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Öğe A new genetic algorithm with arithmetic crossover to economic and environmental economic dispatch(2005) Yalcinoz T.; Altun H.This paper presents a new genetic approach based on arithmetic crossover for solving the economic dispatch and environmentally constrained economic dispatch problems. Elitism, arithmetic crossover and mutation are used in the genetic algorithm to generate successive sets of possible operating policies. The proposed technique improves the quality of the solution. The employed arithmetic crossover operation takes the real values presented by two individuals and produced new generation on the basis of the arithmetic mean. For economic dispatch problem, the new genetic approach is compared with an improved Hopfield NN approach (IHN), a fuzzy logic controlled genetic algorithm (FLCGA), an advance engineered-conditioning genetic approach (AECGA) and an advance Hopfield NN approach (AHNN). The results of the proposed approach for environmentally economic dispatch are compared with the results of the Taboo Search (TS), the Hopfield NN and a neural networks approach. © 2005 CRL Publishing Ltd.Öğe Determining efficiency of speech feature groups in emotion detection [Ses özni·teli·k gruplarinin duygu tespi·ti·nde etki·nli·kleri·ni·n beli·rlenmesi·](2007) Polat G.; Altun H.Features, extract from speech parameter are frequently used in emotion detection problem. Prosodic, MFCC, LPC and band energy feature groups are commonly used in literature to detect emotion in speech. The aim of the study is to examine the efficiency of these features groups in emotion detection problem using a SVM classifier.Öğe Economic dispatch solution using a genetic algorithm based on arithmetic crossover(2001) Yalcinoz T.; Altun H.; Uzam M.In this paper, a new genetic approach based on arithmetic crossover for solving the economic dispatch problem is proposed. Elitism, arithmetic crossover and mutation are used in the genetic algorithm to generate successive sets of possible operating policies. The proposed technique improves the quality of the solution. The new genetic approach is compared with an improved Hopfield NN approach (IHN) [1], a fuzzy logic controlled genetic algorithm (FLCGA) [2], an advance engineered-conditioning genetic approach (AECGA) [3] and an advance Hopfield NN approach (AHNN) [4]. © 2001 IEEE.Öğe Evalutation of performance of KNN, MLP and RBF classifiers in emotion detection problem [Duygu tespi·t problemi·nde KNN, MLP ve RBF siniflandiricilarin başarimlarinin degerlendi·ri·lmesi·](2007) Polat G.; Altun H.Emotion Detection has gained increasing attention and become an active research area. The problem is solved with improved feature set with different number of feature groups, by employing different classifiers in order to achieve satisfactory recognition rate. In this study, speech related features are employed to evaluate the performance of different classifiers in emotion detection problem.Öğe Hardware emulation of HOG and AMDF based scale and rotation invariant robust shape detection(2012) Peker M.; Altun H.; Karakaya F.In this study, a hardware emulation of HOG and AMDF based scale and rotation invariant robust shape detection for Field Programmable Gate Arrays (FPGA) is described. For this purpose, a robust algorithm with light-computational load has been developed based on features extracted from histogram of oriented gradients (HOG). A normalization scheme is proposed to obtain scale-invariant robust features using HOG algorithm. Also a novel method for shape detection is proposed using Average Magnitude Difference Function (AMDF) which leads to a rotation-invariant and computationally light shape detection method. It is shown that the proposed method is robust against noise as well. Also it is indicated that the performance of the method is highly satisfactory for implementation on real-life industrial problems. © 2012 IEEE.Öğe On the comparison of classifiers' performance in emotion classification: Critiques and suggestions [Duygu siniflandirma problemlerinde siniflandirici performanslarinin karşilaştirilmasi: Eleştiri ve öneriler](2008) Altun H.; Polat G.In literature there is a huge body of references available which compare various classifiers in a particular application. However, the reliability of such a comparison is only valid if the model parameters, performance criteria and training environment are chosen in a fair framework, as successful application of a classifier is dependent on the those parameters. In this study we attempt to answer the questions below in a emotion detection framework, using classifiers such as KNN, SVM, RBF and MLP: Is the success of a classifier enough to make the claim that a classifier is "the best one" in a particular classification task? How is it possible to carry out a fair comparison between classifiers? ©2008 IEEE.Öğe Power economic dispatch using a hybrid genetic algorithm(2001) Yalcinoz T.; Altun H.This letter outlines a hybrid genetic algorithm (HGA) for solving the economic dispatch problem. The algorithm incorporates the solution produced by an improved Hopfield neural network (NN) [1] as a part of its initial population. Elitism, arithmetic crossover, and mutation are used in the GAs to generate successive sets of possible operating policies. The technique improves the quality of the solution and reduces the computation time, and is compared with the classical optimization technique, an improved Hopfield NN approach (IHN) [1], a fuzzy logic controlled GA (FLCGA) [2], and an improved GA (IGA) [3].Öğe Sawability prediction of carbonate rocks from shear strength parameters using artificial neural networks(2006) Kahraman S.; Altun H.; Tezekici B.S.; Fener M.[No abstract available]
