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
•Dissertation
Attack Detection for Cyber Systems and Probabilistic State Estimation in Partially Observable Cyber Environments
Sayantan Guha
- 01 Jan 2016
TL;DR: An approach to estimating the types of states in partially observable cyber systems, which is the first phase of attack detection in cyber systems in partially observable environments, is presented.
8
Generalized Regression Neural Networks in
Time-Varying Environment,Leszek Rutkowski +1 more
- 01 Jan 2004
TL;DR: The generalized regession neural networks studied in this paper are able to follow changes of the best model, i.e., time-varying regression functions, and prove convergence of the GRNN based on general learning theorems presented in Section IV.
8
A Comparative Analysis of Forecasting Methods for Aerobiological Studies
Karuna S. Verma,Apurva K. Pathak +1 more
- 01 Jan 2009
TL;DR: In this article, the authors used ARIMA, MRL and Neural Network Application to forecast air borne fungal spores with an accuracy of 95% for short-term forecasting.
8
Fusion based learning approach for predicting concrete pouring productivity based on construction and supply parameters
TL;DR: In this paper, a machine learner fusion-regression (MLF-R) is used to predict the concrete pouring production rate by considering both construction and supply parameters, and by using a more stable learning method.
8
The Weights Detection of Multi-criteria by using Solver
TL;DR: Novelty in the study is a model to detect pattern of weights criteria and biases on subcontractor selection by transferring the expert's judgment using Solver Application.