Solve the regression evaluation problem by iterating the cost function, and obtain good benefits, a with out complicating the model. It also improves the interpretability of explanatory variables. We apply the fractional differential to gradient descent, and evaluate the overall performance of fractional-order gradient descent with that of integer-order gradient descent. It was identified that the fractional-order features a more quickly convergence price, higher fitting accuracy and lower prediction error than the integer-order. This gives an option system for fitting and forecasting GDP and has a specific reference value.Axioms 2021, ten,9 ofAuthor Contributions: J.W. supervised and led the preparing and execution of this study, proposed the investigation idea of combining fractional calculus with gradient descent, formed the all round study objective, and reviewed, evaluated and revised the manuscript. Based on this study objective, X.W. collected data of economic indicators and applied statistics to make a model and used Python computer software to write codes to analyze information and optimize the model, and finally wrote the first draft. M.F. reviewed, evaluated and revised the manuscript. All authors have read and agreed to the published version with the manuscript. Funding: This work is partially supported by Education Object of Higher Level and Innovative Talents of Guizhou Province ((2016)4006), Significant Analysis Project of Innovative Group in Guizhou Education Department ([2018]012), the Slovak Analysis and Improvement Agency below the contract No. APVV-18-0308 and by the Slovak Grant Agency VEGA No. 1/0358/20 and No. 2/0127/20. Institutional Evaluation Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: https://data.worldbank.org.cn/. Acknowledgments: The authors are grateful for the referees for their careful reading of your manuscript and valuable comments. The authors thank the aid in the editor too. Conflicts of Interest: The authors declare no conflict of interest.
big data and cognitive computingArticleAmifostine thiol Activator effects of Neuro-Cognitive Load on Finding out Transfer Making use of a Virtual Reality-Based Driving SystemUsman Alhaji Abdurrahman 1, , Shih-Ching Yeh 2 , Yunying Wong 3 and Liang WeiSchool of Data Science and Technologies, Fudan University, Shanghai 200433, China; [email protected] Division of Personal computer Science and Information and facts Engineering, National Central University, Taoyuan City 32001, Taiwan; [email protected] College of Psychology, Fudan University, Shanghai 200433, China; [email protected] Correspondence: [email protected] or [email protected]: Abdurrahman, U.A.; Yeh, S.-C.; Wong, Y.; Wei, L. Effects of Neuro-Cognitive Load on Mastering Transfer Using a Virtual Reality-Based Driving System. Huge Information Cogn. Comput. 2021, five, 54. https://doi.org/ 10.3390/bdcc5040054 Academic Editors: Achim Ebert, Peter Dannenmann and Gerrit van der Veer Received: 13 August 2021 Accepted: 7 October 2021 Published: 13 OctoberAbstract: Understanding the methods various persons perceive and apply acquired knowledge, specifically when driving, is definitely an essential area of study. This study introduced a novel virtual reality (VR)-based driving technique to decide the effects of neuro-cognitive load on finding out transfer. Within the experiment, effortless and tricky routes had been introduced to the participants, as well as the VR system is capable of recording eye-gaze, pupil dilation, heart rate, also as driving efficiency information. So.