Soft Computing in Engineering Design and Manufacturing
(Sprache: Englisch)
Soft Computing has emerged as an important approach towards achieving intelligent computational paradigms where key elements are learning from experience in the presence of uncertainties, fuzzy belief functioos, and ·evolutioo of the computing strategies of...
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Soft Computing has emerged as an important approach towards achieving intelligent computational paradigms where key elements are learning from experience in the presence of uncertainties, fuzzy belief functioos, and ·evolutioo of the computing strategies of the learning agent itself. Fuzzy, neural and evolutionary computing are the three major themes of soft computing. The book presents original research papers dealing with the theory of soft computing and its applicatioos in engineering design and manufacturing. The methodologies have been applied to a large variety of real life problems. Applicatioo of soft computing has provided the opportunity to integrate human like 'vagueness' and real life 'uncertainty' to an otherwise 'hard' computer programme. Now, a computer programme can learn, adapt, and evolve using soft computing. The book identifies the strengths and Iimitatioos of soft cOOlputing techniques, particularly with reference to their engineering applications. The applications range fran design optimisatioo to scheduling and image analysis. Goal optimisatioo with incomplete infmnatioo and under uncertainty is the key to solving real-life problems in design and manufacturing. Soft computing techniques presented in this book address these issues. Computatiooal complexity and efficient implementatioo of these techniques are also major concerns for realising useful industrial applications of soft computing. The different parts in the book also address these issues. The book cootains 9 parts, 8 of which are based 00 papers fran the '2nd On-line World Conference 00 Soft Computing in Engineering Design and Manufacture (WSC2),.
Inhaltsverzeichnis zu „Soft Computing in Engineering Design and Manufacturing “
Artificial Neural Networks Optimization by means of Evolutionary Algorithms.- Fitness Causes Bloat.- Triune Brain Inspired Unifying View of Intelligent Computation.- An Overview of Evolutionary Computing for Multimodal Function Optimisation.- Evolution of Cellular-automaton-based Associative Memories.- Simple Implementation of Genetic Programming by Column Tables.- XCS Classifier System Reliably Evolves Accurate, Complete and Minimal Representations for Boolean Functions.- Designing Neural Networks using a Genetic Rule-based System.- A Neural Network for Real-World Postal Address Recognition.- Neural Processing in Semi-Rigid Connections of Steel Structures.- Evolutionary Design of Neural trees for Heart Rate Prediction.- Hypertrapezoidal Fuzzy Membership Functions for Decision Aiding.- An Iterative Two-phase Approach to Fuzzy System Design.- A fuzzy control course on Internet.- FUZOS - Fuzzy Operating System Support for Information Technology.- Industrial Application of Chaos Engineering.- A Genetic Method for Evolutionary Agents in a Competitive Environment.- Empirically-Derived Population Size and Mutation Rate Guidelines for a Genetic Algorithm with Uniform Crossover.- Analysis of various evolutionary algorithms and the classical dumped least squares in the optimization of the doublet.- Genetic Programming with One-Point Crossover.- Evolutionary Tabu Search for Geometric Primitive Extraction.- Parallel Genetic Algorithms in the Optimization of Composite Structures.- Mijn Mutation Operator for Aerofoil Design Optimisation.- Design Problems with Soft Linear Constraints.- Finding Acceptable Solutions in the Pareto-Optimal Range using Multiobjective Genetic Algorithms.- Handling Probabilistic Uncertainty in Constraint Logic Programming.- A Voxel-based Representation for Evolutionary Shape Optimisation: A case-study of a problem-centred approach to operator design.- A comparison of crossover for rural postman problem with time windows.- On Generating Optimum
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Configurations of Commuter Aircraft using Stochastic Optimisation Methods.- Application of Genetic Algorithms to Packing Problems - A Review.- Generic Evolutionary Design.- Evolving Digital Logic Circuits on Xilinx 6000 Family FPGAs.- A Dialogue Module at the Conceptual Product Design Stage through Genetic Algorithm.- Hard v. soft computing issues in configuration design.- Airframe optimisation based on structural evolution simulation by means of the GA and sequence of numerical models.- Simulated Evolution and Adaptive Search in Engineering Design - Experiences at the University of Cape Town.- A Genetic Algorithm Based Hybrid Channel Allocation Scheme.- Solving Scheduling Problems via Evolutionary Methods for Rule Sequence Optimization.- Estimation of Geometrical Parameters of Drill Point by Combining Genetic Algorithm and Gradient Method.- Adaptability by Behaviour Selection and Observation for Mobile Robots.- Application-Based Time Tabling by Genetic Algorithm.- A novel self-organising neural network for control chart pattern recognition.- Neuro-Fuzzy Control Based on the NEFCON-Model under MATLAB/SIMUUNK.- An Optimal COG Defuzzification Method for a Fuzzy Logic Controller.- Automatic Structuring of Unknown Dynamic Systems.- Takagi-Sugeno Fuzzy Control of Batch Polymerization Reactors.- Genetic Algorithms and Evolution Strategies Applied in Identification and Control: Case Study.- 9: Summary of Discussions.- Keyword Index.- List of Reviewers.
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Bibliographische Angaben
- 1997, 480 Seiten, Maße: 19,3 x 27 cm, Kartoniert (TB), Englisch
- Herausgegeben:Chawdhry, Pravir K.; Roy, Rajkumar; Pant, Raj K.
- Herausgegeben: Pravir K. Chawdhry, Raj K. Pant, Rajkumar Roy
- Verlag: Springer, London
- ISBN-10: 3540762140
- ISBN-13: 9783540762140
- Erscheinungsdatum: 19.11.1997
Sprache:
Englisch
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