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Full-Text Articles in Physical Sciences and Mathematics
Applying Gmdh-Type Neural Network And Genetic Algorithm For Stock Price Prediction Of Iranian Cement Sector, Saeed Fallahi, Meysam Shaverdi, Vahab Bashiri
Applying Gmdh-Type Neural Network And Genetic Algorithm For Stock Price Prediction Of Iranian Cement Sector, Saeed Fallahi, Meysam Shaverdi, Vahab Bashiri
Applications and Applied Mathematics: An International Journal (AAM)
The cement industry is one of the most important and profitable industries in Iran and great content of financial resources are investing in this sector yearly. In this paper a GMDH-type neural network and genetic algorithm is developed for stock price prediction of cement sector. For stocks price prediction by GMDH type-neural network, we are using earnings per share (EPS), Prediction Earnings Per Share (PEPS), Dividend per share (DPS), Price-earnings ratio (P/E), Earnings-price ratio (E/P) as input data and stock price as output data. For this work, data of ten cement companies is gathering from Tehran stock exchange (TSE) in …
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose a novel method for unsupervised change detection in multi-temporal satellite images by using multiobjective cost function optimization via genetic algorithm (GA). The spatial image grid of the input multi-temporal satellite images is divided into two distinct regions, representing ``changed'' and ``unchanged'' regions between input images, via the intermediate change detection mask produced by the GA. The dissimilarity of pixels of ``changed'' regions and similarity of pixels of ``unchanged'' regions between input multi-temporal images are measured using image quality metrics which consider correlation, spectral distortion, radiometric distortion, and contrast distortion. The contextual information of each pixel …
Using Learning Automata For Multi-Objective Generation Dispatch Considering Cost, Voltage Stability And Power Losses, Ari̇f Karakaş, Celal Kocatepe, Fangxing Li
Using Learning Automata For Multi-Objective Generation Dispatch Considering Cost, Voltage Stability And Power Losses, Ari̇f Karakaş, Celal Kocatepe, Fangxing Li
Turkish Journal of Electrical Engineering and Computer Sciences
The economical and secure operation of power systems has significant importance. Due to technical limitations, the best economical operation point is not always the desired operating point for system stability or power losses. In this study, first, the most economical operating point is obtained by solving the non-linear, network-constrained economic dispatch problem using a genetic algorithm. Then, the system voltage stability is analyzed to compare the different possible operating points using V-Q sensitivity analysis. The power losses, obtained for various operating points, are considered the third objective function. Finally, these 3 aspects of cost, voltage stability, and power losses are …