Research Article
Towards Achieving Energy Security: Data-Driven Analysis of Electric Vehicle Trends (1997-2024)
Jimoh Afeez Oyeshola*,
Muhammad Muktar Namadi,
Sulaiman Afolabi,
Teslim Oyewale Jimoh
Issue:
Volume 8, Issue 1, June 2024
Pages:
1-12
Received:
15 December 2023
Accepted:
29 December 2023
Published:
11 January 2024
Abstract: The evolution of electric vehicles has emerged among the possible strategies towards achieving energy security. The amount of data produced is growing very fast, providing opportunities for information discovery through big data analysis. This study undertakes a comprehensive data analysis of electric vehicles produced from 1997 to 2024, exploring the development trends on data evaluation system that considers electric vehicle models, types (Battery Electric Vehicles - BEV, Plug-in Hybrid Electric Vehicles - PHEV, Clean Alternative Fuel Vehicle - CAFV Eligibility), electric vehicle range, and base Manufacturer Suggested Retail Price. Data analysis employs k-means as an unsupervised machine learning algorithm for dataset partitioning into clusters. Factor analysis and Principal Component Analysis (PCA) were also employed as supervised learning methods to explore patterns in the dataset without specific emphasis on underlying factors while retaining maximum variance. Further visualizations were carried out using scatterplots, correlation matrices, contingency tables, density plots, and box plots. This study was able to uncover dynamic directions and future industry trends in addressing significant challenges in sustainable development, the study recommends the use of datasets with increased observations spanning the period from 2020 to 2024 with emphasis on electric vehicle prices and their electric ranges. These are essential factors for a comprehensive understanding of the electric vehicle market.
Abstract: The evolution of electric vehicles has emerged among the possible strategies towards achieving energy security. The amount of data produced is growing very fast, providing opportunities for information discovery through big data analysis. This study undertakes a comprehensive data analysis of electric vehicles produced from 1997 to 2024, exploring ...
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Research Article
Near-optimality Conditions for Relaxed and Strict Mean-field Singular FBSDEs
Issue:
Volume 8, Issue 1, June 2024
Pages:
13-28
Received:
4 January 2024
Accepted:
17 January 2024
Published:
24 January 2024
Abstract: In this paper, we investigate the relaxed and strict near-optimality conditions for mean-field singular FBSDEs, where the coefficients depend on the state of the solution process as well as of its expected value. Moreover, the cost functional is also of mean-field type. This makes the control problem time inconsistent in the sense that the Bellman’s optimality principle does not hold. The purpose of this paper is to establish necessary and sufficient conditions of near-optimality for relaxed and strict mean-field singular controls. For strict mean-field singular FBSDEs, whose wellposedness is ensured under the twice continuously differentiable assumptions of coefficients. Then, the moment estimations of variational processes as well as first- order and second-order adjoint processes are presented by using Burkholder-Davis-Gundy inequality. Further, by introducing Hamiltonian function via Ekeland’s variational principle, the necessary near-optimality conditions are established. For relaxed mean-field singular FBSDEs, we first give the definition of admissible set of relaxed singular controls, then use the mapping defined by Dirac measure, we prove that the near-optimal problem of strict singular controls is a particular case of the near- optimal problem of relaxed singular ones. Further, a well known chattering lemma is introduced. By virtue of this famous lemma addition with the stability of trajectories with respect to the control variable and dominated convergence theorem, necessary as well as sufficient near-optimality conditions for relaxed controls are established.
Abstract: In this paper, we investigate the relaxed and strict near-optimality conditions for mean-field singular FBSDEs, where the coefficients depend on the state of the solution process as well as of its expected value. Moreover, the cost functional is also of mean-field type. This makes the control problem time inconsistent in the sense that the Bellman’...
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