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dc.contributor.advisorTwomey, Janet M.en_US
dc.contributor.authorEsmaeili, Mohammad Aminen_US
dc.date.accessioned2011-07-15T14:59:54Z
dc.date.available2011-07-15T14:59:54Z
dc.date.issued2011-05-04en_US
dc.identifier.citationEsmaeili, Mohammad Amin (2011). Self-Organizing Map (SOM) in Wind Speed Forecasting: A New Approach in Computational Intelligence (CI) Forecasting Methods. -- In Proceedings: 7th Annual Symposium: Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University, p. 69-70en_US
dc.identifier.urihttp://hdl.handle.net/10057/3628
dc.descriptionPaper presented to the 7th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Marcus Welcome Center, Wichita State University, May 4, 2011.en_US
dc.descriptionResearch completed at the Department of Industrial and Manufacturing Engineeringen_US
dc.description.abstractTwo critical issues in renewable energy are how to make wind energy cost effective and how to integrate wind energy into electricity grids. Within many approaches to cost reduction, wind speed forecasting was mentioned as an effective approach because accurate forecasting of wind speed has a direct impact on the scheduling of a power system, and also the dynamic control of the wind turbine. This research investigates the practical use of Self Organizing Map (SOM) as a special type of neural network based forecasting method. In this paper, forecasting the average, maximum and minimum of one-day-ahead wind speed based on the past wind speed states of the previous 24 hours is the objective.en_US
dc.language.isoen_USen_US
dc.publisherWichita State University. Graduate Schoolen_US
dc.relation.ispartofseriesGRASPen_US
dc.relation.ispartofseriesv.7en_US
dc.titleSelf-Organizing Map (SOM) in Wind Speed Forecasting: A New Approach in Computational Intelligence (CI) Forecasting Methodsen_US
dc.typeConference paperen_US


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