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Artificial intelligence : approaches, tools, and applications /
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York :
Nova Science Publishers,
[2011]
|
| Colección: | Scientific revolutions series.
Computer science, technology and applications. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 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.
- 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.
- 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.
- 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.