Forecasting Wind Power Generation using Artificial Neural Network: “Pawan Danawi” - A Case Study from Sri Lanka

Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/840

Title:	Forecasting Wind Power Generation using Artificial Neural Network: “Pawan Danawi” - A Case Study from Sri Lanka
Authors:	Pereis, A. T Jayasinghe, J. M. J. W Rathnayake, U. S
Keywords:	Filtering Algorithm Positioning Accuracy Logistics Tracking System Tracking System Based 3D Virtual Warehousing Warehousing Logistics Demonstration System
Issue Date:	Mar-2021
Publisher:	Hindawi
Citation:	mila T. Peiris, Jeevani Jayasinghe, Upaka Rathnayake, "Forecasting Wind Power Generation Using Artificial Neural Network: “Pawan Danawi”—A Case Study from Sri Lanka", Journal of Electrical and Computer Engineering, vol. 2021, Article ID 5577547, 10 pages, 2021. https://doi.org/10.1155/2021/5577547
Series/Report no.:	Journal of Electrical and Computer Engineering;Vol 2021 Issue Mar
Abstract:	Under the background of the global integrated supply chain, the work of logistics is more and more complicated. Warehouse management is now an important part of logistics. The optimization of the logistics tracking system in the building material market proves that the tracking result of the system is highly reliable. The system has the advantages of small size, low cost, accurate positioning, real-time convergence, and high performance.
URI:	http://localhost:80/handle/123456789/840
ISSN:	2090-0147
Appears in Collections:	Department of Civil Engineering-Scopes Research Papers - Department of Civil Engineering Research Papers - Open Access Research Research Papers - SLIIT Staff Publications

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