Rough Set Theory Application in Online Course Satisfaction

2011 ◽  
Vol 271-273 ◽  
pp. 1239-1242
Author(s):  
Shao Jun Chen
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Online Courses ◽  
Educational Environment ◽  
Course Satisfaction ◽  
Online Course ◽  
High Quality ◽  
Proposed Model ◽  
Theory Application

The most important issue for online courses is to provide learners with high quality satisfacion. In order to resolve the question and evaluating course satisfaction , rough set theory is proposed in this article, by which we reduce 10 attributes to 5 and get the index of value assessment.As a result, teachers can make an adjustment to achieve better effect in teaching by taking advantage of the method.The proposed model can be applied to not only a network environment but also remote educational environment.

A rough set theory application in forecasting models

2020 ◽  
Vol 3 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Haresh Sharma ◽  
◽  
Kriti Kumari ◽  
Samarjit Kar ◽  
◽  
...  
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Forecasting Models ◽  
Theory Application

scholarly journals Using Variable Precision Rough Set for Selection and Classification of Biological Knowledge Integrated in DNA Gene Expression

2012 ◽  
Vol 9 (3) ◽  
pp. 1-17 ◽  
Author(s):  
D. Calvo-Dmgz ◽  
J. F. Gálvez ◽  
D. Glez-Peña ◽  
S. Gómez-Meire ◽  
F. Fdez-Riverola
Keyword(s):  
Gene Expression ◽  
Set Theory ◽  
Rough Set ◽  
Microarray Data ◽  
Rough Set Theory ◽  
Biological Knowledge ◽  
Variable Precision ◽  
Gene Sets ◽  
Proposed Model ◽  
Variable Precision Rough Set

Summary DNA microarrays have contributed to the exponential growth of genomic and experimental data in the last decade. This large amount of gene expression data has been used by researchers seeking diagnosis of diseases like cancer using machine learning methods. In turn, explicit biological knowledge about gene functions has also grown tremendously over the last decade. This work integrates explicit biological knowledge, provided as gene sets, into the classication process by means of Variable Precision Rough Set Theory (VPRS). The proposed model is able to highlight which part of the provided biological knowledge has been important for classification. This paper presents a novel model for microarray data classification which is able to incorporate prior biological knowledge in the form of gene sets. Based on this knowledge, we transform the input microarray data into supergenes, and then we apply rough set theory to select the most promising supergenes and to derive a set of easy interpretable classification rules. The proposed model is evaluated over three breast cancer microarrays datasets obtaining successful results compared to classical classification techniques. The experimental results shows that there are not significat differences between our model and classical techniques but it is able to provide a biological-interpretable explanation of how it classifies new samples.

scholarly journals English poems categorization using text mining and rough set theory

2020 ◽  
Vol 9 (4) ◽  
pp. 1701-1710
Author(s):  
Saif Ali Alsaidi ◽  
Ahmed T. Sadeq ◽  
Hasanen S. Abdullah
Keyword(s):  
Text Mining ◽  
Set Theory ◽  
Rough Set ◽  
Text Categorization ◽  
Rough Set Theory ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Text Data ◽  
Data Set ◽  
Proposed Model

In recent years, Text Mining wasan important topic because of the growth of digital text data from many sources such as government document, Email, Social Media, Website, etc. The English poemsare one of the text data to categorization English Poems will use Text categorization, Text categorization is a method in which classify documents into one or more categories that were predefined the category based on the text content in a document .In this paper we will solve the problem of how to categorize the English poem into one of the English Poems categorizations by using text mining technique and Machine learning algorithm, Our data set consist of seven categorizations for poems the data set is divided into two-part training (learning)and testing data. In the proposed model we apply the text preprocessing for the documents file to reduce the number of feature and reduce dimensionality the preprocessing process converts the text poem to features and remove the irrelevant feature by using text mining process (tokenize,remove stop word and stemming), to reduce the feature vector of the remaining feature we usetwo methods for feature selection and use Rough set theory as machine learning algorithm to perform the categorization, and we get 88% success classification of the proposed model.

scholarly journals Decision-Making Method based on Mixed Integer Linear Programming and Rough Set: A Case Study of Diesel Engine Quality and Assembly Clearance Data

2019 ◽  
Vol 11 (3) ◽  
pp. 620 ◽  
Author(s):  
Wenbing Chang ◽  
Xinglong Yuan ◽  
Yalong Wu ◽  
Shenghan Zhou ◽  
Jingsong Lei ◽  
...  
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Mixed Integer Linear Programming ◽  
Rough Set Theory ◽  
Mixed Integer ◽  
Quality Level ◽  
Proposed Model

The purpose of this paper is to establish a decision-making system for assembly clearance parameters and machine quality level by analyzing the data of assembly clearance parameters of diesel engine. Accordingly, we present an extension of the rough set theory based on mixed-integer linear programming (MILP) for rough set-based classification (MILP-FRST). Traditional rough set theory has two shortcomings. First, it is sensitive to noise data, resulting in a low accuracy of decision systems based on rough sets. Second, in the classification problem based on rough sets, the attributes cannot be automatically determined. MILP-FRST has the advantages of MILP in resisting noisy data and has the ability to select attributes flexibly and automatically. In order to prove the validity and advantages of the proposed model, we used the machine quality data and assembly clearance data of 29 diesel engines of a certain type to validate the proposed model. Experiments show that the proposed decision-making method based on MILP-FRST model can accurately determine the quality level of the whole machine according to the assembly clearance parameters.

Sign in / Sign up

Export Citation Format

Share Document