Application of artificial neural networks for prediction of solar radiation for Botswana

V. Sampath Kumar; J. Prasad; V. Lakshmi Narasimhan; S. Ravi

doi:10.1109/ICECDS.2017.8390110

Application of artificial neural networks for prediction of solar radiation for Botswana

V. Sampath Kumar
, J. Prasad
, V. Lakshmi Narasimhan
, S. Ravi

Electrical, Computer & Telecommunications Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

Energy plays a pivotal role in the socio and economic development of a country. It is the key to many daily chores. The depleting fossil fuels reserve and its climatic impact on a global scale encourage the development of alternate sources of energy. It is crucial that the developing countries utilize other renewable sources and tap the potential for its development. Botswana being a landlocked country has abundance of resources and receives sunshine throughout the year. This paper discusses Artificial Neural Network Model for solar radiation in Botswana. By using data of global solar radiation, sunshine hours data recorded for six locations, Gaborone, Francistown, Kasane, Maun, Shakawe, Ghanzi the solar constants were obtained. MATLAB Neural Network tool was used for training and regression analysis computed. The results using Artificial Neural Network encourages the development of a Neural Network Model application for developing a significant model for estimating the Solar Potential in Botswana.

Original language	English
Title of host publication	2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3493-3501
Number of pages	9
ISBN (Electronic)	9781538618868
DOIs	https://doi.org/10.1109/ICECDS.2017.8390110
Publication status	Published - Jun 19 2018
Event	2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017 - Chennai, India Duration: Aug 1 2017 → Aug 2 2017

Publication series

Name	2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017

Conference

Conference	2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017
Country/Territory	India
City	Chennai
Period	8/1/17 → 8/2/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 8 Decent Work and Economic Growth

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Networks and Communications
Information Systems
Decision Sciences (miscellaneous)
Information Systems and Management
Energy Engineering and Power Technology
Computer Science Applications
Signal Processing

Access to Document

10.1109/ICECDS.2017.8390110Licence: Unspecified

Cite this

Kumar, V. S., Prasad, J., Narasimhan, V. L., & Ravi, S. (2018). Application of artificial neural networks for prediction of solar radiation for Botswana. In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017 (pp. 3493-3501). (2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICECDS.2017.8390110

Kumar, V. Sampath ; Prasad, J. ; Narasimhan, V. Lakshmi et al. / Application of artificial neural networks for prediction of solar radiation for Botswana. 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 3493-3501 (2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017).

@inproceedings{1e635526bc4647e49e96951f2e0775b2,

title = "Application of artificial neural networks for prediction of solar radiation for Botswana",

abstract = "Energy plays a pivotal role in the socio and economic development of a country. It is the key to many daily chores. The depleting fossil fuels reserve and its climatic impact on a global scale encourage the development of alternate sources of energy. It is crucial that the developing countries utilize other renewable sources and tap the potential for its development. Botswana being a landlocked country has abundance of resources and receives sunshine throughout the year. This paper discusses Artificial Neural Network Model for solar radiation in Botswana. By using data of global solar radiation, sunshine hours data recorded for six locations, Gaborone, Francistown, Kasane, Maun, Shakawe, Ghanzi the solar constants were obtained. MATLAB Neural Network tool was used for training and regression analysis computed. The results using Artificial Neural Network encourages the development of a Neural Network Model application for developing a significant model for estimating the Solar Potential in Botswana.",

author = "Kumar, \{V. Sampath\} and J. Prasad and Narasimhan, \{V. Lakshmi\} and S. Ravi",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017 ; Conference date: 01-08-2017 Through 02-08-2017",

year = "2018",

month = jun,

day = "19",

doi = "10.1109/ICECDS.2017.8390110",

language = "English",

series = "2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3493--3501",

booktitle = "2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017",

address = "United States",

}

Kumar, VS, Prasad, J, Narasimhan, VL & Ravi, S 2018, Application of artificial neural networks for prediction of solar radiation for Botswana. in 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017. 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017, Institute of Electrical and Electronics Engineers Inc., pp. 3493-3501, 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017, Chennai, India, 8/1/17. https://doi.org/10.1109/ICECDS.2017.8390110

Application of artificial neural networks for prediction of solar radiation for Botswana. / Kumar, V. Sampath; Prasad, J.; Narasimhan, V. Lakshmi et al.
2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017. Institute of Electrical and Electronics Engineers Inc., 2018. p. 3493-3501 (2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Application of artificial neural networks for prediction of solar radiation for Botswana

AU - Kumar, V. Sampath

AU - Prasad, J.

AU - Narasimhan, V. Lakshmi

AU - Ravi, S.

PY - 2018/6/19

Y1 - 2018/6/19

N2 - Energy plays a pivotal role in the socio and economic development of a country. It is the key to many daily chores. The depleting fossil fuels reserve and its climatic impact on a global scale encourage the development of alternate sources of energy. It is crucial that the developing countries utilize other renewable sources and tap the potential for its development. Botswana being a landlocked country has abundance of resources and receives sunshine throughout the year. This paper discusses Artificial Neural Network Model for solar radiation in Botswana. By using data of global solar radiation, sunshine hours data recorded for six locations, Gaborone, Francistown, Kasane, Maun, Shakawe, Ghanzi the solar constants were obtained. MATLAB Neural Network tool was used for training and regression analysis computed. The results using Artificial Neural Network encourages the development of a Neural Network Model application for developing a significant model for estimating the Solar Potential in Botswana.

AB - Energy plays a pivotal role in the socio and economic development of a country. It is the key to many daily chores. The depleting fossil fuels reserve and its climatic impact on a global scale encourage the development of alternate sources of energy. It is crucial that the developing countries utilize other renewable sources and tap the potential for its development. Botswana being a landlocked country has abundance of resources and receives sunshine throughout the year. This paper discusses Artificial Neural Network Model for solar radiation in Botswana. By using data of global solar radiation, sunshine hours data recorded for six locations, Gaborone, Francistown, Kasane, Maun, Shakawe, Ghanzi the solar constants were obtained. MATLAB Neural Network tool was used for training and regression analysis computed. The results using Artificial Neural Network encourages the development of a Neural Network Model application for developing a significant model for estimating the Solar Potential in Botswana.

UR - https://www.scopus.com/pages/publications/85050140562

UR - https://www.scopus.com/pages/publications/85050140562#tab=citedBy

U2 - 10.1109/ICECDS.2017.8390110

DO - 10.1109/ICECDS.2017.8390110

M3 - Conference contribution

AN - SCOPUS:85050140562

T3 - 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017

SP - 3493

EP - 3501

BT - 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017

Y2 - 1 August 2017 through 2 August 2017

ER -

Kumar VS, Prasad J, Narasimhan VL, Ravi S. Application of artificial neural networks for prediction of solar radiation for Botswana. In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017. Institute of Electrical and Electronics Engineers Inc. 2018. p. 3493-3501. (2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017). doi: 10.1109/ICECDS.2017.8390110

Application of artificial neural networks for prediction of solar radiation for Botswana

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this