In this paper,a fractional order model based on the management of waste plastic in the ocean(FO-MWPO)is numerically investigated.The mathematical form of the FO-MWPO model is categorized into three components,waste pl...In this paper,a fractional order model based on the management of waste plastic in the ocean(FO-MWPO)is numerically investigated.The mathematical form of the FO-MWPO model is categorized into three components,waste plastic,Marine debris,and recycling.The stochastic numerical solvers using the Levenberg-Marquardt backpropagation neural networks(LMQBP-NNs)have been applied to present the numerical solutions of the FO-MWPO system.The competency of the method is tested by taking three variants of the FO-MWPO model based on the fractional order derivatives.The data ratio is provided for training,testing and authorization is 77%,12%,and 11%respectively.The exactness of LMQBP-NNs is observed by using the comparative performances of the obtained and the Adams-BashforthMoulton method.To verify the competence,validity,capability,exactness,and consistency of LMQBP-NNs,the performances have been obtained using the regression,state transitions,error histograms,correlation and mean square error.展开更多
基金This work was supported through the Annual Funding track by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia[Project No.AN000128].
文摘In this paper,a fractional order model based on the management of waste plastic in the ocean(FO-MWPO)is numerically investigated.The mathematical form of the FO-MWPO model is categorized into three components,waste plastic,Marine debris,and recycling.The stochastic numerical solvers using the Levenberg-Marquardt backpropagation neural networks(LMQBP-NNs)have been applied to present the numerical solutions of the FO-MWPO system.The competency of the method is tested by taking three variants of the FO-MWPO model based on the fractional order derivatives.The data ratio is provided for training,testing and authorization is 77%,12%,and 11%respectively.The exactness of LMQBP-NNs is observed by using the comparative performances of the obtained and the Adams-BashforthMoulton method.To verify the competence,validity,capability,exactness,and consistency of LMQBP-NNs,the performances have been obtained using the regression,state transitions,error histograms,correlation and mean square error.
