Performance Evaluation of an Improved ANFIS Approach Using Different Algorithms to Predict the Bonding Strength of Glulam Adhered by Modified Soy Protein–MUF Resin Adhesive
Round 1
Reviewer 1 Report
This paper was introduced the ANFIS-GA model to solve the bonding strength problems of the laminated products. Combining the genetic algorithm with the ANFIS, the response estimation has been more accurate compared to other algorithms so that its R2 was 0.9809, RMSE was 0.3366, MAE was 0.2082 and SSE was 3.8523. The manuscript is suggested to accepted after minor modification. Some comments:
1. Page5. Line 203, The subheading number is incorrect.
2. Page6. Line 227, 232, the (4) and (5) are suggested uniform format.
3. Page7. Line 281, the formula (11) doesn’t have b l, please check it.
4. Page19. Line689-690, some references are missing DOI numbers.
Author Response
Please see attached
Author Response File: 
Author Response.docx
Reviewer 2 Report
In this manuscript, the authors reported the performance evaluation of the improved ANFIS approach for predicting the bonding strength of Glulam adhered by the modified soy protein-MUF resin adhesive. Currently, artificial intelligence techniques are very popular, and they may help researchers to reduce unnecessary experimental work. I suggested a minor revision to the manuscript, and the following issues should be addressed.
1. The abbreviations in the title, such as GA and ACOR, should be removed since it did not convey much information.
2. In the introduction, the authors should add one or two sentences explaining why AI technique is needed to analyze soy protein-based adhesives. Also, why choose soy protein-MUF?
3. “Putting the boards crosswise for 3 months in the laboratory, their moisture content reduced to 15%” why not directly dry them in the oven to the expected moisture content?
4. What’s the temperature to prepare glulam?
5. Is there any limitation for the AI analysis?
Author Response
Please see attached
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
This work is acceptable for publication.
Reviewer 2 Report
The authors have addressed my concerns. It can be accepted for publication.
