scholarly journals Measures of Uncertainty for a Four-Hybrid Information System and Their Applications

2021 ◽  
Author(s):  
Bin Qin ◽  
Fanping Zeng ◽  
Kesong Yan
Keyword(s):  
Information System ◽  
Missing Data ◽  
Distance Function ◽  
Information Structure ◽  
Attribute Reduction ◽  
Information Structures ◽  
Tolerance Relation ◽  
Effectiveness Analysis ◽  
Entropy Measures

Abstract A four-hybrid information system (4HIS) is an information system (IS) where the dataset of object descriptions consists of categorical, boolean, real-valued and missing data or attributes. This paper studies measures of uncertainty for a 4HIS and its application in attribute reduction. The distance function for each type of attribute in a 4HIS is first provided. Then, this distance is used to produce the tolerance relation induced by a given subsystem in a 4HIS. Next, information structure of this subsystem is proposed in terms of a set vector and dependence between information structures is introduced. Moreover, granulation and entropy measures in a 4HIS are investigated on the basis of information structures. In order to verify the feasibility of the proposed measures, effectiveness analysis is performed from a statistical perspective. Finally, an application of the proposed measures for attribute reduction in a 4HIS is given.

Information structures and uncertainty in an image information system

2021 ◽  
Vol 40 (1) ◽  
pp. 295-317
Author(s):  
Gangqiang Zhang ◽  
Zhaowen Li ◽  
Pengfei Zhang ◽  
Ningxin Xie
Keyword(s):  
Information System ◽  
Kernel Method ◽  
Attribute Reduction ◽  
Gaussian Kernel ◽  
Information Structures ◽  
Image Information ◽  
Effectiveness Analysis ◽  
Uncertainty Measurement ◽  
Properties Of Information ◽  
Information Values

An information system as a database that stands for relationships between objects and attributes is an important mathematical model. An image information system is an information system where each of its information values is an image and its information structures embody internal features of this type of information system. Uncertainty measurement is an effective tool for evaluation. This paper explores measures of uncertainty for an information system by using the proposed information structures. The distance between two objects in an image information system is first given. After that, the fuzzy Tcos-equivalence relation, induced by this system by using Gaussian kernel method, is obtained, where Gaussian kernel is based on this distance. Next, information structures of this system are described by set vectors, dependence between information structures is studied and properties of information structures are given by using inclusion degree, and application for information structures and uncertainty measures of an image information system are investigated by the information structures. Moreover, effectiveness analysis is done to show the feasibility of the proposed measures from the angle of statistics. Finally, an application of the proposed measurement for attribute reduction is given. These results will be helpful for understanding the essence of uncertainty in an image information system.

Information structures and entropy measurement for a fuzzy probabilistic information system

2021 ◽  
pp. 1-19
Author(s):  
Yanling He ◽  
Chunji Yao
Keyword(s):  
Information System ◽  
Information Structure ◽  
Granular Computing ◽  
Basic Structure ◽  
Fuzzy Relations ◽  
Information Structures ◽  
Inclusion Degree ◽  
Probabilistic Information ◽  
Entropy Measurement ◽  
Types Of Information

An information system (IS), an important model in the field of artificial intelligence, takes information structure as the basic structure. A fuzzy probabilistic information system (FPIS) is the combination of some fuzzy relations in the same universe that satisfy probability distribution. A FPIS as an IS with fuzzy relations includes three types of uncertainties (i.e., roughness, fuzziness and probability). This paper studies information structures in a FPIS from the perspective of granular computing (GrC). Firstly, two types of information structures in a FPIS are defined by set vectors. Then, equality, dependence and independence between information structures in a FPIS are proposed, and they are depicted by means of the inclusion degree. Next, information distance between information structures in a FPIS is presented. Finally, entropy measurement for a FPIS is investigated based on the proposed information structures. These results may be helpful for understanding the nature of structures and uncertainty in a FPIS.

Information structures in a fuzzy β-covering information system

2021 ◽  
pp. 1-26
Author(s):  
Rui-Lin Liu ◽  
Hai-Long Yang ◽  
Li-Juan Zhang
Keyword(s):  
Information System ◽  
Information Systems ◽  
Data Compression ◽  
Information Structure ◽  
Information Structures ◽  
Concept Of Information

This paper studies information structures in a fuzzy β-covering information system. We introduce the concepts of a fuzzy β-covering information system and homomorphism between them, and investigate related properties. The concept of information structure of a fuzzy β-covering information system is given. We discuss the relationships between information structures from the view of dependence and separation. Then granularity measures for a fuzzy β-covering information system are studied. Finally, we discuss invariance of fuzzy β-covering information systems under homomorphism and illustrate its application on data compression.

