Fr. 189.00

Artificial Neural Network Modelling

English · Hardback

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Description

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This book covers theoretical aspects as well as recent innovativeapplications of Artificial Neural networks (ANNs) in natural, environmental,biological, social, industrial and automated systems.
It presents recent results of ANNs in modelling small, largeand complex systems under three categories, namely, 1) Networks, Structure Optimisation,  Robustness and Stochasticity 2) Advances in Modelling Biological andEnvironmental Systems and 3) Advancesin Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchersin ANN computational modelling.    

List of contents

ArtificialNeural Networks Applications: An Introduction.- Order in the Black Box: ConsistencyAnd Robustness Of Neuron Activation Of Feed Forward Neural Networks And Its UseIn Efficient Optimization Of Network Structure.- ArtificialNeural Networks as Models of Robustness in Development And Regeneration: Stabilityof Memory During Morphological Remodeling.- A StructureOptimization Algorithm of Neural Networks For Pattern Learning from EducationalData.- StochasticNeural Networks for Modelling Random Processes from Observed Data.- Curvelet Interaction with ArtificialNeural Networks.- Hybrid WaveletNeural Network Approaches.-Quantification ofPrediction Uncertainty in Artificial Neural Network Models.- Classifying CalpainInhibitors for The Treatment of Cataracts: A Self Organising Map (SOM) ANN/KM Approachin Drug Discovery.- Improved Ultrasound Based Computer Aided Diagnosis System for BreastCancer Using Neural Networks Incorporating a NovelEffective Feature -  Degree of Central Regularity of Mass.-SOM Clusteringand Modelling of Australian Railway Drivers' Sleep, Wake, Duty Profiles.- A NeuralApproach to Electricity Demand Forecasting.- Development of ArtificialIntelligence Based Regional Flood Estimation Techniques for Eastern Australia.- Artificial NeuralNetworks in Precipitation Nowcasting: An Australian Case Study.- Construction ofPmx Concentration Surfaces Using Neural Evolutionary Fuzzy Models of SemiPhysical Class.- Application of ArtificialNeural Network in Social Media Data Analysis: A Case of Lodging Business in Philadelphia.- Sentiment Analysison Morphologically Rich Languages - An Artificial Neural Network (ANN) Approach.- Predicting StockPrice Movements with News Sentiment: An Artificial Neural Networks Approach.- Modelling ModeChoice of Individual In Linked Trips with Artificial Neural Networks and FuzzyRepresentation.- ArtificialNeural Network (ANN) Pricing Model for Natural Rubber Products Based on ClimateDependencies.- A Hybrid ArtificialNeural Network (ANN) Approach to Spatial and Non-Spatial Attribute Data Mining:A Case Study Experience.

Summary

This book covers theoretical aspects as well as recent innovative
applications of Artificial Neural networks (ANNs) in natural, environmental,
biological, social, industrial and automated systems.
It presents recent results of ANNs in modelling small, large
and complex systems under three categories, namely, 1) Networks, Structure Optimisation,  Robustness and Stochasticity 2) Advances in Modelling Biological and
Environmental Systems
and 3) Advances
in Modelling Social and Economic Systems

The book aims at serving undergraduates, postgraduates and researchers
in ANN computational modelling.    

Product details

Assisted by Samarasinghe (Editor), Samarasinghe (Editor), Sandhya Samarasinghe (Editor), Suban Shanmuganathan (Editor), Subana Shanmuganathan (Editor)
Publisher Springer, Berlin
 
Languages English
Product format Hardback
Released 01.01.2016
 
EAN 9783319284934
ISBN 978-3-31-928493-4
No. of pages 472
Dimensions 156 mm x 251 mm x 32 mm
Weight 912 g
Illustrations VII, 472 p. 187 illus., 124 illus. in color.
Series Studies in Computational Intelligence
Studies in Computational Intelligence
Subjects Natural sciences, medicine, IT, technology > Technology > General, dictionaries

B, Artificial Intelligence, engineering, Computational Intelligence, genetic programming, Supervised and Unsupervised ANNs

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