Neural Network and Fuzzy Logic Implementation on Lake Ecosystems Muhittin Aslan

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Muhittin Aslan - «Neural Network and Fuzzy Logic Implementation on Lake Ecosystems»

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Modeling is a helpful tool that might be used to predict the Dissolved Oxygen (DO) level of a lake. Most ecological systems are complex and unstable. In case black box models might be essential instead of deterministic ones. DO in Eymir Lake was modeled by using both Artificial Neural Networks (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS). Phosphate, Orthophospate, pH, Chlorophyll-a, Temperature, Alkalinity, Nitrate,Total Kjeldahl Nitrogen, Wind, Precipitation, Air Temperature were the input parameters of ANN and ANFIS. The aims of these modeling studies were: developing models with ANN to predict DO level in Lake Eymir with high fidelity to actual DO data, to compare the success of ANN and ANFIS on DO modeling, to determine the degree of dependence of different parameters on DO. “Matlab R 2007b” software was used. The results indicated that ANN has high prediction capacity of DO and ANFIS has low with respect to ANN. Failure of ANFIS was due to low functionality of... Это и многое другое вы найдете в книге Neural Network and Fuzzy Logic Implementation on Lake Ecosystems (Muhittin Aslan)

Полное название книги Muhittin Aslan Neural Network and Fuzzy Logic Implementation on Lake Ecosystems
Автор Muhittin Aslan
Ключевые слова технические науки, технические науки в целом, техника
Категории Образование и наука, Технические науки
ISBN 9783846537084
Издательство
Год 2011
Название транслитом neural-network-and-fuzzy-logic-implementation-on-lake-ecosystems-muhittin-aslan
Название с ошибочной раскладкой neural network and fuzzy logic implementation on lake ecosystems muhittin aslan