Comparison of Gaussian process regression, artificial neural network, and response surface methodology modeling approaches for predicting drying time of mosambi ( Citrus limetta ) peel-Reference-Cited by-同舟云学术

Comparison of Gaussian process regression, artificial neural network, and response surface methodology modeling approaches for predicting drying time of mosambi ( Citrus limetta ) peel

Published:2018-12-04 Issue:2 Volume:42 Page:e12966
ISSN:0145-8876
Container-title:Journal of Food Process Engineering
language:en
Short-container-title:J Food Process Eng

Author:

Chaurasia Parul¹,Younis Kaiser¹,Qadri Ovais Shafiq¹,Srivastava Gaurav²,Osama Khwaja¹^ORCID

Affiliation:

1. Department of BioengineeringIntegral University Lucknow Uttar Pradesh India

2. Department of BiotechnologyInstitute of Engineering and Technology, Bundelkhand University Jhansi Uttar Pradesh India

Publisher

Wiley

Subject

General Chemical Engineering,Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfpe.12966

Reference30 articles.

1. Artificial neural networks (ANN) approach for modeling of removal of Lanaset Red G on Chara contraria

2. Comparison of artificial neural network (ANN) and response surface methodology (RSM) in fermentation media optimization: Case study of fermentative production of scleroglucan

3. Optimization of hot air drying of olive leaves using response surface methodology

4. Comparison of genetic algorithm and neural network approaches for the drying process of carrot

5. Comparison of response surface and neural network with other methods for structural reliability analysis

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