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An artificial neural network model for the effects of chicken manure on ground water
Authors:Erdal KaradurmusMustafa Cesmeci  Mehmet Yuceer  Ridvan Berber
Affiliation:a Department of Chemical Engineering, Faculty of Engineering, Hitit University, Corum 19100, Turkey
b Provincial Directorship of Health, Corum 19200, Turkey
c Department of Chemical Engineering, Faculty of Engineering, Inonu University, Malatya 44280, Turkey
d Department of Chemical Engineering, Faculty of Engineering, Ankara University, Ankara 06100, Turkey
Abstract:In the areas where broiler industry is located, poultry manure from chicken farms could be a major source of ground water pollution, and this may have extensive effects particularly when the farms use nearby ground water as their fresh water supply. Therefore the prediction the extent of this pollution, either from rigorous mathematical diffusion modeling or from the perspective of experimental data evaluation bears importance. In this work, we have investigated modeling of the effects of chicken manure on ground water by artificial neural networks. An ANN model was developed to predict the total coliform in the ground water well in poultry farms. The back-propagation algorithm was employed for training and testing the network, and the Levenberg-Marquardt algorithm was utilized for optimization. The MATLAB 7.0 environment with Neural Network Toolbox was used for coding. Given the associated input parameters such as the number of chickens, type of manure pool management and depth of well, the model estimates the possible amount of total coliform in the wells to a satisfactory degree. Therefore it is expected to be of help in future for estimating the ground water pollution resulting from chicken farms.
Keywords:ANN   Poultry farms   Water pollution
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