The Difference Between Probabilistic and Interval Reasoning Under Uncertainty

2002 ◽  
Author(s):  
Alexandre Chamanski
Keyword(s):  
Decision Analysis ◽  
Uncertain Information ◽  
Reasoning Under Uncertainty ◽  
The Difference ◽  
Interval Reasoning

The purpose of this study is to provide a basic comparison of the probabilistic and interval methodologies for processing uncertain information in decision analysis. The awareness of fundamental differences between these methodologies is considered to be useful not only for better understanding their principles, but also for their appropriate application.

Extended two-dimensional belief function based on divergence measurement

2020 ◽  
pp. 1-8
Author(s):  
Jianping Fan ◽  
Jing Wang ◽  
Meiqin Wu
Keyword(s):  
Belief Function ◽  
Distribution Functions ◽  
Divergence Measure ◽  
Uncertain Information ◽  
Belief Functions ◽  
Two Dimensional ◽  
Probability Distribution Functions ◽  
Basic Probability ◽  
The Difference ◽  
Supporting Degree

The two-dimensional belief function (TDBF = (mA, mB)) uses a pair of ordered basic probability distribution functions to describe and process uncertain information. Among them, mB includes support degree, non-support degree and reliability unmeasured degree of mA. So it is more abundant and reasonable than the traditional discount coefficient and expresses the evaluation value of experts. However, only considering that the expert’s assessment is single and one-sided, we also need to consider the influence between the belief function itself. The difference in belief function can measure the difference between two belief functions, based on which the supporting degree, non-supporting degree and unmeasured degree of reliability of the evidence are calculated. Based on the divergence measure of belief function, this paper proposes an extended two-dimensional belief function, which can solve some evidence conflict problems and is more objective and better solve a class of problems that TDBF cannot handle. Finally, numerical examples illustrate its effectiveness and rationality.

Information Disclosure in Contests with Endogenous Entry: An Experiment

2020 ◽  
Vol 66 (11) ◽  
pp. 5128-5150
Author(s):  
Luke Boosey ◽  
Philip Brookins ◽  
Dmitry Ryvkin
Keyword(s):  
Decision Analysis ◽  
Laboratory Experiment ◽  
Information Disclosure ◽  
Endogenous Entry ◽  
Outside Option ◽  
Second Stage ◽  
Aggregate Investment ◽  
The Difference ◽  
Positive Effect

We use a laboratory experiment to study the effects of disclosing the number of active participants in contests with endogenous entry. At the first stage, potential participants decide whether to enter competition, and at the second stage, entrants choose their investments. In a 2[Formula: see text]2 design, we manipulate the size of the outside option, [Formula: see text], and whether the number of entrants is disclosed between the stages. Theory predicts more entry for lower [Formula: see text] and the levels of entry and aggregate investment to be independent of disclosure in all cases. We find empirical entry frequencies decreasing with [Formula: see text]. For aggregate investment, we find no effect of disclosure when [Formula: see text] is low but a strong positive effect of disclosure when [Formula: see text] is high. The difference is driven by substantial overinvestment in contests with a small, publicly known number of players contrasted by more restrained investment in contests in which the number of players is uncertain and may be small. The behavior under disclosure is explained by a combination of joy of winning and entry regret. This paper was accepted by Yan Chen, decision analysis.

scholarly journals An Improved Belief Entropy and Its Application in Decision-Making

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Deyun Zhou ◽  
Yongchuan Tang ◽  
Wen Jiang
Keyword(s):  
Decision Making ◽  
Mass Function ◽  
The Body ◽  
Uncertain Information ◽  
Uncertainty Measure ◽  
Numerical Examples ◽  
Fusion Applications ◽  
Belief Entropy ◽  
The Difference ◽  
Available Information

Uncertainty measure in data fusion applications is a hot topic; quite a few methods have been proposed to measure the degree of uncertainty in Dempster-Shafer framework. However, the existing methods pay little attention to the scale of the frame of discernment (FOD), which means a loss of information. Due to this reason, the existing methods cannot measure the difference of uncertain degree among different FODs. In this paper, an improved belief entropy is proposed in Dempster-Shafer framework. The proposed belief entropy takes into consideration more available information in the body of evidence (BOE), including the uncertain information modeled by the mass function, the cardinality of the proposition, and the scale of the FOD. The improved belief entropy is a new method for uncertainty measure in Dempster-Shafer framework. Based on the new belief entropy, a decision-making approach is designed. The validity of the new belief entropy is verified according to some numerical examples and the proposed decision-making approach.

