A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Published: |
Springer Verlag
2019
|
| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069435045&doi=10.1007%2f978-3-319-69889-2_1&partnerID=40&md5=e381282f0ac52300283784893075ad37 http://eprints.utp.edu.my/24179/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
my.utp.eprints.24179 |
|---|---|
| record_format |
eprints |
| spelling |
my.utp.eprints.241792021-08-19T15:27:25Z A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption Chiroma, H. Abdullahi, U.A. Hashem, I.A.T. Saadi, Y. Al-Dabbagh, R.D. Ahmad, M.M. Dada, G.E. Danjuma, S. Maitama, J.Z. Abubakar, A. Abdulhamid, S.�M. Springer Verlag 2019 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069435045&doi=10.1007%2f978-3-319-69889-2_1&partnerID=40&md5=e381282f0ac52300283784893075ad37 Chiroma, H. and Abdullahi, U.A. and Hashem, I.A.T. and Saadi, Y. and Al-Dabbagh, R.D. and Ahmad, M.M. and Dada, G.E. and Danjuma, S. and Maitama, J.Z. and Abubakar, A. and Abdulhamid, S.�M. (2019) A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption. Green Energy and Technology . pp. 1-20. http://eprints.utp.edu.my/24179/ |
| institution |
Universiti Teknologi Petronas |
| building |
UTP Resource Centre |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Teknologi Petronas |
| content_source |
UTP Institutional Repository |
| url_provider |
http://eprints.utp.edu.my/ |
| format |
Article |
| author |
Chiroma, H. Abdullahi, U.A. Hashem, I.A.T. Saadi, Y. Al-Dabbagh, R.D. Ahmad, M.M. Dada, G.E. Danjuma, S. Maitama, J.Z. Abubakar, A. Abdulhamid, S.�M. |
| spellingShingle |
Chiroma, H. Abdullahi, U.A. Hashem, I.A.T. Saadi, Y. Al-Dabbagh, R.D. Ahmad, M.M. Dada, G.E. Danjuma, S. Maitama, J.Z. Abubakar, A. Abdulhamid, S.�M. A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption |
| author_facet |
Chiroma, H. Abdullahi, U.A. Hashem, I.A.T. Saadi, Y. Al-Dabbagh, R.D. Ahmad, M.M. Dada, G.E. Danjuma, S. Maitama, J.Z. Abubakar, A. Abdulhamid, S.�M. |
| author_sort |
Chiroma, H. |
| title |
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption |
| title_short |
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption |
| title_full |
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption |
| title_fullStr |
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption |
| title_full_unstemmed |
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption |
| title_sort |
theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption |
| publisher |
Springer Verlag |
| publishDate |
2019 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069435045&doi=10.1007%2f978-3-319-69889-2_1&partnerID=40&md5=e381282f0ac52300283784893075ad37 http://eprints.utp.edu.my/24179/ |
| _version_ |
1738656576784302080 |
| score |
13.211869 |