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INTRODUCTION
Economic dispatch is one of the most important optimization
problems in power system operation and forms the basis of
many application programs. Conventional methods employ
the widely used Lagrangian approach. However in the case of
segmented piece-wise quadratic function, corresponding to the
valve point loading or mixed fuel fired inputs, conventional
approach fails to obtain an optimal solution. In this context,
several approaches have been proposed using non-conventional
optimization approaches, including artif ....etc

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Abstract

This paper presents an adaptive Hopfield neural network (AHNN) based methodology, where the slope of the activation function is adjusted, for finding approximate Pareto solutions for the multi-objective optimization problem of emission and economic load dispatch (EELD).We have placed emphasis on finding solutions quickly, rather than the global Pareto solutions, so that our algorithm can be employed in large on-line power systems where variations in load are quite frequent. To ena ....etc

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Hopfield networks


One of the earliest recurrent neural networks reported in literature was the auto-associator independently described by Anderson and Kohonen. The auto-associator network. All neurons are both input and output neurons, i.e., a pattern is clamped, the network iterates to a stable state, and the output of the network consists of the new activation values of the neurons. The Hopfield network is created by su ....etc

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