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The time series prediction model based on neural network can perfectly reflect the trend of development of nonlinear system, but the training speed for neural network is very slow, therefore, it is easily prone to local extremum. So we come up with a learning algorithm combining genetic algorithm and BP algorithm for the training of BP neural network, to realize optimization of network structure....
Road pavement performance evaluation and prediction is two most important parts of pavement management system. In order to scientifically and accurately predict the future road pavement situation,evaluation indexes and main influence factors of pavement performance were analyzed. Then functional performance,structure performance, safety performance, and comfortability performance was selected as the...
This paper presents a grey predictive control method for a class of nonlinear systems with unknown input delay. By using BP neural network, the unknown input delay is identified firstly. The system output is then estimated by the grey predictive algorithm. The output feedback control is fulfilled by PID algorithm which is used to tune its three parameters. By means of combining grey predictive algorithm...
Genetic back propagation (BP) neural network is fast, quick, steady in forecasting of traffic flow, and the result has lowly error ability. But it can easily cause premature convergence, and usually the solution we got is local optimal solution. For overcoming those drawbacks of Genetic BP neural network, we add Simulated Annealing Algorithm to the processing of GA, using the ability of Annealing...
With the development of electric power, Large-scale Generating Unit in heat power plant is a system which is Strong-coupling, nonlinear and difficulty to establish accurate model, and etc, those characteristic become more and more prominent. So it is hard to make system gain optimum running effect with conventional control strategy. Aiming at characteristic of generating unit, GA-BP network is used...
The BP neural network algorithm has characteristics of slow convergence speed and local minimum value which could cause the loss of global optimal solution. In order to eliminate the shortcoming of BP neutral network algorithm, genetic algorithm is been put forward to optimize authority value and threshold value of BP nerve network. This paper establishes genetic neural network model. Study has been...
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