Neural network is a massively parallel distributed processor made of simple processing units which has a natural propensity for storing experimental knowledge and making it available for us. Neural network are a different paradigm for computing. v Von Neumann machines are based on the processing / memory abstraction of human information processing. v Neural networks are based on the parallel architecture of human brain. For the insulation design of high voltage apparatus, electric field optimization technique becomes indispensable tool. Once the neural network learns the relationship between inputs and outputs, the system easily allows to get a target solution. This paper describes about the application of neural network in Electric Field Optimization. In order to realize highly efficient electric field optimization calculation under PC, neural network is introduced and it is available for optimization problem, with electric field analysis technique. In this paper firstly, an algorithm of electric field optimization method using two kinds of neural network is described. Next for evaluating the availability of the method an optimum contour by electric field optimization method based on neural network was calculated. As a result, optimized electrode contour with highly uniform electric field distribution could be obtained. Consequently availability of method is proved. Moreover, it is conformed that once neural network has learned, optimized contour can be found with high speed on personal computer. Hence electric field optimization method based on neural network has advantage in the calculation of efficiency. .

Sir please ppt send kro Electric field optimization high voltage electrode based on a neural network

Abstract
For the insulation design of high voltage apparatus (such as gas insulated switchgear and transformers), the electric field optimization technique becomes an indispensable tool. We developed a highly efficient electric field optimization technique based on a neural network under the personal computer. Once the neural network learns the relationship between inputs and outputs, the system easily allows a target solution to be obtained. The principle of the developed optimization technique is described with the calculation example. Moreover, normalization of learning data is introduced and the applicability is expanded Electric field optimization of high voltage electrode based on neural network