Quality Prediction Model of KICA-JITL-LWPLS Based on Wavelet Kernel Function

Round 1

Reviewer 1 Report

The paper proposes a quality prediction model based on wavelet kernel functions. This method is verified for prediction of the bacteriophage concentration and penicillin concentration. Results prove the superiority of the proposed method over similar methods presented in literature.

Questions and remarks:

1) It would be interesting to compare the performance of the proposed prediction method with neural network based methods or at least present some discussion of the advantages of the proposed method over neural network methods

2) Some more details of implementation should be given - what platform and language, what libraries were used.

3) the proposed method should be compared against other methods for computational efficiency (computation time).

Minor remarks:

1) figure1 should be converted to vector graphics for better readability

2) figures with plots should also be converted to vector graphics and font size in the plots should be increased.

I recommend that this paper is accepted after incoporating revisions listed above.

Author Response

Please see the attachment.

Author Response File: Author Response.doc

Reviewer 2 Report

This paper proposes a KICA-JITL-LWPLS quality prediction model based on the wavelet kernel function. The paper is written well and signature sound. But there are some suggestions required for the authors to improve the manuscript.

1. Some equations are not presented properly and have no meaning. Must be written properly. Eq in line no 318, 367.

2. Figure 1 is not depicted properly. Must be clear.

3. Less amount of dataset is used in this work. For more accuracy, it must have an exceptionally large amount of data.

4. More visual representation can be used to show the effective results of comparison between the proposed and existing ones.

Author Response

Please see the attachment.

Author Response File: Author Response.doc