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Artificial intelligence: approaches, tools and applications.

Artificial intelligence: approaches, tools and applications.
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10022756 Access this eBook online Ebook for Applied Information Technology   GUtech Library . . Available .  
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ISBN 9781620814857
9781613240199
Author Gordon, Brent M.
Title Artificial intelligence : approaches, tools and applications.
Description 1 online resource (179 pages)
Contents ARTIFICIAL INTELLIGENCE: APPROACHES, TOOLS AND APPLICATIONS -- ARTIFICIAL INTELLIGENCE: APPROACHES, TOOLS AND APPLICATIONS -- Library of Congress Cataloging-in-Publication Data -- CONTENTS -- PREFACE -- Chapter 1 APPLICATION OF ARTIFICIAL INTELLIGENCE IN THE UPSTREAM OIL AND GAS INDUSTRY -- ABSTRACT -- 1. NEURAL NETWORKS AND THEIR BACKGROUND -- 1.1. A Short History of Neural Networks -- 1.2. Structure of a Neural Network -- 1.3. Mechanics of Neural Networks Operation -- 2. EVOLUTIONARY COMPUTING -- 2.1. Genetic Algorithms -- 2.2. Mechanism of a Genetic Algorithm -- 3. FUZZY LOGIC -- 3.1. Fuzzy Set Theory -- 3.2. Approximate Reasoning -- 3.3. Fuzzy Inference -- 4. APPLICATIONS IN THE OIL AND GAS INDUSTRY -- 4.1. Neural Networks Applications -- 4.1.1. Reservoir Characterization -- 4.1.2. Virtual Magnetic Resonance Imaging Logs -- 4.2. Genetic Algorithms Applications -- 4.3. Fuzzy Logic Applications -- 4.3.1. Results -- REFERENCES -- Chapter 2 AN ARTIFICIAL INTELLIGENCE APPROACH FOR MODELING AND OPTIMIZATION OF THE EFFECT OF LASER MARKING PARAMETERS ON GLOSS OF THE LASER MARKED GOLD -- ABSTRACT -- 1. INTRODUCTION -- 2. ANFIS, ANNS, GA AND PSO -- 2.1. Adaptive Neuro-Fuzzy Inference System -- 2.1.1. Anfis Architecture -- 2.1.2. ANFIS Learning Algorithm -- 2.2. Artificial Neural Networks -- 2.2.1. Network Types -- 2.2.2. Training Algorithm -- 2.3. Genetic Algorithm -- (a) Population Initialization -- (b) Operators -- (c) Chromosome Evaluation -- 2.4. Particle Swarm Optimization -- 3. INPUT/OUTPUT VARIABLES -- 4. ANFIS AND ANNSIMPLEMENTATION -- 4.1.Model Building Methodology -- 4.2. ANFIS Modeling -- 4.3. ANNs Modeling -- 4.4. Results and Discussion -- 5. GA AND PSO IMPLEMENTATION -- 5.1. Optimization -- 5.2. Optimization Using GA -- 5.3. Optimization Using PSO -- 5.4. Results and Discussion -- 6. METHODOLOGY VALIDATION -- CONCLUSION.
Subject Artificial intelligence
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