Electronic nose classification and differentiation of bacterial foodborne pathogens based on support vector machine optimized with particle swarm optimization algorithm-Reference-Cited by-同舟云学术

Electronic nose classification and differentiation of bacterial foodborne pathogens based on support vector machine optimized with particle swarm optimization algorithm

Published:2019-08-23 Issue:6 Volume:42 Page:
ISSN:0145-8876
Container-title:Journal of Food Process Engineering
language:en
Short-container-title:J Food Process Eng

Author:

Bonah Ernest¹²,Huang Xingyi¹^ORCID,Yi Ren¹³,Aheto Joshua H.¹,Osae Richard¹,Golly Moses¹

Affiliation:

1. School of Food and Biological EngineeringJiangsu University Zhenjiang Jiangsu PR China

2. Food and Drugs AuthorityLaboratory Services Department Cantonments Accra Ghana

3. School of Smart AgricultureSuzhou Polytechnic Institute of Agriculture Suzhou PR China

Funder

National Key Research and Development Program of China

Publisher

Wiley

Subject

General Chemical Engineering,Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfpe.13236

Reference52 articles.

1. A novel orthogonal PSO algorithm based on orthogonal diagonalization

2. A new hybrid firefly algorithm and particle swarm optimization for tuning parameter estimation in penalized support vector machine with application in chemometrics

3. Investigation of Different Gas Sensor-Based Artificial Olfactory Systems for Screening Salmonella typhimurium Contamination in Beef

4. Possible Application of Electronic Nose Systems for Meat Safety: An Overview

5. A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications

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