Evolutionary heuristic with Gudermannian neural networks for the nonlinear singular models of third kind

Sabir, Zulqurnain; Wahab, Hafiz Abdul

doi:10.1088/1402-4896/ac3c56

Cited by 32 publications

(11 citation statements)

References 39 publications

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“…Cui et al [6] proposed a new three-dimensional quadratic two-wing hidden chaotic system and analyzed the corresponding fractional order multi-wing system by the Adomian decomposition algorithm. Sabir et al [25,26] solved the nonlinear singular EF model of the third kind based on the Gudermannian neural network.…”

Section: 3mentioning

confidence: 99%

Analysis of the short-term game and long-term evolutionary game behaviors of the waste battery remanufacturing market considering government subsidies

Dao-ming

Liu

2023

JIMO

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<p style='text-indent:20px;'>The popularity of new energy vehicles is undoubtedly the best response to the current global call to protect the environment, and the subsequent waste battery recycling and remanufacturing industry is quietly emerging under government promotion. This paper considers the government provides production subsidy or consumption subsidy for a supply chain consisting of a manufacturer and a remanufacturer. The main theme of this research is to explore the impacts of these two types of subsidy on the short-term game and long-term evolutionary game behaviors of the manufacturer and the remanufacturer. To be specific, a Cournot model is built to exam short-term game behaviors in case of production subsidy and consumption subsidy, respectively. Furthermore, we investigate a nonlinear dynamic system to study the long-term evolutionary trend of the supply chain, including long-term operation strategies, the stability of the equilibrium, and how different subsidies impact the system. Results suggest that: (a) the production subsidy is better for higher output of remanufactured products when the eco-design cost of new products is relatively low. And this subsidy works better when consumers are more environmentally conscious. (b) The government is more likely to choose consumption subsidy when consumers have less acceptance of remanufactured products. (c) In the long-term market, the consumption subsidy is more beneficial for the market to remain stable. Nevertheless, excessive adjustments in output by the manufacturer and the remanufacturer can still lead the market to be uncontrolled.</p>

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Section: 3mentioning

confidence: 99%

Analysis of the short-term game and long-term evolutionary game behaviors of the waste battery remanufacturing market considering government subsidies

Dao-ming

Liu

2023

JIMO

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“…the proposed stochastic computing framework can be applied to solve the nonlinear mathematical models arising in fluid dynamics [ [54] , [55] , [56] , [57] ], thermal explosion models [ 58 , 59 ], singular studies [ 60 , 61 ], and food chain systems [ 62 , 63 ].…”

Section: Future Research Directionsmentioning

confidence: 99%

Artificial neural network-based heuristic to solve COVID-19 model including government strategies and individual responses

Botmart

Sabir

Javeed

et al. 2022

Informatics in Medicine Unlocked

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“…The motive of the present work is to provide a computational design using the stochastic scaled conjugate gradient (SCG) neural networks (NNs) called as SCGNNs for the SED with reef ecosystems and conservation estimation. The stochastic frameworks have been used to provide the results of several evolutionary/swarming schemes [28][29][30][31][32][33][34]. The advanced topographies have never been exploited before to solve the SED with reef ecosystems and conservation estimation using the SCGNNs.…”

Section: Density Of Parrotfish Growth Rate Of Macroalgal B Macroalgal...mentioning

confidence: 99%

Computational Stochastic Investigations for the Socio-Ecological Dynamics with Reef Ecosystems

Botmart¹,

Sabir²,

Alwabli³

et al. 2022

Computers, Materials &Amp; Continua

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The motive of this work is to present a computational design using the stochastic scaled conjugate gradient (SCG) neural networks (NNs) called as SCGNNs for the socio-ecological dynamics (SED) with reef ecosystems and conservation estimation. The mathematical descriptions of the SED model are provided that is dependent upon five categories, macroalgae M(v), breathing coral C(v), algal turf T(v), the density of parrotfish P(v) and the opinion of human opinion X (v). The stochastic SCGNNs process is applied to formulate the SED model based on the sample statistics, testing, accreditation and training. Three different variations of the SED have been provided to authenticate the stochastic SCGNNs performance through the statics for training, accreditation, and testing are 77%, 12% and 11%, respectively. The obtained numerical performances have been compared with the Runge-Kutta approach to solve the SED model. The reduction of mean square error (MSE) is used to investigate the numerical measures through the SCGNNs for solving the SED model. The precision of the SCGNNs is validated through the comparison of the results and the absolute error performances. The reliability of the SCGNNs is performed by using the correlation values, state transitions (STs), error histograms (EHs), MSE measures and regression analysis.

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Evolutionary heuristic with Gudermannian neural networks for the nonlinear singular models of third kind

Cited by 32 publications

References 39 publications

Analysis of the short-term game and long-term evolutionary game behaviors of the waste battery remanufacturing market considering government subsidies

Analysis of the short-term game and long-term evolutionary game behaviors of the waste battery remanufacturing market considering government subsidies

Artificial neural network-based heuristic to solve COVID-19 model including government strategies and individual responses

Computational Stochastic Investigations for the Socio-Ecological Dynamics with Reef Ecosystems

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