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Artificial Neural Nets and Genetic Algorithms: "Proceedings Of The International Conference In Innsbruck, Austria, 1993" - Brossura

 
9783211824597: Artificial Neural Nets and Genetic Algorithms: "Proceedings Of The International Conference In Innsbruck, Austria, 1993"

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Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are the subjects of contributions to this volume. There are contributions reporting theoretical developments in the design of neural networks, and in the management of their learning. In a number of contributions, applications to speech recognition tasks, control of industrial processes as well as to credit scoring, and so on, are reflected. Regarding genetic algorithms, several methodological papers consider how genetic algorithms can be improved using an experimental approach, as well as by hybridizing with other useful techniques such as tabu search. The closely related area of classifier systems also receives a significant amount of coverage, aiming at better ways for their implementation. Further, while there are many contributions which explore ways in which genetic algorithms can be applied to real problems, nearly all involve some understanding of the context in order to apply the genetic algorithm paradigm more successfully. That this can indeed be done is evidenced by the range of applications covered in this volume.

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Contenuti

Workshop Summary.- Artificial Neural Networks.- The Class of Refractory Neural Nets.- The Boltzmann ECE Neural Network: A Learning Machine for Estimating Unknown Probabilty Distributions.- The Functional Intricacy of Neural Networks — A Mathematical Study.- Evolving Neural Feedforward Networks.- An Example of Neural Code: Neural Trees Implemented by LRAAMs.- Kolmogorov’s Theorem: From Algebraic Equations and Nomography to Neural Networks.- Output Zeroing Within a Hopfield Network.- Evolving Recurrent Neural Networks.- Speeding Up Back Propagation by Partial Evaluation.- A New Min-Max Optimization Approach for Fast Learning Convergence of Feed-Forward Neural Networks.- Evolution of Neural Net Architectures by a Hierarchical Grammar-Based Genetic System.- Interactive Classification Through Neural Networks.- Visualisation of Neural Network Operation for Improving the Performance Optimization Process.- Identification of Nonlinear Systems Using Dynamical Neural Networks: A Singular Perturbation Approach.- The Polynomial Method Augmented by Surpervised Training for Hand Printed Character Recognition.- Analysis of Electronic Nose Data Using Logical Neurons.- Neural Tree Network Based Electronic Nose.- Lime Kiln Process Identification and Control: A Neural Network Approach.- Application of Neural Networks to Automated Brain Maturation Study.- A Neuron Model for Centroid Estimation in Clustering Problems.- Systolic Pattern Recognition Based on Neural Network Algorithm.- Neural Networks Versus Image Pyramids.- Application of Neural Networks to Gradient Search Techniques in Cluster Analysis.- LVQ-Based On-Line EEG Classification.- A Scalable Neural Architecture Combining Unsupervised and Suggestive Learning.- Stability Analysis of The Separation of Sources Algorithm: Application to an Analogue Hardware.- Learning with Mappings and Input-Orderings Using Random Access Memory-Based Neural Networks.- New Preprocessing Methods for Holographic Neural Networks.- A Solution for the Processor Allocation Problem: Topology Conserving Graph Mapping by Self-Organization.- Using a Synergetic Computer in an Industrial Classification Problem.- Connectionist Unifying Prolog.- Plausible Self-Organizing Maps for Speech Recognition.- Application of Neural Networks to Fault Diagnosis for HVDC Systems.- The Hopfield and Hamming Networks Applied to the Automatic Speech Recognition of the Five Spanish Vowels.- Speaker-Independent Work Recognition with Backpropagation Networks.- A Neural Learning Framework for Advisory Dialogue Systems.- Symbolic Learning in Connectionist Production Systems.- An Evaluation of Different Network Models in Machine Vision Applications.- Combined Application of Neural Network and Artificial Intelligence Methods to Automatic Speech Recognition in a Continuous Utterance.- A Neural Network Based Control of a Simulated Biochemical Process.- Applications of Neural Networks for Filtering.- A Recurrent Neural Network for Time-Series Modelling.- The Application of Neural Sensors to Fermentation Processes.- An Application of Unsupervised Neural Networks Based Condition Monitoring System.- A Report of the Practical Application of a Neural Network in Financial Service Decision Making.- Performance Evaluation of Neural Networks Applied to Queueing Allocation Problem.- Real-Data-Based Car-Following with Adaptive Neural Control.- Genetic Algoritms.- An Adaptive Plan.- Mapping Parallel Genetic Algorithms on WK-Recursive Topologies.- Diversity and Diversification in Genetic Algorithms: Some Connections with Tabu Search.- Clique Partitioning Problem and Genetic Algorithms.- Self-Organization of Communication in Distributed Learning Classifier Systems.- Design of Digital Filters with Evolutionary Algorithms.- An Empirical Study of Population and Non-Population Based Search Strategies for Optimizing a Combinatorical Problem.- The Parallel Genetic Cellular Automata: Application to Global Function Optimization.- Optimization of Genetic Algorithms by Genetic Algorithms.- Achieving Self-Stabilization in a Distributed System Using Evolutionary Strategies.- Improving Simple Classifier Systems to Alleviate the Problems of Duplication, Subsumption and Equivalence of Rules.- Genetic Algorithm Selection of Features for Hand-Printed Character Identification.- Analysis and Comparison of Different Genetic Models for the Clustering Problem in Image Analysis.- Evolving Recurrent Dynamical Networks for Robot Control.- Genetic Algorithms for On-Line System Identification.- Evolvable Hardware Genetic Programming of a Darwin Machine.- A Fast Genetic Algorithm with Sharing Scheme Using Cluster Analysis Methods in Multimodal Function Optimization.- An Interactive Genetic Algorithm for Controller Parameter Optimization.- Robustness and Evolution in an Adaptive System Application on Classification Task.- On Robot Navigation Using a Genetic Algorithm.- Genetic Algorithms and Classifier Systems in Simulating a Cooperative behavior.- Dynamic Management of the Specificity in Classifier Systems.- Dynamic Sequencing of a Multi-Processor System: A Genetic Algorithm Approach.- Genetic Algorithms Versus Tabu Search for Instruction Scheduling.- A Massively Parallel Genetic Algorithm on the MasPar MP 1.- Standard Cell Routing Optimization Using a Genetic Algorithm.- Efficient Parallel Learning in Classifier Systems.- Co-Evolving Communicating Classifier Systems for Tracking.- On Finding Optimal Potential Customers from a Large Marketing Database — A Genetic Algorithm Approach.- Structural Design for Enhanced Noise Performance Using Genetic Algorithms and Other Optimization Techniques.- The Concrete Arch Dam, an Evolutionary Model of the Design Process.- The GENIE Project — A Genetic Algorithm Application to a Sequencing Problem in the Biological Domain.- Hybrid Genetic Algorithms for the Traveling Salesman Problem.- Using a Genetic Algorithm to Investigate Taxation Induced Interactions in Capital Budgeting.- Fast Sequential and Parallel Implementation of Genetic Algorithms Using the GAmeter Toolkit.- Locating Pressure Control Elements for Leakage Minimisation in Water Supply Networks by Genetic Algorithms.- A ‘Noise Gene’ for Econets.- A Solution to Global Illumination by Recursive Genetic Algorithms.- NeXTGene: A Graphical User-Interface for GENESIS under NeXTStep.- Using Genetic Algorithms in Economic Modelling: The Many-Agents Approach.- GIRS: A Genetic Approach to Information Retrieval.- Classifier System in Traffic Management.- Artificial Neural Networks & Genetic Algorithms.- Genetic Search for Optimal Representations in Neural Networks.- Searching Among Search Spaces: Hastening the Genetic Evolution of Feedforward Neural Networks.- Representation and Evolution of Neural Networks.- Using a Genetic Algorithm to Tune Potts Neural Networks.- Genetic Weight Optimization of a Feedforward Neural Network Controller.- Using a Genetic Algorithm to Find the Rules of a Neural Network.- MLP Optimal Topology via Genetic Algorithms.- Application of Genetic Algorithms to the Construction of Topologies for Multilayer Perceptrons.- Genetic Algorithms as Heuristics for Optimizing ANN Design.- Genetic Algorithm Design of Neural Net Based Electronic Nose.- Circuits of Production Rule GenNets. The Genetic Programming of Artificial Nervous Systems.- Neuromimetic Algorithms Processing: Tools for Design of Dedicated Architectures.- Towards the Development of Cognitive Maps in Classifier Systems.- Genetic Optimization of Neural Network Architectures for Colour Recipe Predicti.- Use of Genetic Algorithms for Optimal Topology Determination in Back Propagation Neural Networks.- Counting and Naming Connection Islands on a Grid of Conductors.

