Data Classification and Demand Prediction Methods Based on Semi-Supervised Agricultural Machinery Spare Parts Data

Round 1

Reviewer 1 Report

Reviewer’s Comments

The manuscript " Data classification and demand prediction methods based on semi -supervised agricultural machinery spare parts data," with the Manuscript id: agriculture-2052350, needs minor revision for further consideration. The selected topic is very interesting and aligned with the todays need. Following are the comments that needs to be addressed.

1.       Author must adopt the standard pattern of article i.e. Abstract, Introduction, Materials and methods, results and discussion, conclusions and references.

2.       Abstract needs to be rewritten and the objectives of the work and the major findings must be incorporated in the abstract.

3.       Introduction needs to be improved by adding some more relevant recent articles. Author must mention that what are the techniques currently deployed and the pros and cons as per the literature to formulate the research gap. In present status research gap formulation is very poor.

4.       Line no. 61: What is “ono-linear”?, Please correct.

5.       Line no 169-170: Rewrite sentence, “And it only needs to establish a network relationship between input and output to o simulate the target value.”.

6.       Line 174: What is “-1~1”?

7.       Line 189-190:  In sentence, “this paper applies the improved PSO algorithm to optimize the connection weights and thresholds of BP neural network.”, Author claimed that PSO was deployed, but there are no results presented.

8.       Line 202: “Then the input and output after the normalization are divided into a training sample and a test sample according to a certain proportion.”, What is certain Proportion here?

9.       What is the size of data set used, as author mentioned semi supervised? What are the parameters considered for input and what are the predicted outputs?

10.   Line 246-250: What is implicit layer means? How author comes to 10 nodes in implicit layer?

11.   The results need to be presented systematically and discussed by comparing with the recently published similar articles to justify and present the significance of the work.

12.   Conclusion must be rewritten (within 150 words) presenting the major findings/takeaways with the support of the numbers. Also at the end, if author wish then adds 1-2 sentences for the application and future research.

I wish authors a great success.

Comments for author File: Comments.pdf

Author Response

Response to Reviewer 1 Comments

Point 1: Author must adopt the standard pattern of article i.e. Abstract, Introduction, Materials and methods, results and discussion, conclusions and references.

Response 1: Dear Reviewer, according to your suggestion, I have revised the structure of the article to Abstract, Introduction, Materials and methods, results and discussion, conclusions and references. Thank you for pointing out the structural errors in my article.

Point 2: Abstract needs to be rewritten and the objectives of the work and the major findings must be incorporated in the abstract.

Response 2: According to your suggestion, I have rewritten the summary, and incorporated the work objectives and main findings into the summary. I have revised the parts that are easy to cause misunderstanding before. Thank you for pointing out the mistakes in my abstract.

Point 3: Introduction needs to be improved by adding some more relevant recent articles. Author must mention that what are the techniques currently deployed and the pros and cons as per the literature to formulate the research gap. In present status research gap formulation is very poor.

Response 3: Based on your suggestions, I have added some more relevant recent articles. We also mentioned the current technology and the advantages and disadvantages based on the literature to determine the research gap. Thank you for pointing out the mistakes in my introduction.

Point 4: Line no. 61: What is “ono-linear”?, Please correct.

Response 4: According to your suggestion, I have corrected the nonstandard language. Thank you for pointing out the mistakes in my article.

Point 5: Line no 169-170: Rewrite sentence, “And it only needs to establish a network relationship between input and output to o simulate the target value.”.

Response 5: According to your suggestion, I have corrected the nonstandard language. Thank you for pointing out the mistakes in my article.

Point 6: Line 174: What is “-1~1”?

Response 6: According to your suggestion, I have corrected the nonstandard parts in the language. "- 1~1" is modified to be greater than - 1 and less than 1. Thank you for pointing out the errors in my article.

Point 7: Line 189-190:  In sentence, “this paper applies the improved PSO algorithm to optimize the connection weights and thresholds of BP neural network.”, Author claimed that PSO was deployed, but there are no results presented.

Response 7: According to your suggestions, I have corrected the language that is easy to cause misunderstanding. The improved PSO algorithm here is the IPSO algorithm deployed later. Thank you for pointing out the errors in my article.

Point 8: Line 202: “Then the input and output after the normalization are divided into a training sample and a test sample according to a certain proportion.”, What is certain Proportion here?

Response 8: According to your suggestion, I have corrected the unclear parts in the language. The proportion here is 8:2. Thank you for pointing out the mistakes in my article.

Point 9: What is the size of data set used, as author mentioned semi supervised? What are the parameters considered for input and what are the predicted outputs?

Response 9: According to your suggestion, I have corrected the unclear points in the language. The dataset here contains 1869 pieces of data. Enter the name of spare parts, cost of repair materials, urgency of maintenance, num-ber of suppliers and annual repair usage as parameters to predict the quantity of spare parts needed in the near future. Thank you for pointing out the errors in my article.

Point 10: Line 246-250: What is implicit layer means? How author comes to 10 nodes in implicit layer?

