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Parameters Estimation Of A Fan System Using Artificial Neural Networks (Anns),, D. K. Chaturvedi
Parameters Estimation Of A Fan System Using Artificial Neural Networks (Anns),, D. K. Chaturvedi
D. K. Chaturvedi Dr.
Electric Fans are very commonly used in the industries, domestic applications and in tunnels for cooling and ventila-tion purposes. Fan parameters estimation is an important task as far as the reliable operation of a fan system is con-cerned. Basically, a fan is mainly consisting of a single phase induction motor and therefore fan system parameters are essentially the electrical parameters e.g. resistances, reactances and some load parameters (fan blades).These parame-ters often change under varying operating conditions and the knowledge of these parameters is necessary to have opti-mum and efficient operation of the system. Therefore, fan system parameters are required to …
Ann /Gn Programs, D. K. Chaturvedi
Ann /Gn Programs, D. K. Chaturvedi
D. K. Chaturvedi Dr.
The file contains programms of multi layer feedforward backpropagation ANN, GN and their varients.
Artificial Neural Network Learning Using Improved Genetic Algorithms, D. K. Chaturvedi
Artificial Neural Network Learning Using Improved Genetic Algorithms, D. K. Chaturvedi
D. K. Chaturvedi Dr.
The feedforward back-propagation artificial neural networks (ANN) are widely used to control the various industrial process, for modelling, simulation of systems and forecasting. The backpropagation learning has various drawbacks such as slowness in learning, stuck in local minima, requies functional derivative of aggregation function and thresholding function to minimize error function. Various researchers have suggested a number of improvement in simple back-propagation learning algorithm developed by Widrow and Holf in 1956. In this paper, a program is developed for feedforward artificial neural network with genetic algorithm (GA) as the learning mechanism to overcome some of the disadvantages of back-propagation learning …