NDLI: Configuring artificial neural networks for the prediction of available energy in solar-powered sensor nodes

Content Provider	IEEE Xplore Digital Library
Author	Gebben, F. Bader, S. Oelmann, B.
Copyright Year	2015
Description	Author affiliation: Dept. of Electron. Design, Mid Sweden Univ., Sundsvall, Sweden (Gebben, F.; Bader, S.; Oelmann, B.)
Abstract	The behavior prediction of solar energy harvesting systems requires accurate system models in order to dimension the system with respect to its application and location constraints. In contrast to commonly used equivalent circuit models, artificial neural networks (ANN) allow for the behavior of the entire system to be captured in an efficient manner. In this work, we have investigated the influences of the underlying ANN configuration on the model's prediction performance. It was found that the performance variation between training runs increases with an rising number of neurons, which can lead to a higher model performance, but makes the performance outcome more sensitive to initial training conditions. Moreover, the results demonstrate that even simple ANN configurations capture the system behavior accurately and result in low prediction errors for the harvesting architecture under test.
Sponsorship	IEEE
Starting Page	1
Ending Page	4
File Size	795092
Page Count	4
File Format	PDF
e-ISBN	9781479982035
DOI	10.1109/ICSENS.2015.7370253
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-01
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Integrated circuit modeling Training Solar energy Artificial neural networks Neurons Biological neural networks Predictive models artificial neural networks wireless sensor networks energy harvesting solar energy harvesting system modeling
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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