Hybrid Load Forecasting Using Gaussian Process Regression and Novel Residual Prediction

Round 1

Reviewer 1 Report

Thank you for submitting your paper “Hybrid load forecasting with Gaussian process regression and residual prediction” to the Journal of Applied sciences.

The topic is interesting, but the paper needs some improvements.

1. The title of the paper should show the intent or novelty, in my opinion it results too generic.
2. The Abstract should contain answers to the following questions: What problem was studied and why is it important? What methods were used? What are the important results? What conclusions can be drawn from the results? What is the novelty of the work and where does it go beyond previous efforts in the literature? The abstract should also report the main numerical results. The originality of the paper needs to be stated clearly and the most significative results.
3. All the graphs should be explained much more.
4. The results section is poor; it should be implemented.
5. Please, add the table of nomenclature

Author Response

Hello,

Thank you for kindly reviewing our paper. Please find in the attachment the responses for your suggestions.

Best regards,

Authors 

Author Response File: Author Response.docx

Reviewer 2 Report

The authors presented a load-forecasting approach which is an interesting topic and has reasonable novelty. Paper is well-written and well-presented. However, there are few areas author may consider improving to make the ready for publication, including:

• Abstract need to modify focusing the contributions of the research. Current Abstract is not convincing.
• Need to explore existing research including their strengths and weaknesses that deals with load forecasting in order to identify research gaps from which authors can identify the research objectives.
• In Figure 4 and 5 authors presented the characteristics pattern which is great. But authors have not mentioned the reason of the observed pattern. Need to demonstrate the pattern with its reason.
• Please check the quality of the figures and improve as much as possible.
• In line 241, authors mentioned that a comparison was made with and without error prediction - not clear to me. Can you please clarify. 
• Need to compare the performance of the proposed hybrid model with the existing model to prove the superiority of the proposed model
• Conclusions should be concise focusing the findings/outcome of the research. Moreover, author may mention the benefit of the research for the research domain including future direction.

Author Response

Hello,

Thank you for kindly reviewing our paper. Please find in the attachment our responses for your suggestions.

Best regards,

Authors

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The authors addressed the reviewers' suggestions.