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Due to the highly complex dynamics of hydraulic generator unit, it is hard to develop an accurate analytical expression of the dynamic model, a new adaptive control algorithm based on the learning characteristic of neural network and the function approximation ability of the wavelet is presented in this paper. The control system consists of two wavelet networks, one realizes active identification...
A new approach based on an artificial neural network (ANN) is presented for the forecasting of machining precision of plane grinding. The ANN model is based on GCAOBP (Globally Convergent Adaptive Quick Back Propagation) algorithm. A genetic algorithm (GA) was then applied to the trained ANN model to predict the machining precision. The integrated GCAOBP-GA algorithm was successful in predicting the...
The pressure system of gas collectors of coke oven is a multivariable non-linear process. A model reference adaptive control using the genetic algorithm and the neural network for the pressure system of gas collectors of coke ovens is proposed in this paper. The neural model of the system is identified by the genetic algorithm. Another neural network is trained to learn the inverse dynamics of the...
In order to overcome the limitation such as premature convergence and low global convergence speed of standard genetic algorithm, an improved genetic algorithm named adaptive genetic algorithm simulating human reproduction mode is proposed. The genetic operators of this algorithm include selection operator, help operator, adaptive crossover operator and adaptive mutation operator. The genetic individuals'...
Distributed neural network based on RBF network is used to establish the model of fire detection in view of complexity of fire process and multiplicity of fire environment. For guaranteeing network adaptability, the number of subnets neural network and degree of sample belong to subnet are determined by fuzzy nearest clustering, RBF network is optimized though a improved genetic algorithm by adaptive...
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