Engineering and TechnologySustainability
Weather Impact on Solar Farm Performance: A Comparative Analysis of Machine Learning Techniques
A. Gopi, P. Sharma, et al.
This study presents an innovative prediction model for forecasting the annual power generation yield and performance ratio of photovoltaic farms. Using advanced AI techniques, the results highlight ANFIS as the most precise model, providing valuable insights for policymakers and solar energy developers. The research was conducted by Ajith Gopi, Prabhakar Sharma, Kumarasamy Sudhakar, Wai Keng Ngui, Irina Kirpichnikova, and Erdem Cuce.
Related Publications
Explore these studies to deepen your understanding
Adjacent work that informs or extends this paper's methodology and findings.
Engineering and Technology
Weather Impact on Solar Farm Performance: A Comparative Analysis of Machine Learning Techniques
A. Gopi, P. Sharma, et al.
Education
Exploring the impact of intelligent learning tools on students' independent learning abilities: a PLS-SEM analysis of grade 6 students in China
R. Pan, Z. Qin, et al.
Psychology
The impact of relevant versus irrelevant media multitasking on academic performance during online learning: a serial of mediating models
L. Fan, C. Pan, et al.
Interdisciplinary Studies
The impact of COVID-19 on the debate on open science: a qualitative analysis of published materials from the period of the pandemic
M. B. Marshall, S. Pinfield, et al.
