推进核能预测:探索回归建模技术以提高准确性

IF 2.6 3区 工程技术 Q1 NUCLEAR SCIENCE & TECHNOLOGY
Anjali Nighoskar, Preeti Chaurasia, Nagendra Singh
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引用次数: 0

摘要

对可持续和可靠能源的迫切需求激发了人们对精确预测核能发电量的更大兴趣。这项研究利用复杂的回归建模方法(即 XGBoost),通过国内生产总值 (GDP) 等经济指标来预测核能发电量。通过研究各地核能产量和 GDP 的历史数据,对每个模型的预测准确性进行了评估。这里使用了均方误差 (MSE) 和判定系数 (R2) 等指标来分析其有效性。研究结果表明,XGBoost 模型优于标准回归方法,显示出更大的 R2 值和更低的 MSE 分数。此外,这些发现对能源政策制定的影响也为今后的能源预测研究提供了可能的方向。这项研究为能源规划者和决策者提供了有用的见解,使他们能够更深刻地理解经济指标与核能发电之间的复杂关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancing nuclear energy forecasting: Exploring regression modeling techniques for improved accuracy
The urgent requirement for sustainable and dependable energy sources has stimulated an increased fascination with precisely forecasting nuclear energy generation. This work utilizes sophisticated regression modeling approaches, namely XGBoost, to predict nuclear energy generation by leveraging economic indices such as Gross Domestic Product (GDP). Each model's prediction accuracy has been evaluated by examining historical data on nuclear energy output and GDP from various locations. Here, measures such as mean squared error (MSE) and coefficient of determination (R2) to analyze their effectiveness have been used. The results of this study demonstrate that the XGBoost model outperforms standard regression approaches, showing greater R2 values and lower MSE scores. Furthermore, the consequences of these discoveries for the development of energy policy offer possible directions for future study in energy forecasting. This study provides useful insights for energy planners and policymakers, enabling a more profound comprehension of the complex relationship between economic indicators and nuclear energy generation.
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来源期刊
Nuclear Engineering and Technology
Nuclear Engineering and Technology 工程技术-核科学技术
CiteScore
4.80
自引率
7.40%
发文量
431
审稿时长
3.5 months
期刊介绍: Nuclear Engineering and Technology (NET), an international journal of the Korean Nuclear Society (KNS), publishes peer-reviewed papers on original research, ideas and developments in all areas of the field of nuclear science and technology. NET bimonthly publishes original articles, reviews, and technical notes. The journal is listed in the Science Citation Index Expanded (SCIE) of Thomson Reuters. NET covers all fields for peaceful utilization of nuclear energy and radiation as follows: 1) Reactor Physics 2) Thermal Hydraulics 3) Nuclear Safety 4) Nuclear I&C 5) Nuclear Physics, Fusion, and Laser Technology 6) Nuclear Fuel Cycle and Radioactive Waste Management 7) Nuclear Fuel and Reactor Materials 8) Radiation Application 9) Radiation Protection 10) Nuclear Structural Analysis and Plant Management & Maintenance 11) Nuclear Policy, Economics, and Human Resource Development
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