Food Product Design: A Hybrid Machine Learning and Mechanistic Modeling Approach-Reference-Cited by-同舟云学术

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Food Product Design: A Hybrid Machine Learning and Mechanistic Modeling Approach

Published:2019-08-12 Issue:36 Volume:58 Page:16743-16752
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Zhang Xiang¹,Zhou Teng²^ORCID,Zhang Lei³^ORCID,Fung Ka Yip¹,Ng Ka Ming¹^ORCID

Affiliation:

1. Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China

2. Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany

3. Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology, Dalian 116012, China

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.9b02462

Reference46 articles.

1. Product/Process integration in food manufacture: Engineering sustained health

2. New insights into consumer-led food product development

3. A methodology for simultaneous process and product design in the formulated consumer products industry: The case study of the detergent business

4. Integrated process and product analysis: A multiscale approach to paint spray

5. Design of fuel additives using neural networks and evolutionary algorithms

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