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利用机器学习技术进行性能优化的太阳能预测

IF 1.7 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Electric Power Components and Systems Pub Date : 2024-02-19 DOI:10.1080/15325008.2024.2316245
Murugesan S, M. Mahasree, F. Kavin, N. Bharathiraja
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引用次数: 0

摘要

本文的目的是提出一种预测技术系统，利用机器学习（ML）技术构成数据完整性阶段，并对后处理输出进行优化，以提高预测结果的准确性。
本文章由计算机程序翻译，如有差异，请以英文原文为准。
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Solar Energy Forecasting With Performance Optimization Using Machine Learning Techniques
The objective of this paper is proposed a forecasting technique system constitute the data integrity phase using Machine Learning (ML) techniques and post-processing output optimization to improve ...
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来源期刊
Electric Power Components and Systems
Electric Power Components and Systems 工程技术-工程：电子与电气
CiteScore
2.70
自引率
6.70%
发文量
95
审稿时长
7.2 months
期刊介绍： Electric Power Components and Systems publishes original theoretical and applied papers of permanent reference value related to the broad field of electric machines and drives, power electronics converters, electromechanical devices, electrical equipment, renewable and sustainable electric energy applications, and power systems. Specific topics covered include: -Electric machines- Solid-state control of electric machine drives- Power electronics converters- Electromagnetic fields in energy converters- Renewable energy generators and systems- Power system planning- Transmission and distribution- Power system protection- Dispatching and scheduling- Stability, reliability, and security- Renewable energy integration- Smart-grid and micro-grid technologies.
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