Application of rough set theory for evaluating polysaccharides extraction

Authors:
Shuang Liu;Lijun Sun;Yurong Guo;Jialin Gao;Lei Liu
Affiliations:
Xinhua School of Finance and Insurance, Zhongnan University of Economics and Law, Wuhan, P.R.China;College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, P.R. China;College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, P.R. China;College of Food Engineering and Nutritional Science, Shaanxi Normal University, Xi'an, P.R. China;College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, P.R. China
Venue:
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Year:
2011

Citing 13
Cited 0

Rough set algorithms in classification problem

Rough set methods and applications
Rough Sets: Theoretical Aspects of Reasoning about Data

Rough Sets: Theoretical Aspects of Reasoning about Data
Reduction algorithms based on discernibility matrix: the ordered attributes method

Journal of Computer Science and Technology
A reduction algorithm meeting users' requirements

Journal of Computer Science and Technology
Feature Selection via Discretization

IEEE Transactions on Knowledge and Data Engineering
A Rough Set-Aided System for Sorting WWW Bookmarks

WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
Data mining tasks and methods: Rule discovery: rough set approaches for discovering rules and attribute dependencies

Handbook of data mining and knowledge discovery
Probabilistic approach to rough sets

International Journal of Approximate Reasoning
Criteria for choosing a rough set model

Computers & Mathematics with Applications
The superiority of three-way decisions in probabilistic rough set models

Information Sciences: an International Journal
The application of rough set and Mahalanobis distance to enhance the quality of OSA diagnosis

Expert Systems with Applications: An International Journal
Early warning of enterprise decline in a life cycle using neural networks and rough set theory

Expert Systems with Applications: An International Journal
On reduct construction algorithms

RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper reports an application of rough set theory for evaluating polysaccharides extraction from apple pomace. The importance of factors affecting polysaccharides yield is analyzed by the means of attribute reduction. The significances of four factors are obtained. It is found that extraction time and ratio of solution to sample are the dominant factors. The results show that rough set theory can effectively analyze and evaluate factors influencing polysaccharides yield from apple pomace and can be used in the analysis of extraction of functional components in foods.