Abstract
An Artificial Neural Network is an information processing system that has certain performance characteristics in common with biological neural networks. Artificial neural networks have been developed as generalizations of mathematical models of human cognition or neural biology [16]. The basic processing elements of neural networks are called neurons. Neuron performs as summing and nonlinear mapping junctions. In some cases they can be considered as threshold units that fire when their total input exceeds certain bias levels. Neurons usually operate in parallel and are configured in regular architectures. The neurons are generally arranged in parallel to form layers. Strength of the each connection is expressed by a numerical value called a weight, which can be modified [17].
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© 2013 Springer-Verlag Berlin Heidelberg
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Ünal, M., Ak, A., Topuz, V., Erdal, H. (2013). Artificial Neural Networks. In: Optimization of PID Controllers Using Ant Colony and Genetic Algorithms. Studies in Computational Intelligence, vol 449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32900-5_2
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DOI: https://doi.org/10.1007/978-3-642-32900-5_2
Publisher Name: Springer, Berlin, Heidelberg
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