Open AccessBook
Artificial Neural Networks: Theory and Applications
Dan W. Patterson
- 01 Aug 1998
760
TL;DR: This book introduces the newly emerging technology of artificial neural networks and demonstrates its use in intelligent manufacturing systems and presents some of the most promising current research in the design and training of artificial Neural networks with applications in speech and vision.
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Abstract: DOWNLOAD http://bit.ly/1OslRBc Artificial neural networks: theory and applications This comprehensive tutorial on artifical neural networks covers all the important neural network architectures as well as the most recent theory-e.g., pattern recognition, statistical theory, and other mathematical prerequisites. A broad range of applications is provided for each of the architectures. Artificial neural networks for intelligent manufacturing , Cihan H. Dagli, 1994, Technology & Engineering, 469 pages. This book introduces the newly emerging technology of artificial neural networks and demonstrates its use in intelligent manufacturing systems.. Presents some of the most promising current research in the design and training of artificial neural networks (ANNs) with applications in speech and vision, as reported by the. Provides an introduction to the use of neural networks in mechanical engineering applications. This book presents models like Hopfield, Bi-directional Associative Memory, fuzzy. The recent interest in artificial neural networks has motivated the publication of numerous books, including selections of research papers and textbooks presenting the most.
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Citations
Neural network for the estimation of leaf wetness duration: application to a Plasmopara viticola infection forecasting
TL;DR: The aim of this work was to carry out an ANN capable to find out the relationships between the agrometeorological input and LWD and to evaluate the impact of this estimated LWD when integrated in epidemiological simulations.
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A synergetic neural network-genetic scheme for optimal transformer construction
Nikolaos Doulamis,Anastasios Doulamis,Pavlos S. Georgilakis,Stefanos Kollias,Nikos Hatziargyriou +4 more
TL;DR: Application of the proposed neural network-genetic algorithm scheme to the industrial environment indicates a significant reduction in the variation between the actual and the designed transformer iron losses, which leads to a reduction of the production cost since a smaller safety margin can be used for the transformer design.
Breast density pattern characterization by histogram features and texture descriptors
Pedro Cunha Carneiro,Marcelo Lemos Nunes Franco,Ricardo de Lima Thomaz,Ana Claudia Patrocinio +3 more
TL;DR: Texture descriptors have proven to be better than gray levels features at differentiating the breast densities in mammographic images and it was possible to automate the feature selection and the classification with acceptable error rates.