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  SPECIFICATION
NEURAL NETWORK AND GENETIC ALGORITHM IN MATERIAL SCIENCE AND ENGINEERING (hb)2006
Author: BANDYOPADHYAY
ISBN: 0070610991
Year: 2006
Publisher: MCGRAW-HILL EDUCATION ASIA
Category: GENERAL SCIENCES
Edition: 1
Format: Hard Cover
Language: English
Pages: 463
 ABOUT THE TITLE
Neutral Network analyses are a form of regression or classification modelling that are free from the ambiguities of regression analysis. They embody a learning technique that enables to map the hidden input-output relationships accurately. Genetic algorithms, on the other hand, are highly robust & efficient computing techniques for optimisation. They are based on the evolutionary concepts of natural selection & are increasingly making their presence felt in the field of material science.
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 TABLE OF CONTENTS
Plenary Lectures
1. Neural Networks in Material Science: The Importance of Uncertainty
2. Rough –fuzzy Granulation, Case Based Reasoning and Data Mining: Concepts, features and Examples.
3. Practical Optimization Using Evolutionary Methods
4. Artificial Neural Nets, Genetic Algorithms and Multiple Linear Regression as Complementary
Modeling Techniques in Oxygen Steel- Making
5. Interactive Multi-objective Optimization Method NIMBUS Applied to Continuous Casting of Steel
6. Multi-objective Genetic Algorithms: Some Recent Materials Perspectives
7. Mining Data from the Blast Furnace using Neural Networks Evolved by a Multi-objective Genetic Algorithms
8. Do Plants Act As Memory Devices?
Invited Chapters
1. Integration of Fuzzy Techniques and Neural Networks- An Approach for Developing Intelligent Systems.
2. Incorporation of Prior Knowledge in Neural Network and Neuro-fuzzy Materials Modeling
3. Recent Advances in Evolutionary Search and Optimization Algorithms
4. Hybrid Approach to Optimal Packing Using Genetic Algorithm and Coulomb Potential Algorithm
5. On Solving the Energy Eigen Value Problem by Genetic Algorithm
6. Computation Methods and Artificial Intelligence in Materials Science
7. Material Characterization through Neural Network Technique
8. Neural Network Analysis of Steel Plate Processing
9. Finding Better Catalyst for Optimal Control of PPT Polymerization Reactor
Contributory Chapters
1. Artificial Neural Network Models to Predict Workability Parameters for Dynamic Recrystallisation Domain and Instability Regimes
2. Indexing Fly Ashes through Radial basis Function Networks
3. Prediction of a-A1 Dendritic Parameters and Macro Hardness Variation in Permanent Mould Casting of A1-12%Si Alloys using Artificial Neural Networks
4. Learning through Neural Networks: Directions set by the Second Law of Thermodynamics
5. Engineering of Textile Yarns using Artificial Neural Networks
6. Optimization of 15 DOF Tracked Vehicle Model for the Fitment Location of Hydro-Pneumatic Strut using Genetic Algorithm
7. Efficiency of ANN over MTS in classifying HOT Rolled Steel Product using Small Data
8. Systems Parameters Evaluation of a Copper Biosorption Process in Assisted with Artificial Neural Network
9. Prediction of Contact Surface Temperatures between bodies in sliding contact using an Artificial Neural Network
10. Capability of a Feed-Forward Artificial Neural Network to predict Constitutive behavior of type 304L stainless steel during hot torsion.
11. Modelling the Correlation between Chemical Composition and tensile Properties in a 15Cr-15Ni-2.2Mo-Ti Modified Austenitic Stainless Steel using Artificial Neural Network
12. Design of Pearlite Free Air-Cooled Cu Added Ti, B Microalloyed steel from ANN Prediction of CCT Diagrams.
13. Neural Networks Modelling and Multiple Response Optimization of CNC Grinding Process: A Case Study
14. Prediction of Flow Stress in Austentic Stainless Steels under Hot Compression using Artificial Neural Network.
15. Optimization of Process Parameters for GTAW with Filler Wire of 316LN Stainless Steel using Genetic Algorithm
16. Neural Network Application in Wear Particle Analysis: An Integrative Approach of Machine Condition Monitoring.
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