artificial neural networks in real life applications pdf

... should be divided into several sets (training, testing, production, on-line, remaining). The training set is used to adjust the interconnection weights of the MPNN model. The testing set is used ... local minimum far from the global one. During the learning process, the network should be periodically tested on the testing set (not included in the training set) www.intechopen.com Artificial ... feedforward networks. Neural Networks 4, pp. 251-257 Kohonen, T. (1995). Self-organizing maps. Springer, Berlin Kurkova, V. (1992). Kolmogorov’s Theorem and Multilayer Neural Networks, Neural Networks, ...

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... pilling, finger marks, and others. free online editions of InTech Books and Journals can be found at www.intechopen.com Artificial Neural Networks - Industrial and Control Engineering Applications Edited ... application of ANN in textiles and clothing industries will be addressed in last section. Artificial Neural Networks - Industrial and Control Engineering Applications 6 neural net produced ... 2011 Printed in India A free online edition of this book is available at www.intechopen.com Additional hard copies can be obtained from orders@intechweb.org Artificial Neural Networks - Industrial...

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... 14.14GPa which is corresponding to the sintering temperature of 1420°C and the holding time of 80min, while Artificial Neural Networks - Industrial and Control Engineering Applications 158 2.5 ... algorithm in the optimization of hot pressing parameters Artificial Neural Networks - Industrial and Control Engineering Applications 162 The depicting effect of mentioned factors and their interactions ... the input layer to the hidden layer as the transfer function and Artificial Neural Networks - Industrial and Control Engineering Applications 134 input and output vector values are in the...

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... for use in training and testing the neural network. A large training data reduces the risk of under-sampling the nonlinear function, but increases the training time. To improve training, preprocessing ... minmax min VV VV A − − = (4) Training was performed iteratively until the average of sum squared error over all the training patterns was minimized. Experiment were carried out using ... DESIGN ARTIFICIAL NEURAL NETWORK MODEL Neural networks are computer models that mimic the knowledge acquisition and organization skills of the human brain. Since, the characteristics of a neural...

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... of Neural Networks 163 Hazem M. El-Bakry Chapter 9 Applying Artificial Neural Network Hadron - Hadron Collisions at LHC 183 Amr Radi and Samy K. Hindawi Chapter 10 Applications of Artificial Neural ... as a method to realize flexible infor‐ mation processing. Neural networks consider neuron groups of the brain in the creature, and imitate these neurons technologically. Neural networks have some ... Pattern Recognition by Self-organizing Neu‐ ral Networks. The MIT Press. Artificial Neural Networks – Architectures and Applications2 2 16 Artificial Neural Networks Figure 11. The expectation...

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... Artificial Neural Networks - Industrial and Control Engineering Applications 42 organizing feature map neural network. There were ten input neurons corresponding to ten feature indexes and ... 1000 spindle hours; by means of inputs including the processing parameters such as fiber properties, spinning method, and process variables influencing on the yarn properties and spinning performance. ... representing five cluster centers (five pilling grades) by training twenty kinds of samples including colored and patterned pilled worsted fabrics. The total number of iterations in the training...

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... percentage Artificial Neural Networks - Industrial and Control Engineering Applications 88 Sao, K.P. & Jain, A. K. (1995). Mercerization and crimp formation in jute. Indian Journal ... of Intelligent Methods for Evaluating the Apparent Quality of Knitted Fabrics. Engineering Applications of Artificial Intelligence, Vol.23, pp. 217-221, ISSN 0952-1976 Artificial Neural Networks ... by linear connection with linear or nonlinear transformations. The weights were determined by training the neural nets. Once the ANN was trained, it was used for predicting new sets of inputs....

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... trainin g 2 nd ANN trainin g 3 rd ANN trainin g 4 th ANN trainin g 5 th ANN trainin g Randoml y initialized wei g hts & biases Wei g hts & biases from the 1 st trainin g 1 st trainin g ... for inputs too far beyond. 2.1 Neural network training algorithms Artificial neural networks are used as an interdisciplinary tool in many types of nonlinear problems. In order to design a neural ... step training; (b) – in the beginning of the 2 nd step training; (c) – at the end of the training. On each screenshot: the menu on the left defines training parameters; the graph in middle-top...

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... Precipitation in North Carolina. Water, Air, and Soil Pollution, 172, 167. Artificial Neural Networks - Industrial and Control Engineering Applications 176 for testing. For the training stage, ... (as-received) Artificial Neural Networks - Industrial and Control Engineering Applications 168 Botlani-Esfahani. M, Toroghinejad. M. R. and Abbasi. Sh. (2009b) Artificial Neural Network Modeling the ... structures in a coal mine using Artificial Neural Networks. International Journal of Rock Mechanics and Mining Sciences, Volume 45, Issue 6, 999-1006. Wasserman, P.D. (1993). Advanced methods in neural...

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... 150-158(9) Part 3 Food Industry Artificial Neural Networks - Industrial and Control Engineering Applications 232 ANN was investigated, is given in Table 2. In regard to carcass classification ... propagation error. Learning of the network was carried out using 9 data points from the Artificial Neural Networks - Industrial and Control Engineering Applications 228 networks is given by ... near-infrared spectroscopy: Linear and nonlinear calibration methods Journal of the American Oil Chemists' Society, 83(5) Artificial Neural Networks - Industrial and Control Engineering Applications...

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