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Article Citation - WoS: 1Application of Artificial Neural Network-Based Approach for Calculating Dissolved Oxygen Profiles in Kapulukaya Dam Reservoir(Centre Environment Social & Economic Research Publ-ceser, 2007) Tuzun, Ilhami; Soyupak, Selcuk; Ince, Ozlem; Basaran, GokbenAn Artificial Neural Network (ANN) modelling approach has been shown to be successful in calculating time and space dependent dissolved oxygen (DO) concentration profiles in Kapulukaya Dam Reservoir using limited number of input variables. The variation of inflow to the reservoir with respect to time was significantly high. The reservoir operational levels were relatively stable. The Levenberg-Marquardt algorithm was adopted during training. Preprocessing before training and post processing after simulation steps were the treatments applied to raw data and predictions respectively. Different configurations of Multilayer perceptron neural networks were designed by selecting different combinations of number of hidden layers (single and double) and number of neurons within each of the hidden layers. Generalisation was improved and over-fitting problems were eliminated: Early stopping method was applied for improving generalisation. The conventional model criteria of correlation coefficient (R) and mean square errors (MSE) were adopted to compare model performances. The correlation coefficients between neural network estimates and field measurements were as high as 0.96 for daily and monthly data respectively with experiments that involve double layer neural network structure with 31 neurons within each hidden layer. The study results revealed that the data sizes effect model performances up to a certain level.Article A Comparison of Regression, Neural Network and Fuzzy Logic Models for Estimating Chlorophyll-A Concentrations in Reservoirs(Centre Environment Social & Economic Research Publ-ceser, 2005) Chen, Ding-Geng; Soyupak, SelcukA comparison is conducted in this paper for the multiple linear regression, neural network and fuzzy logic models for their ability to estimate pseudo steady state chlorophyll-a concentrations in a very large and deep dam reservoir that exhibits high spatial and temporal variability. The utilized data set include chlorophyll-a concentrations as an indicator of primary productivity as well as several other water quality variables such as alkalinity, PO4 phosphorus, water temperature and dissolved oxygen concentrations as independent environmental variables. Using the conventional model criteria of correlation coefficient and mean square errors, the fuzzy logic model performed the best with the neural network model better than multiple linear regression model.
