Accurate Prediction of Hourly Energy Consumption in a Residential Building Based on the Occupancy Rate Using Machine Learning Approaches
, Ka Ho Karl Chow 1, Rungsimun Luevisadpaibul 1, Gokul Sidarth Thirunavukkarasu 1,*, Mehdi Seyedmahmoudian 1,*, Ben Horan 2, Saad Mekhilef 1,3 and Alex Stojcevski 1Round 1
Reviewer 1 Report
This is the review of the manuscript entitled “ Accurate prediction of hourly energy consumption in a residential building based on the occupancy rate using machine learning approaches”.
The authors present an interesting topic, being in line with the mission of the Applied Sciences Journal.
I have some suggestions:
Abstract: - authors could highlight the main results of their work. Avoid general discussions and assessments.
Introduction:
- the authors need to clarify and explain the difference between the current study with the available literature;
- the authors must highlight the original contribution of their work in relation to other works in the literature dedicated to the same topic.
Materials and Methods:
- the authors must highlight the original personal contributions (what are the merits of the authors);
- - discuss aspects related to the implementation in practical applications of the proposed method.
Results: - discuss issues related to how the accuracy of the results data can be verified.
Author Response
Thank you to the reviewer for the insightful feedback. Individual comments and a rebuttal letter is attached for your kind reference.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
There are some weaknesses through the manuscript which need improvement. Therefore, the submitted manuscript cannot be accepted for publication in this form, but it has a chance of acceptance after a major revision. My comments and suggestions are as follows:
1- Abstract gives information on the main feature of the performed study, but some details about the proposed algorithm should be added. However, a concise abstract is needed.
2- In abstract it was focused on review of the previous research works. These sentences must be reduced and focused must be on proposed algorithm.
3- Authors must clarify necessity of the performed research. The objectives of the study, must be clearly mentioned in concluding part of introduction.
4- The literature study must be enriched. It is highly recommended to read and cite the published papers in industrial applications of AI: (a) https://doi.org/10.1016/j.promfg.2018.12.017 and (b) https://doi.org/10.1016/j.asoc.2018.11.017
5- Text in figures must be presented in a high quality. Italic text in formula must be avoided. The main reference of each equation must be cited. Also, all the parameters in each formula must be introduced.
6- In its language layer, the manuscript should be considered for English language editing. There are sentences which have to be rewritten.
7- The conclusion must be more than just a summary of the manuscript. Please provide all changes in text and reference update (based on recommended papers) by red color in the revised version.
Author Response
Thank you to the reviewer for the insightful feedback. Individual comments and a rebuttal letter is attached for your kind reference.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
The paper has been improved and corresponding modifications have been conducted. In my opinion, the current version can be considered for publication in Applied Sciences.
