Performance improvement of hybrid renewable energy sources connected to the grid using artificial neural network and sliding mode control

Research article (Journal of Power Electronics, 2021) · cited 56× · AI/ML
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Performance improvement of hybrid renewable energy sources connected to the grid using artificial neural network and sliding mode control

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Performance improvement of hybrid renewable energy sources connected to the grid using artificial neural network and sliding mode control is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Performance improvement of hybrid renewable energy sources connected to the grid using artificial neural network and sliding mode control. Retrieved May 24, 2026, from https://4ort.xyz/entity/performance-improvement-of-hybrid-renewable-energy-sources-connected-to-the-grid-using-artificial-neural-network-and-sli
MLA “Performance improvement of hybrid renewable energy sources connected to the grid using artificial neural network and sliding mode control.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/performance-improvement-of-hybrid-renewable-energy-sources-connected-to-the-grid-using-artificial-neural-network-and-sli.
BibTeX @misc{4ortxyz_performance-improvement-of-hybrid-renewable-energy-sources-connected-to-the-grid-using-artificial-neural-network-and-sli_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Performance improvement of hybrid renewable energy sources connected to the grid using artificial neural network and sliding mode control}}, year = {2026}, url = {https://4ort.xyz/entity/performance-improvement-of-hybrid-renewable-energy-sources-connected-to-the-grid-using-artificial-neural-network-and-sli}, note = {Accessed: 2026-05-24}}
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