A Performance Evaluation of Solar Energy Prediction Approaches for Energy-Harvesting Wireless Sensor Networks

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dc.contributor.authorKoşunalp, Selahattin
dc.date.accessioned2026-02-28T12:25:13Z
dc.date.available2026-02-28T12:25:13Z
dc.date.issued2016
dc.departmentBayburt Üniversitesi
dc.description.abstractEnergy harvesting from the surrounding environment has been a superior way of eliminating the burden of having to replace depleted batteries in wireless sensor networks (WSNs), thereby achieving a perpetual lifetime. However, the ambient energy is highly time-variable and depends on the environmental conditions, which raises the need to design new approaches for predicting future energy availability. This paper presents a performance evaluation and comparison of three recently-proposed solar energy prediction algorithms for WSNs. In order to provide an accurate performance of the algorithms, real-world measurements obtained from a solar panel were considered. Also, the performance characteristics of the algorithms in four seasons –winter, spring, summer and autumn – were demonstrated. To do this, a month in each season was selected for performance comparison, discussing the performance of the algorithms in each season.
dc.identifier.doi10.18100/ijamec.266963
dc.identifier.endpage427
dc.identifier.issn2147-8228
dc.identifier.issn2147-8228
dc.identifier.issueSpecial Issue-1
dc.identifier.startpage424
dc.identifier.urihttps://doi.org/10.18100/ijamec.266963
dc.identifier.urihttps://hdl.handle.net/20.500.12403/6283
dc.language.isoen
dc.publisherPLUSBASE AKADEMİ ORGANİZASYON VE DANIŞMANLIK
dc.relation.ispartofInternational Journal of Applied Mathematics Electronics and Computers
dc.relation.ispartofInternational Journal of Applied Mathematics Electronics and Computers
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20260218
dc.subjectEngineering
dc.subjectMühendislik
dc.titleA Performance Evaluation of Solar Energy Prediction Approaches for Energy-Harvesting Wireless Sensor Networks
dc.typeArticle

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