Handbook of Genetic Programming Applications / edited by Amir H. Gandomi, Amir H. Alavi, Conor Ryan.

Format:

Book

Contributor:

Gandomi, Amir H., editor.

Alavi, Amir H., editor.

Ryan, Conor, 1972- editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Language:

English

Subjects (All):

Artificial intelligence.

Computational intelligence.

Artificial Intelligence.

Computational Intelligence.

Local Subjects:

Artificial Intelligence.

Computational Intelligence.

Physical Description:

1 online resource (XI, 593 pages) : 197 illustrations, 105 illustrations in color

Edition:

First edition 2015.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2015.

System Details:

text file PDF

Summary:

This contributed volume, written by leading international researchers, reviews the latest developments of genetic programming (GP) and its key applications in solving current real world problems, such as energy conversion and management, financial analysis, engineering modeling and design, and software engineering, to name a few. Inspired by natural evolution, the use of GP has expanded significantly in the last decade in almost every area of science and engineering. Exploring applications in a variety of fields, the information in this volume can help optimize computer programs throughout the sciences. Taking a hands-on approach, this book provides an invaluable reference to practitioners, providing the necessary details required for a successful application of GP and its branches to challenging problems ranging from drought prediction to trading volatility. It also demonstrates the evolution of GP through major developments in GP studies and applications. It is suitable for advanced students who wish to use relevant book chapters as a basis to pursue further research in these areas, as well as experienced practitioners looking to apply GP to new areas. The book also offers valuable supplementary material for design courses and computation in engineering.

Contents:

Graph-Based Evolutionary Art

Genetic Programming for Modelling of Geotechnical Engineering Systems

Application of Genetic Programming in Hydrology

Application of Gene-Expression Programming in Hydraulics Engineering

Genetic Programming applications in Chemical Sciences and Engineering

Application of Genetic Programming for Electrical Engineering Predictive Modeling

Mate Choice in Evolutionary Computation

Genetically Improved Software

Design of Real-Time Computer-Based Systems Using Developmental Genetic Programming

Image Classification with Genetic Programming

On the Application of Genetic Programming for New Generation of Ground Motion Prediction Equations

Evaluation of Liquefaction Potential of Soil Based on Shear Wave Velocity Using Multi-Gene Genetic Programming

Site Characterization Using GP, MARS, and GPR

Use of Genetic Programming Based Surrogate Models to Simulate Complex Geochemical Transport Processes in Contaminated Mine Sites

Potential of Genetic Programming in Hydroclimatic Prediction of Droughts

Application of Genetic Programming for Uniaxial and Multiaxial Modeling of Concrete

Genetic Programming for Mining Association Rules in Relational Database Environments

Evolving GP Classifiers for Streaming Data Tasks with Concept Change and Label Budgets

A New Evolutionary Approach to Geotechnical and Geo-environmental Modelling

Application of GFA-MLR and G/PLS Techniques in QSAR/QSPR Studies with Application in Medicinal Chemistry and Predictive Toxicology

Trading Volitility using Highly Accurate Symbolic Regression

GPTIPS 2: An Open-Source Software Platform for Symbolic Data Mining

eCrash: A Genetic Programming-Based Testing Tool for Object-Oriented Software.

Other Format:

Printed edition:

ISBN:

978-3-319-20883-1

9783319208831

Access Restriction:

Restricted for use by site license.