Response 10: According to your suggestion, I have corrected the part that is not explained clearly in the language. The implicit layer is a part of the non input layer and non output layer, and also added the formula to determine the node of the implicit layer. Thank you for pointing out the error in my article.

Point 11: The results need to be presented systematically and discussed by comparing with the recently published similar articles to justify and present the significance of the work.

Response 11: According to your suggestion, I have corrected the experimental results in the article. Thank you for pointing out the mistakes in my article.

Point 12: Conclusion must be rewritten (within 150 words) presenting the major findings/takeaways with the support of the numbers. Also at the end, if author wish then adds 1-2 sentences for the application and future research.

Response 12: According to your suggestion, I have rewritten the conclusion, reduced the number of words, and presented the conclusion with the support of numbers. Thank you for pointing out the mistakes in my article.

Thank you again for your suggestions. Your suggestions are very professional and you point out the problems that need to be solved urgently in my article, which is very important to me. I am lucky to have such a conscientious and responsible reviewer as you.

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper  used the semi supervised learning algorithm  for solving the problem of data classification of agricultural machinery spare parts. Explain what is the novelty of the proposed model?

The Related work part is missing. Summarize the research issue and highlight the motivation of the proposed work.

How will you collect the spare parts information? clarity needed.

How will you find the accuracy?

How will you find the effectiveness of the proposed model?

Include the mathematical model for the calculation of E.

Result section needs to be upgraded with two more simulation parameters.

Refer the latest and suitable references as follows:

Jing-Yu, Chen, and Wang Ya-Jun. "Semi-Supervised Fake Reviews Detection based on AspamGAN." Journal of Artificial Intelligence 4, no. 1 (2022): 17-36.

Hore, Umesh W., and D. G. Wakde. "An Effective Approach of IIoT for Anomaly Detection Using Unsupervised Machine Learning Approach." Journal of IoT in Social, Mobile, Analytics, and Cloud 4, no. 3 (2022): 184-197.

Author Response

Response to Reviewer 2 Comments

Point 1: This paper  used the semi supervised learning algorithm  for solving the problem of data classification of agricultural machinery spare parts. Explain what is the novelty of the proposed model?

Response 1: Dear Reviewer, according to your suggestion, I have modified the part that I did not explain clearly. This model has not been used in the research of agricultural machinery spare parts, which can solve the problem of insufficient prediction accuracy in the research, easy to fall into the problem of prediction and over fitting, and is appropriate when it is difficult to obtain enough samples of agricultural machinery spare parts labels. Thank you for pointing out the errors in my article.

Point 2: The Related work part is missing. Summarize the research issue and highlight the motivation of the proposed work.

Response 2: According to your suggestion, I have added the missing part, explained the research problems and highlighted the motivation of the work. Thank you for pointing out the mistakes in my article.

Point 3: How will you collect the spare parts information? clarity needed.

Response 3: According to your suggestion, I have added the missing part, explaining that the data set required for the experiment was obtained through the field survey of spare parts warehouses in several provinces and the inquiry of spare parts warehouse staff. Thank you for pointing out the mistakes in my article.

Point 4: How will you find the accuracy?

Response 4: According to your suggestion, I have modified the part that I did not explain clearly. I get the accuracy by entering the data into the model and comparing the predicted value with the actual value. Thank you for pointing out the mistakes in my article.

Point 5: How will you find the effectiveness of the proposed model?

Response 5: According to your suggestion, I have modified the part that I did not explain clearly. By comparing the predicted value with the actual value, the model is effective if the accuracy is high. Thank you for pointing out the mistakes in my article.

Point 6: Include the mathematical model for the calculation of E.

Response 6: According to your suggestion, I modified the part that was not explained clearly, input the data into the mathematical model, predict the results obtained, and compare the predicted value with the actual value. If the accuracy is high, the mathematical model is effective. Thank you for pointing out the mistakes in my article.

Point 7: Result section needs to be upgraded with two more simulation parameters.

Response 7: According to your suggestion, I have added the missing parts. Thank you for pointing out the mistakes in my article.

Point 8: Refer the latest and suitable references as follows:

Jing-Yu, Chen, and Wang Ya-Jun. "Semi-Supervised Fake Reviews Detection based on AspamGAN." Journal of Artificial Intelligence 4, no. 1 (2022): 17-36.

Hore, Umesh W., and D. G. Wakde. "An Effective Approach of IIoT for Anomaly Detection Using Unsupervised Machine Learning Approach." Journal of IoT in Social, Mobile, Analytics, and Cloud 4, no. 3 (2022): 184-197.

Response 8: Based on your suggestions, I found that the latest references you proposed have been added to the list, which is not the latest references. Thank you for pointing out the mistakes in my article.

Thank you again for your suggestions. Your suggestions are professional and point out the problems that need to be solved urgently in my article, which is very important to me. I am lucky to have such a conscientious and responsible reviewer as you. I hope you will get better and better.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Acceptance recommended