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    A new genetic algorithm with arithmetic crossover to economic and a environmental economic dispatch
    (C R L PUBLISHING LTD, 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) [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]. The results of the proposed approach for environmentally economic dispatch are compared with the results of the Taboo Search (TS) [5], the Hopfield NN [5] and a neural networks approach [6].
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    Constrained economic dispatch with prohibited operating zones: A Hopfield neural network approach
    (IEEE, 2000) Yalcinoz, T; Altun, H; Hasan, U; Economides, C; Pattichis, CS; Maliotis, G; Papaconstantinou, M; Michaelides, N; Schizas, CN
    The work explores the use of Hopfield neural network for a constrained economic dispatch problem with prohibited operating zones. Yalcinoz and Short [1] discussed a special methodology to improve the performance of Hopfield networks for solving the unconstrained economic dispatch problem. In this paper the improved Hopfield network is applied to the constrained economic dispatch problem. A new mapping process has been used and a computational method for obtaining the weights and biases is described using a slack variable technique for handling inequality constraints. Applying the proposed approach is demonstrated by a 15-unit system with 4 units having prohibited zones.
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    Environmentally constrained economic dispatch via a genetic algorithm with arithmetic crossover
    (IEEE, 2002) Yalcinoz, T; Altun, H
    For electric power generation and dispatching problems, absolute minimum cost is not any more the only criterion to be met. Environmental considerations have become one of the major management concerns. The environmentally constrained economic dispatch problem can be classified as a multi-objective optimization and non-linear programming problem. This paper proposes a solution for environmental economic dispatch problem using modified GA which based on arithmetic crossover operator. The employed arithmetic crossover operation takes the real values presented by two individuals and produced new generation on the basis of the arithmetic mean. Numerical results for two case studies have been presented to illustrate the performance and applicability of the proposed method.
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    Neural learning for articulatory speech synthesis under different statistical characteristics of acoustic input patterns
    (PERGAMON-ELSEVIER SCIENCE LTD, 2003) Altun, H; Curtis, KM; Yalcinoz, T
    Input data representation is highly decisive in neural learning in terms of convergence. In this paper, within an analytical and statistical framework, the effect of the distribution characteristics of the input pattern vectors on the performance of the back-propagation (BP) algorithm is established for a function approximation problem, where parameters of an articulatory speech synthesizer are estimated from acoustic input data. The aim is to determine the optimum statistical characteristics of the acoustic input patterns in order to improve neural learning. Improvement is obtained through a modification of the statistical characteristics of the input data, which reduces effectively the occurrence of node saturation in the hidden layer. (C) 2002 Elsevier Science Ltd. All rights reserved.