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Article
Peer-Review Record

Optimal Sprinkler Application Rate of Water–Fertilizer Integration Machines Based on Radial Basis Function Neural Network

Water 2022, 14(18), 2838; https://doi.org/10.3390/w14182838
by Xiaochu Liu 1,2,3, Xiangjin Zhu 1,2,3, Zhongwei Liang 1,2,3,* and Tao Zou 1,3
Reviewer 1:
Reviewer 2:
Reviewer 3:
Water 2022, 14(18), 2838; https://doi.org/10.3390/w14182838
Submission received: 20 August 2022 / Revised: 6 September 2022 / Accepted: 7 September 2022 / Published: 12 September 2022
(This article belongs to the Special Issue Advances in Sprinkler Irrigation Systems and Water Saving)

Round 1

Reviewer 1 Report

Dear,

The present research developed a mathematical soil infiltration model for rainwater irrigation and fertilizer integration machines. The constrained German method obtained the soil water accumulation time for different initial soil water content, apparent specific gravity, rain application rate, and soil texture. These data were used as a training database for the neural network. There are suggestions for improvement.

1. More artificial intelligence studies are used in relation to the subject

2.The flowchart of the program should be given in the method section

3.The advantages of using this neural network method are given

 

Comments for author File: Comments.pdf

Author Response

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Reviewer 2 Report

Qualify of the scientific article is good and do not requires any changes and additions. I recommend it to publication in original form.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Please see attached for suggested edits. 

Comments for author File: Comments.pdf

Author Response

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Author Response File: Author Response.pdf

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