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Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/840
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dc.contributor.authorPereis, A. T-
dc.contributor.authorJayasinghe, J. M. J. W-
dc.contributor.authorRathnayake, U. S-
dc.date.accessioned2022-01-31T03:48:32Z-
dc.date.available2022-01-31T03:48:32Z-
dc.date.issued2021-03-
dc.identifier.citationmila 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/10.1155/2021/5577547en_US
dc.identifier.issn2090-0147-
dc.identifier.urihttp://localhost:80/handle/123456789/840-
dc.description.abstractUnder 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.en_US
dc.language.isoenen_US
dc.publisherHindawien_US
dc.relation.ispartofseriesJournal of Electrical and Computer Engineering;Vol 2021 Issue Mar-
dc.subjectFiltering Algorithmen_US
dc.subjectPositioning Accuracyen_US
dc.subjectLogistics Tracking Systemen_US
dc.subjectTracking System Baseden_US
dc.subject3D Virtual Warehousingen_US
dc.subjectWarehousing Logisticsen_US
dc.subjectDemonstration Systemen_US
dc.titleForecasting Wind Power Generation using Artificial Neural Network: “Pawan Danawi” - A Case Study from Sri Lankaen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1155/2021/5577547en_US
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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