Study On Coal And Gas Outburst Prediction Model Based On FWA-ESN

The five major disasters in coal mine including coal and gas outburst.Preventing coal and.gas outburst is the key to ensure safe mining of the coal industry.The mechanism model of gas outburst is not clear yet,and the gas emission amount is nonlinear time series data,which makes the traditional prediction method difficult to deal with the complex nonlinear process of gas outburst.Because of the strong nonlinear fitting ability of neural network,the prediction model of gas emission quantity of neural network can be built to effectively prevent and control gas disasters.In order to improve the prediction accuracy of gas emission,the improved Fireworks Algorithm(WOFWA)was adopted in this paper to optimize the parameter selection process of ESN reserve pool,and a coal and gas outburst prediction system based on WOFWA-ESN network was established.The main research contents of this paper are as follows:Firstly,to improve the optimization ability of the fireworks algorithm,an improved fireworks algorithm based on opposition-based learning and exponential decline strategy was proposed.The algorithm for traditional fireworks algorithm improved basically has two aspects:one is to use opposite learning strategies to generate initial fireworks populations,which at the same time to produce the current individual fireworks and corresponding opposing the fireworks,and then through the comparison and choose better fitness value of fireworks as the initial populations of individuals,thus improve the searching efficiency of the algorithm.Secondly,aiming at the displacement mode of explosive spark in the original FWA,the explosive spark generation mode in the enhanced fireworks algorithm and an inertia weight factor which decreases non-linearly with the increase of iteration times are introduced to improve the optimization accuracy and convergence speed of the algorithm.Four classical complex nonlinear reference functions are selected as test functions to verify the superiority of WOFWA algorithm.Secondly,it's difficult to determine relevant parameters of the reserve pool in the traditional ESN network,which leads to the low accuracy of the prediction model.WOFWA algorithm is used to optimize the setting process of four parameters of the reserve pool,so as to build a gas outburst prediction model based on WOFWA-ESN network.The core of the model construction is to optimize the selection process of ESN reserve pool parameters by using WOFWA algorithm,replacing the objective function of WOFWA algorithm with the training error function for optimization,and then setting the optimal solution obtained by the algorithm as the reserve pool parameter value of ESN network.Experimental results show that compared with other models,the accuracy of the proposed WOFWA-ESN prediction model is significantly improved,thus confirming the effectiveness of the model.Finally,based on the study of WOFWA-ESN algorithm,the system interface was established through PyCharm,the prediction model was called,and the prediction and early warning platform of coal and gas outburst was established to realize the function of gas concentration sequence analysis and outburst prediction and early warning.The platform interface is comfortable and beautiful,the system is convenient to use,practical value and application prospects are good.