INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Machine learning have an inherent attribute of learning from the data which may be numerical data or categorical data in order to imitate human intelligence for increasing the performance of the system. All this is attributed to the availability of different types of machine learning algorithm Each type of machine learning model has its strengths and weaknesses, and the choice of model depends on the nature of the data and the specific problem at hand. So generalization is always worked upon for the selection of the machine learning model. In this paper, authors have systematically developed a framework for machine learning based control for a very practical problem of supply-load balance as applicable to electrical power system. The identified problem is regression based. The paper thoroughly analyzes different combinations of machine learning algorithm along with different network architecture for achieving the desired results in the selected multi-area load frequency control problem with greater accuracy and high speed.
Keywords:
Machine learning, network type, training technique, load frequency control, Mutli area control
Cite Article:
"Machine Learning Taxonomy for Multi Area Network Control", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 3, page no.e724-e733, March-2023, Available :http://www.ijnrd.org/papers/IJNRD2303495.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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