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Numerical Computational Heuristic Through Morlet Wavelet Neural Network for Solving the Dynamics of Nonlinear SITR COVID-19
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作者 Zulqurnain Sabir Abeer S.Alnahdi +4 位作者 Mdi Begum Jeelani Mohamed A.Abdelkawy Muhammad Asif Zahoor Raja Dumitru Baleanu Muhammad Mubashar Hussain 《Computer Modeling in Engineering & Sciences》 SCIE EI 2022年第5期763-785,共23页
The present investigations are associated with designing Morlet wavelet neural network(MWNN)for solving a class of susceptible,infected,treatment and recovered(SITR)fractal systems of COVID-19 propagation and control.... The present investigations are associated with designing Morlet wavelet neural network(MWNN)for solving a class of susceptible,infected,treatment and recovered(SITR)fractal systems of COVID-19 propagation and control.The structure of an error function is accessible using the SITR differential form and its initial conditions.The optimization is performed using the MWNN together with the global as well as local search heuristics of genetic algorithm(GA)and active-set algorithm(ASA),i.e.,MWNN-GA-ASA.The detail of each class of the SITR nonlinear COVID-19 system is also discussed.The obtained outcomes of the SITR system are compared with the Runge-Kutta results to check the perfection of the designed method.The statistical analysis is performed using different measures for 30 independent runs as well as 15 variables to authenticate the consistency of the proposed method.The plots of the absolute error,convergence analysis,histogram,performancemeasures,and boxplots are also provided to find the exactness,dependability and stability of the MWNN-GA-ASA. 展开更多
关键词 Nonlinear SITR model morlet function artificial neural networks RUNGE-KUTTA TREATMENT genetic algorithm TREATMENT active-set
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Modeling of coal consumption rate based on wavelet neural network
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作者 Xiaoqiang Wen Shuguang Jian 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2017年第3期78-92,共15页
In this paper,two wavelet neural network(WNN)frames which depend on Morlet wavelet function and Gaussian wavelet function were established.In order to improve the efficiency of model training,the momentum term was app... In this paper,two wavelet neural network(WNN)frames which depend on Morlet wavelet function and Gaussian wavelet function were established.In order to improve the efficiency of model training,the momentum term was applied to modify the weights and thresholds,and the output of the network was summed up by function transformation of output layer nodes.When the Gaussian Wavelet Neural Networks(GWNN)and Morlet Wavelet Neural Networks(MWNN)were applied to coal consumption rate(CCR)estimation in a thermal power plant,the results confirmed their potency in function approximation.In addition,the influence of learning rate on the models was also discussed through the orthogonal experiment. 展开更多
关键词 Wavelet neural network morlet wavelet function Gaussian wavelet function ESTIMATION coal consumption rate
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