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Investigation On Forecasted Mode Of Neural Network And Genetic Algorithm In The Intelligent Monitor System For Coalmine

Posted on:2007-06-25Degree:MasterType:Thesis
Country:ChinaCandidate:X BaiFull Text:PDF
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The key problem solved by the intelligent monitor system for coal mine is how to forecast accurately and timely the distributions and varied trends of the parameters for each working face under the ground such as temperature, humidity, and the concentrations of gas and carbon monoxide et al..In this paper, the artificial neural network and genetic algorithm, especially the theory and the applied condition of the BP neural network combined with genetic algorithm, have been investigated, and an intelligent monitor network system has been proposed. Through the self-studying of the artificial neural network optimized by the genetic algorithm, the system can predict the temperature, humidity, and the concentrations of gas and carbon monoxide; Based on the data measured by Moxinpo Coalmine in Tianfu Coalmine Administrant Bureau, the mathematical model of the intelligent monitor system for coalmine has been established and the gas outburst quantity of some working face has been predicted through emulation technology of MATLAB; Moreover the intellectualized management to the whole system has been achieved through using the source code editing and the forecasting managing software.The emulations and experimental results indicate that the theoretical model combined the neural network and genetic algorithm not only can conquer the disadvantage, which network is prone to enmesh the partial minimal error, but also utilize the powerful artificial intelligence of neural network.; This model provides a new method and idea for the monitor systems management, meanwhile it also offer a new method for solving the problems of the undetermined information processing; This model has powerful studying function, high accuracy, and strong practicability, so it has promoted value.
Keywords/Search Tags:monitor system for coalmine, artificial neural network, genetic algorithm, forecasting, error
PDF Full Text Request
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