A cost forecasting application in the automotive industry by using artificial neural network
2007
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Advisor: Yrd. Doç. Dr. Tarık Çakar
Abstract (EN)
Key Words: Artificial Neural Networks, Back Propagation Algorithm, Cost Forecasting Nowadays, the one of sections which are studied about is Artificial Neural Network (ANN) Models. ANN researchs are related to most field like optimisation, control, image processing, meaning and seperating language, naturel language and forecasting The inspiration of the ANNs is the power, elasticity and sensivity of the Biological Brain. ANN is the Mathematical Model of the nevre cells, sinaps and dentrits which are the main biological components of the Brain. ANN is formed from simple mathematical elements. There are two kinds of learning processes in ANN; supervised and unsupervised. In the supervısed learning process, the output set necessary for each input set, and both of them form the learning set. Usually, learning is used to realize by introduced to these pairs (input/output sets) to ANN. In the learning process, firstly, the input sets are given to ANN, and the output of them are computed. Afterwards, ANN change the weights, until the desired convergence criteria level between the computed outputs and the real outputs is proved. As a result, ANN is trained and the weights at the most suitable values. In this study, An Artificial Intelligence, Structure of the ANN, Components of the ANN, Types of the ANN, Learning Stratigies and Cost Systems were described. And an Application was carried out within context of Cost/Production Time reletion in the ISILSAN MAKİNE SANAYİ factory
Author
Dr. Serkan Bucak
How to Cite
Serkan Bucak (Master Thesis). A cost forecasting application in the automotive industry by using artificial neural network, 2007, Sakarya University.
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