A three-way decision method based on hybrid data1

2021 ◽  
Vol 40 (5) ◽  
pp. 8639-8650
Author(s):  
Sheng Luo
Keyword(s):  
Artificial Intelligence ◽  
Mathematical Model ◽  
Information System ◽  
Data Analysis ◽  
Rough Set ◽  
Gaussian Kernel ◽  
Inclusion Degree ◽  
Decision Method ◽  
Hybrid Data ◽  
Conditional Attribute

An information system as a database that represents relationships between objects and attributes is an important mathematical model in the field of artificial intelligence. Hybrid data means boolean, categorical, real-valued, set-valued data and missing data in this paper. A hybrid information system is an information system where its attribute is hybrid data. This paper proposes a three-way decision method based on hybrid data. First, the distance between two objects based on the conditional attribute set in a given hybrid information system is developed and Gaussian kernel based on this distance is acquired. Then, the fuzzy Tcos-equivalence relation, induced by this information system, is obtained by using Gaussian kernel. Next, the decision-theoretic rough set model in this hybrid information system is presented. Moreover, a three-way decision method is given by means of this decision-theoretic rough set model and inclusion degree between two fuzzy sets. Finally, an example is employed to illustrate the feasibility of the proposed method, which may provide an effective method for hybrid data analysis in real applications.

Three-way decision for incomplete real-valued data

2020 ◽  
Vol 39 (5) ◽  
pp. 7843-7862
Author(s):  
Haili Wen ◽  
Fei Xia ◽  
Hongxiang Tang
Keyword(s):  
Information System ◽  
Decision Rule ◽  
Rough Set ◽  
Equivalence Relation ◽  
Risk Preference ◽  
Decision Makers ◽  
Gaussian Kernel ◽  
Decision Attributes ◽  
Different Levels ◽  
Conditional Attribute

An information system (IS) is a database that expresses relationships between objects and attributes. An IS with decision attributes is said to be a decision information system (DIS). An incomplete real-valued decision information system (IRVDIS) is a DIS based on incomplete real-valued data. This paper studies three-way decision (3WD) for incomplete real-valued data and its application. In the first place, the distance between two objects on the basis of the conditional attribute set in an IRVDIS is constructed. In the next place, the fuzzy Tcos-equivalence relation on the object set of an IRVDIS is received by means of Gaussian kernel. After that, the decision-theoretic rough set model for an IRVDIS is presented. Furthermore, the 3WD method is proposed based on this model. Lastly, to illustrate the feasibility of the proposed method, an application of the proposed method is given. It is worth mentioning that levels of risk may be determined by thresholds that can be directly acquired according to risk preference of different decision-makers, as well as the decision rule for each decision class under different levels of risk is showed in tabular forms.

scholarly journals Data analysis in Cashless Payment Systems

2021 ◽  
Vol 320 ◽  
pp. 03005
Author(s):  
Alexey Bataev ◽  
Antonina Glushkova
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Information System ◽  
Data Analysis ◽  
Financial Institutions ◽  
Comprehensive Analysis ◽  
Investment Model ◽  
Payment Systems ◽  
Payments System

The use of artificial intelligence in the financial sphere are analyzed in this study. One of the possible areas of using neural network in financial institutions is the system of cashless payments. One of the main problems in introducing innovative projects is to evaluate the efficiency of the implemented information system. In this regard, the construction of an investment model that allows evaluating the implementation and use of artificial intelligence in the cashless payments system of financial institutions is proposed in this article. Based on the constructed model, an analysis is made of the dependence of the effectiveness of the system with artificial intelligence on the size of the client base of a credit organization, while the minimum and maximum possible efficiency parameters of the implemented system are evaluated. Based on a comprehensive analysis, recommendations are given on perspectives of introducing such systems into credit organizations.

Representations of Vague Approximation Operators

2011 ◽  
Vol 282-283 ◽  
pp. 287-290
Author(s):  
Hai Dong Zhang ◽  
Yan Ping He
Keyword(s):  
Artificial Intelligence ◽  
Mathematical Model ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Fuzzy Relation ◽  
Partial Knowledge ◽  
Data Bases ◽  
Approximation Operators ◽  
Rough Approximation

As a suitable mathematical model to handle partial knowledge in data bases, rough set theory is emerging as a powerful theory and has been found its successive applications in the fields of artificial intelligence such as pattern recognition, machine learning, etc. In the paper, a vague relation is first defined, which is the extension of fuzzy relation. Then a new pair of lower and upper generalized rough approximation operators based on the vague relation is first proposed by us. Finally, the representations of vague rough approximation operators are presented.

Inclusion degree: a perspective on measures for rough set data analysis

2002 ◽  
Vol 141 (3-4) ◽  
pp. 227-236 ◽  
Author(s):  
Z.B Xu ◽  
J.Y Liang ◽  
C.Y Dang ◽  
K.S Chin
Keyword(s):  
Data Analysis ◽  
Rough Set ◽  
Inclusion Degree

THE INFLUENCE OF EDUCATIONAL LEVEL, WORK EXPERIENCE AND COMPREHENSION OF ACCOUNTING INFORMATION SYSTEM ON FINANCIAL REPORT QUALITY

2018 ◽  
Vol 4 (2) ◽  
pp. 33-42
Author(s):  
Fajar Adiyanto ◽  
Yuli Chomsatu Samrotun ◽  
Anita Wijayanti
Keyword(s):  
Information System ◽  
Data Analysis ◽  
Educational Level ◽  
Work Experience ◽  
Accounting Information ◽  
Primary Data ◽  
Multiple Series ◽  
Accounting Information System ◽  
Financial Report ◽  
Report Quality

This study is conducted to: 1) test and analyze the influence of educational level on financial report quality; 2) test and analyze the influence of work experience on financial report quality; 3) test and analyze the influence of accounting information system on financial report quality. This type of research i.e. research with quantitative data sources in this study is the primary data. Population in this study is all employees employed in district financial department in Surakarta with the sample amounted of 30 employees, where all population was taken as sample. The technique in this study use the question form. The data analysis in a linear regression multiple series program spss for windows version 17.0. From data analysis known that the variabel work experience (H2) and accounting information system comprehension (H3) have influence on financial report quality, and the educational level (H1) variable has no influence on financial report quality, with in the regression coefficient values show that showed a negative value i.e. t count-0.985 and significant value of 0.334

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