MACLA-LSTM: A Novel Approach for Forecasting Water Demand
Round 1
Reviewer 1 Report
The manuscript is overall well written and easy to follow and the authors have well thought out their main contributions in the field of Forecasting Water Demand using machine learning. The author should work on to improve the following:
[Abstract] What is the actual finding of the research, the result should be discussed in this section. The core objective (What are you trying to solve) is not discussed.
[Keywords] Provide meaningful keywords in alphabetical order.
[Introduction] Abbreviation should be explained in the first attempt (UN). Recheck the manuscript. Moreover, this section is short and includes content based on LSTM based related deep learning models and CLA based optimization algorithms to understand the need of this combination.
[Introduction] The author discusses the gap, we recommend the author to include specific contributions to the research. The mentioned contributions are generic. Moreover, mention the novelty of the proposed model / recommendation.
[Related work] This section is weak, the author should work on recent year papers to support the need and importance of the proposed model. What is the limitation of the existing model, explain in detail.
[Materials and Methods] Recheck typos and grammatical errors. Use only the required subsections. This section is explained well. But the actual problem is discussion over the name. The author mentioned that the ICLA-LSTM combination is used in this research. Unfortunately, we could find this explanation.
[Materials and Methods] Line 292-298: These steps should be explained properly in detail or provide pseudocode for better understanding.
[Materials and Methods] Overall, the author combined 2 well known algorithms with some incremental improvisation. The author explains the novelty of the proposed method.
[Result and discussion] Explained well, but the quantitative analysis is missing. Include 2-3 optimizations to show the effectiveness of the proposed ICLA and other algorithms.
[Result and discussion] Comparative analysis is unacceptable. In comparing the results with two previous papers (15,16), the author found these state of the art papers did not meet his expectations. I recommend the author to include 2-3 recent year papers in table 1.
[Conclusion] Discuss the findings and its advantages.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The authors have considered a critical and important problem of water demand forecasting. They have proposed a new approach CLA-LSTM has been proposed. The authors have discussed the need for using CLA and LSTM. The results have been discussed well.
However the authors should incorporate the following changes to enrich the manuscript:
1. The authors need to highlight more contemporary works that use Clouded Leopard Algorithm in the related works section.
2. In the abstract it is claimed that CLA-LSTM is used to improve the accuracy of time series prediction of water demand. The authors have evaluated it against a constricted environment namely department, company and mall. Has the work been tested in real time?
3. How scalable is the work when applied across a huge volume of data? Will there be any performance issues?
4. The authors define this approach for a short-term water demand. They must clearly demark what is meant by short-term and long-term water demand. The explanation for this should be clearly made available.
5. The initialization and parameter details can be tabulated.
6. The architecture details of the proposed model can be better depicted.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
The paper seems very interesting and it only needs a minor review:
1- The given abstract can be improved to be more focused
2- all the given images must be increased in resolution
3- some given patterns scales of x and y are not adjustable
4- it will be good if the author gives key challenges in the conclusion part and also the merits and future perspective
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 4 Report
Comment on the “CLA-LSTM：A Novel Approach for Forecasting Water Demand”
Water shortage has received large attention and has been studied extensively due to its huge impacts on social-economic development and people’s life. Water demand prediction plays a crucial role in water distribution system 15 management. This topic is interesting. A major revision is suggested before being accepted by this journal. The detailed comments are listed.
1. The manuscript was very lengthy, with some grammatical problems and very long sentences. The English-writing in this manuscript is still insufficient. I suggest that the author revise and simplify the manuscript from beginning to end.
2. There is little introduction about “study area” and “the using data”. As a scientific paper, the “study area” and “using data” must be introduced in detail. Otherwise, I will question your rationality and scientific nature.
3. Missing units on vertical and horizontal axes in figure 5.
Comments for author File: Comments.pdf
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 5 Report
1. Why do you need lines 31-41. In my view they should be deleted. What is stated is obvious.
2. Line 51-78 please break into a number of paragraphs perhaps 4 - 8 lines long to improve reader accessibility to your text.
3. Line 74 reword to "correlation; and adequate experiments"
4. Line 98 please give an example of a candidate solution and a decision variable at this point.
5. Line 109 - please define prey in the context of this study. I think that you should describe in some depth the proposed method in simple English around line 90, since the concept you are applying is new. You should also define at this point the parameters required to work the model, and define the prey, etc.
6. Your English needs some attention throughout the MS. There are some mis-wordings which detract from your messaging. A typical example is provided by line 122 which states
After clouded leopards hunt prey, there would stop moving and rest on the trees,
I think you mean
Following a successful "hunt", the mathematical model, simulates a rest period for the clouded leopards. The model attempts to mimic the behaviour of a wild leopard which catches a prey, and then rests on a tree branch.
Please go through the MS with a native English speaker to improve the English in the MS
Technically I do not have a problem with your work. I think that it is innovative and appears to be mathematically correct. Where the MS is weak is in the following areas.
Firstly the written English needs to be improved throughout. Your syntax needs to be improved as in some sentences your meaning is difficult to discern. Please ask a native English speaker (US, UK, Australian, or Indian) or a Chinese English service to go through the paper with you. This recommendation is for clarity, and to help others understand exactly what you have done
Secondly, you need to simply explain the clouded leopard concept, both what it is and how it works. Sustainability is multi-disciplinary, and you need to explain the concepts in simple terms to allow others to see whether the Clouded Leopard model you propose could be applied to their projects.
Thirdly, you need to clearly define what pieces of data are required to work the model and how this data relates to the equations you have provided.
s.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Revisions are well addressed and satisfactory
Reviewer 2 Report
The changes suggested have been incorporated and the manuscript can be accepted in its current form.
Reviewer 4 Report
It has been revised as required. And I suggest accepting the paper.
Reviewer 5 Report
The authors have addressed my concerns. The new MS reads well and can be published.