scholarly journals Uncertainty Measurement for a Set-Valued Information System: Gaussian Kernel Method

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 199 ◽  
Author(s):  
Jiali He ◽  
Pei Wang ◽  
Zhaowen Li
Keyword(s):  
Information System ◽  
Equivalence Relation ◽  
Kernel Method ◽  
Gaussian Kernel ◽  
Intrinsic Properties ◽  
Information Structures ◽  
Effectiveness Analysis ◽  
Uncertainty Measurement ◽  
Properties Of Information

A set-valued information system (SIS) is the generalization of a single-valued informationsystem. This article explores uncertainty measurement for a SIS by using Gaussian kernel. The fuzzyTcos-equivalence relation lead by a SIS is first obtained by using Gaussian kernel. Then, informationstructures in this SIS are described by set vectors. Next, dependence between information structuresis presented and properties of information structures are investigated. Lastly, uncertainty measuresof a SIS are presented by using its information structures. Moreover, effectiveness analysis is doneto assess the feasibility of our presented measures. The consequence of this article will help usunderstand the intrinsic properties of uncertainty in a SIS.

The Value of Information in the Hold-Up Problem

2004 ◽  
Vol 5 (2) ◽  
pp. 177-203 ◽  
Author(s):  
Thomas Pfeiffer
Keyword(s):  
Information System ◽  
Information Structure ◽  
Value Of Information ◽  
The Other ◽  
Information Control ◽  
Ceteris Paribus ◽  
Head Office ◽  
Specific Investments ◽  
Negative Effect ◽  
Central Management

Abstract In the literature, the information structure of the hold-up problem is typically assumed to be exogenous. In this paper, we introduce an additional stage at which the head office may grant individual divisions access to an information system before they undertake their specific investments. Although more information ceteris paribus enhances each divisions’ profits, more information can reduce divisions’ investments and destroy synergies for the other division that would have been generated by the investments. If this negative effect dominates, then information can be harmful for the entire company. Hence, information control can be a subtle force to deal with the hold-up problem to a certain extent. In this paper we analyze those conditions under which information is either harmful or beneficial for central management.

Radiator threat evaluation with missing data based on improved technique for order preference by similarity to ideal solution

2021 ◽  
pp. 1-10
Author(s):  
Yu-Heng Xu ◽  
Si-Yi Cheng ◽  
Hu-Biao Zhang
Keyword(s):  
Missing Data ◽  
Prior Knowledge ◽  
Attribute Reduction ◽  
Estimation Algorithm ◽  
Weighted Averaging ◽  
Ideal Solution ◽  
Attribute Weights ◽  
Order Preference ◽  
Improved Technique ◽  
Threat Evaluation

To solve the problem of the missing data of radiator during the aerial war, and to address the problem that traditional algorithms rely on prior knowledge and specialized systems too much, an algorithm for radiator threat evaluation with missing data based on improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been proposed. The null estimation algorithm based on Induced Ordered Weighted Averaging (IOWA) is adopted to calculate the aggregate value for predicting missing data. The attribute reduction is realized by using the Rough Sets (RS) theory, and the attribute weights are reasonably allocated with the theory of Shapley. Threat degrees can be achieved through quantization and ranking of radiators by constructing a TOPSIS decision space. Experiment results show that this algorithm can solve the incompleteness of radiator threat evaluation, and the ranking result is in line with the actual situation. Moreover, the proposed algorithm is highly automated and does not rely on prior knowledge and expert systems.

scholarly journals Two Remarks on Blackwell's Theorem

2008 ◽  
Vol 45 (02) ◽  
pp. 580-586 ◽  
Author(s):  
Ehud Lehrer ◽  
Eran Shmaya
Keyword(s):  
Decision Maker ◽  
Information Structure ◽  
Decision Problem ◽  
Partial Information ◽  
The Other ◽  
Actual State ◽  
Information Structures ◽  
Comparison Of Experiments ◽  
Classical Characterization ◽  
Blackwell's Theorem

In a decision problem with uncertainty a decision maker receives partial information about the actual state via an information structure. After receiving a signal, he is allowed to withdraw and gets zero profit. We say that one structure is better than another when a withdrawal option exists if it may never happen that one structure guarantees a positive profit while the other structure guarantees only zero profit. This order between information structures is characterized in terms that are different from those used by Blackwell's comparison of experiments. We also treat the case of a malevolent nature that chooses a state in an adverse manner. It turns out that Blackwell's classical characterization also holds in this case.

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