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|a Handbook of Genetic Programming Applications
|h [electronic resource] /
|c edited by Amir H. Gandomi, Amir H. Alavi, Conor Ryan.
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| 250 |
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|a 1st ed. 2015.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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|a XI, 593 p. 197 illus., 105 illus. in color.
|b online resource.
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|a computer
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|a 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.
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|a 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.
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|a Artificial intelligence.
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|a Computational intelligence.
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|a Artificial Intelligence.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I21000
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|a Gandomi, Amir H.
|e editor.
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|4 http://id.loc.gov/vocabulary/relators/edt
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|a Alavi, Amir H.
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| 700 |
1 |
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|a Ryan, Conor.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a SpringerLink (Online service)
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