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9780387824598: Artificial Neural Nets and Genetic Algorithms: Proceedings of the International Conference in Innsbuck, Austria, 1993

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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the proces. Codice articolo 4488731

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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are the subjects of contributions to this volume.There are contributions reporting theoretical developments in the design of neural networks, and in the management of their learning. In a number of contributions, applications to speech recognition tasks, control of industrial processes as well as to credit scoring, and so on, are reflected.Regarding genetic algorithms, several methodological papers consider how genetic algorithms can be improved using an experimental approach, as well as by hybridizing with other useful techniques such as tabu search. The closely related area of classifier systems also receives a significant amount of coverage, aiming at better ways for their implementation. Further, while there are many contributions which explore ways in which genetic algorithms can be applied to real problems, nearly all involve some understanding of the context in order to apply the genetic algorithm paradigm more successfully. That this can indeed be done is evidenced by the range of applications covered in this volume. Codice articolo 9783211824597

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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain understanding of important natural processes. By focussing on the process models rather than the processes themselves, significant new computational techniques have evolved which have found application in a large number of diverse fields. This diversity is reflected in the topics which are the subjects of contributions to this volume.There are contributions reporting theoretical developments in the design of neural networks, and in the management of their learning. In a number of contributions, applications to speech recognition tasks, control of industrial processes as well as to credit scoring, and so on, are reflected.Regarding genetic algorithms, several methodological papers consider how genetic algorithms can be improved using an experimental approach, as well as by hybridizing with other useful techniques such as tabu search. The closely related area of classifier systems also receives a significant amount of coverage, aiming at better ways for their implementation. Further, while there are many contributions which explore ways in which genetic algorithms can be applied to real problems, nearly all involve some understanding of the context in order to apply the genetic algorithm paradigm more successfully. That this can indeed be done is evidenced by the range of applications covered in this volume.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 756 pp. Englisch. Codice articolo 9783211824597

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Condizione: New. Includes contributions reporting theoretical developments in the design of neural networks and in the management of their learning. In a number of contributions, applications to speech recognition tasks, control of oil industrial processes, as well as to credit scoring, are reflected. Editor(s): Reeves, C. R.; Steele, N.C. Num Pages: 737 pages, 403 black & white illustrations, biography. BIC Classification: UYAM; UYQM; UYQN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 279 x 210 x 38. Weight in Grams: 1832. . 1993. Paperback. . . . . Codice articolo V9783211824597

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