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a| PREFACE ; 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.
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a| 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 ; 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.
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a| 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 ; APPENDIX A. COMPARISONOF SOMEOF ANFIS MODELING AND ANN MODELINGRESULTSBEFORE AND AFTERCLEANING THE DATA.
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a| 3. PROCEDURE FOR DEVELOPMENT OF KNOWLEDGE BASE SYSTEM (KBS) FOR DESIGN OF METAL STAMPING DIE 3.1. Knowledge Acquisition ; Literature Reviews ; Die Design Experts ; Industrial Visits ; Industrial Brochures ; 3.2. Framing of Production Rules ; 3.3. Verification of Production Rules ; 3.4. Sequencing of Production Rules ; 3.5. Identification of Suitable Hardware and a Computer Language ; 3.6. Construction of Knowledge Base ; 3.7. Choice of Search Strategy ; 3.8. Preparation of User Interface ; 4. AN INTELLIGENT SYSTEM FOR DESIGN OF PROGRESSIVE DIE: INTPDIE.
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a| Preface-- Application of Artificial Intelligence in the Upstream Oil & Gas Industry-- Modeling & Optimization of the Effect of Laser Marking Parameters on Gloss of the Laser Marked Gold Using Artificial Intelligence Approaches-- AI Applications to Metal Stamping Die Design-- Structural Features Simulation on Mechanochemical Synthesis of Al2O3-TiB2 Nanocomposite using ANN with Bayesian Regularization & ANFIS-- An Artificial Intelligence Tool for Predicting Embryos Quality-- Passive System Reliability of the Nuclear Power Plants (NPPs) using Fuzzy Set Theory in Artificial Intelligence-- Emergent Tools in AI-- Neural Networks Applied to Micro-Computed Tomography-- Index.
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b| Artificial Intelligence may be defined as a collection of several analytic tools that collectively attempt to imitate life and has matured to a set of analytic tools that facilitate solving problems which were previously difficult or impossible to solve. In this book, the authors present topical research in the study of the tools and applications of artificial intelligence. Topics discussed include the application of artificial intelligence in the oil and gas industry and in metal stamping die design; using artificial intelligence to predict embryo quality and in biomedical imaging techniques.
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