Neural Network Dynamics, J.G. Taylor; E.R. Caianiello; R.M.J. Cotterill; J.
Автор: J.G. Taylor Название: Neural Network Applications ISBN: 3540197729 ISBN-13(EAN): 9783540197720 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Neural Network Applications contains the 12 papers presented at the second British Neural Network Society Meeting (NCM `91) held at King`s College London on 1st October 1991. The meeting was sponsored by the Centre for Neural Networks, King`s College, and the British Neural Network Society, and was also part of the DEANNA ESPRIT programme.
Автор: Anthony, Martin Bartlett, Peter Название: Neural network learning ISBN: 052111862X ISBN-13(EAN): 9780521118620 Издательство: Cambridge Academ Рейтинг: Цена: 7602.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book describes theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. It is intended to be accessible to researchers and graduate students in computer science, engineering, and mathematics.
Описание: This monograph is the continuation and completion of the monograph, "Intelligent Systems: Approximation by Artificial Neural Networks" written by the same author and published 2011 by Springer.The book you hold in hand presents the complete recent and original work of the author in approximation by neural networks.
Автор: Subana Shanmuganathan; Sandhya Samarasinghe Название: Artificial Neural Network Modelling ISBN: 3319284932 ISBN-13(EAN): 9783319284934 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Artificial Neural Networks Applications: An Introduction.- Order in the Black Box: Consistency And Robustness Of Neuron Activation Of Feed Forward Neural Networks And Its Use In Efficient Optimization Of Network Structure.- Artificial Neural Networks as Models of Robustness in Development And Regeneration: Stability of Memory During Morphological Remodeling.- A Structure Optimization Algorithm of Neural Networks For Pattern Learning from Educational Data.- Stochastic Neural Networks for Modelling Random Processes from Observed Data.- Curvelet Interaction with Artificial Neural Networks.- Hybrid Wavelet Neural Network Approaches.-Quantification of Prediction Uncertainty in Artificial Neural Network Models.- Classifying Calpain Inhibitors for The Treatment of Cataracts: A Self Organising Map (SOM) ANN/KM Approach in Drug Discovery.- Improved Ultrasound Based Computer Aided Diagnosis System for Breast Cancer Using Neural Networks Incorporating a Novel Effective Feature - Degree of Central Regularity of Mass.-SOM Clustering and Modelling of Australian Railway Drivers' Sleep, Wake, Duty Profiles.- A Neural Approach to Electricity Demand Forecasting.- Development of Artificial Intelligence Based Regional Flood Estimation Techniques for Eastern Australia.- Artificial Neural Networks in Precipitation Nowcasting: An Australian Case Study.- Construction of Pmx Concentration Surfaces Using Neural Evolutionary Fuzzy Models of Semi Physical Class.- Application of Artificial Neural Network in Social Media Data Analysis: A Case of Lodging Business in Philadelphia.- Sentiment Analysis on Morphologically Rich Languages - An Artificial Neural Network (ANN) Approach.- Predicting Stock Price Movements with News Sentiment: An Artificial Neural Networks Approach.- Modelling Mode Choice of Individual In Linked Trips with Artificial Neural Networks and Fuzzy Representation.- Artificial Neural Network (ANN) Pricing Model for Natural Rubber Products Based on Climate Dependencies.- A Hybrid Artificial Neural Network (ANN) Approach to Spatial and Non-Spatial Attribute Data Mining: A Case Study Experience.
Автор: Yoshiyasu Takefuji Название: Neural Network Parallel Computing ISBN: 079239190X ISBN-13(EAN): 9780792391906 Издательство: Springer Рейтинг: Цена: 28734.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Demonstrates the computational power of neural network computing by solving numerous problems such as N-queen, crossbar switch scheduling, four-coloring and k-colorability, graph planarization and channel routing, RNA secondary structure prediction, knight`s tour, spare allocation, sorting and searching, and tiling.
Автор: Larry R. Medsker Название: Hybrid Neural Network and Expert Systems ISBN: 0792394232 ISBN-13(EAN): 9780792394235 Издательство: Springer Рейтинг: Цена: 24387.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents the basics of expert systems and neural networks, and the important characteristics relevant to the integration of these two technologies. This title demonstrates the use of these hybrid systems in practical situations. It describes guidelines and models to help those who want to develop their own hybrid systems.
Автор: Josef Skrzypek Название: Neural Network Simulation Environments ISBN: 0792394151 ISBN-13(EAN): 9780792394150 Издательство: Springer Рейтинг: Цена: 25149.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Describes examples of neural simulation environments. Various neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. This volume is useful for researchers in both academia and industry, and can be used as a text for advanced courses on the subject.
Автор: Edward J. Rzempoluck Название: Neural Network Data Analysis Using Simulnet™ ISBN: 0387982558 ISBN-13(EAN): 9780387982557 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents an introduction to the analysis of data using neural networks. This book discusses neural network functions such as multilayer feed-forward networks using error back propagation, genetic algorithm-neural network hybrids, generalized regression neural networks, learning quantizer networks, and self-organizing feature maps.
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