genetic Algorithms

Springer, 2007

The origin of evolutionary algorithmswas an attempt tomimic some of the processes taking place in natural evolution. Although the details of biological evolution are not completely understood (even nowadays), there exist some points supported by strong experimental evidence:

• Evolution is a process operating over chromosomes...

Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems

Springer, 2005

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...

AI Game Engine Programming (Game Development Series)

Charles River, 2004

AI Game Engine Programming provides game developers with the tools and wisdom necessary to create modern game AI engines. It takes programmers from theory to actual game development, with usable code frameworks designed to go beyond merely detailing how a technique might be used. In addition, it surveys the capabilities of the different...

Result Page: 33 32 31 30 29 28 27 26 25 24