Sensor network driven novel hybrid model based on feature selection and SVR to predict indoor temperature for energy consumption optimisation in smart buildings-Reference-Cited by-同舟云学术

Sensor network driven novel hybrid model based on feature selection and SVR to predict indoor temperature for energy consumption optimisation in smart buildings

Published:2022-11-09 Issue:6 Volume:13 Page:3048-3061
ISSN:0975-6809
Container-title:International Journal of System Assurance Engineering and Management
language:en
Short-container-title:Int J Syst Assur Eng Manag

Author:

Kumar Sachin^ORCID,Nisha Zairu,Singh Jagvinder,Sharma Anuj Kumar

Publisher

Springer Science and Business Media LLC

Subject

Strategy and Management,Safety, Risk, Reliability and Quality

Link

https://link.springer.com/content/pdf/10.1007/s13198-022-01795-y.pdf

Reference70 articles.

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3. Ahmad MW, Mourshed M, Rezgui Y (2017) Trees vs neurons: comparison between random forest and ANN for high-resolution prediction of building energy consumption. Energy Build 147:77–89

4. Ahmad T, Chen H, Guo Y, Wang J (2018) A comprehensive overview on the data driven and large scale based approaches for forecasting of building energy demand: a review. Energy Build 165:301–320

5. Lecture Notes in Computer Science;S Alawadi,2017

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