Model-based diagnosis of incomplete discrete-event system with rough set theory

2016 ◽  
Vol 60 (1) ◽  
Author(s):  
Xuena Geng ◽  
Dantong Ouyang ◽  
Yonggang Zhang
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Discrete Event ◽  
Discrete Event System ◽  
Model Based ◽  
Event System

scholarly journals Support or Risk? Software Project Risk Assessment Model Based on Rough Set Theory and Backpropagation Neural Network

2019 ◽  
Vol 11 (17) ◽  
pp. 4513 ◽  
Author(s):  
Xiaoqing Li ◽  
Qingquan Jiang ◽  
Maxwell K. Hsu ◽  
Qinglan Chen
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Attribute Reduction ◽  
Assessment Model ◽  
Software Project ◽  
Risk Assessment Model ◽  
Backpropagation Neural Network ◽  
Model Based ◽  
Sample Data

Software supports continuous economic growth but has risks of uncertainty. In order to improve the risk-assessing accuracy of software project development, this paper proposes an assessment model based on the combination of backpropagation neural network (BPNN) and rough set theory (RST). First, a risk list with 35 risk factors were grouped into six risk categories via the brainstorming method and the original sample data set was constructed according to the initial risk list. Subsequently, an attribute reduction algorithm of the rough set was used to eliminate the redundancy attributes from the original sample dataset. The input factors of the software project risk assessment model could be reduced from thirty-five to twelve by the attribute reduction. Finally, the refined sample data subset was used to train the BPNN and the test sample data subset was used to verify the trained BPNN. The test results showed that the proposed joint model could achieve a better assessment than the model based only on the BPNN.

The Applications Based on the Rough Set Theory Algorithms to Determine the Weight

2014 ◽  
Vol 989-994 ◽  
pp. 1736-1738
Author(s):  
Ning Ning Chen
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Model Based

This paper puts forward on the Rough Set theory algorithms, and combined it with the method of determining the index weights, then established a weight determined algorithm model based on rough set, Thereby reducing the influence of subjective factors on the weight determination.

Automated Valuation Model based on fuzzy and rough set theory for real estate market with insufficient source data

2019 ◽  
Vol 87 ◽  
pp. 104021 ◽  
Author(s):  
Malgorzata Renigier-Biłozor ◽  
Artur Janowski ◽  
Maurizio d’Amato
Keyword(s):  
Real Estate ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Real Estate Market ◽  
Model Based ◽  
Valuation Model ◽  
Source Data ◽  
Automated Valuation
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