Visualizing Uncertain Information

1992 ◽  
pp. 10-19 ◽  
Author(s):  
Alan M. MacEachren
Keyword(s):  
Data Quality ◽  
User Interfaces ◽  
Conceptual Models ◽  
Policy Formulation ◽  
Spatial Uncertainty ◽  
Uncertain Information ◽  
Early Stages ◽  
Scientific Analysis ◽  
The Difference

When a GIS is used to drive map-based visualization, exploration of potential relationships takes precedence over presentation of facts. In these early stages of scientific analysis or policy formulation, providing a way for analysts to assess uncertainty in the data they are exploring is critical to the perspectives they form and the approaches they decide to pursue. As a basis from which to develop methods for visualizing uncertain information, this paper addresses the difference between data quality and uncertainty, the application of Berlin's graphic variables to the representation of uncertainty, conceptual models of spatial uncertainty as they relate to kinds of cartographic symbolization, and categories of user interfaces suited to presenting data and uncertainty about that data. Also touched on is the issue of how we might evaluate our attempts to depict uncertain information on maps.

Intelligent reasoning and management decision making with grey rough influence diagrams

2016 ◽  
Vol 9 (4) ◽  
pp. 336-353 ◽  
Author(s):  
Haiqing Hu ◽  
Bingqiang Liu ◽  
Tao Shen
Keyword(s):  
Information Systems ◽  
Decision Analysis ◽  
Rough Sets ◽  
Grey System Theory ◽  
Approximate Reasoning ◽  
Influence Diagrams ◽  
Uncertain Information ◽  
Content Type ◽  
Intelligent Decision ◽  
Interval Valued

Purpose Influence diagrams (IDs) have been widely applied as a form of knowledge expression and a decision analysis tool in the management and engineering fields. Relationship measurements and expectation values are computed depending on probability distributions in traditional IDs, however, most information systems in the real world are nondeterministic, and data in information tables can be interval valued, multiple valued and even incomplete. Consequently, conventional numeric models of IDs are not suitable for information processing with respect to imprecise data whose boundaries are uncertain. The paper aims to discuss these issues. Design/methodology/approach The grey system theory and rough sets have proved to be effective tools in the data processing of uncertain information systems, approximate knowledge acquisition and representation are also the objectives in intelligent reasoning and decision analysis. Hence, this study proposes a new mathematical model by combining grey rough sets with IDs, and approximate measurements are used instead of probability distribution, an implicational relationship is utilized instead of an indiscernible relationship, and all of the features of the proposed approach contribute to deal with uncertain problems. Findings The focus of this paper is to provide a more comprehensive framework for approximate knowledge representation and intelligent decision analysis in uncertain information systems and an example of decision support in product management systems with the new approach is illustrated. Originality/value Collaboration of IDs and grey rough sets is first proposed, which provides a new mathematical and graphical tool for approximate reasoning and intelligent decision analysis within interval-valued information systems.

scholarly journals Detecting, modeling and quantifying differences in terms meaning, in BIM environment

2018 ◽  
Vol 146 ◽  
pp. 01004 ◽  
Author(s):  
Miroslav Sůra
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Computer Processing ◽  
Formal Definitions ◽  
Scaling Methods ◽  
The Difference ◽  
Reliable Basis

Professional tasks in BIM involve sharing information among many participants, and require the use of the most precise terms to meet the following conditions. First, the user (reader) must not hesitate over the meaning. Second, various users should understand them alike, or better – in the same way. Less vague expressions provide more reliable basis for decision analysis and decision making, and for a joint, seamless, unquestionable consensus. Formal definitions of terms are used for that purpose where necessary, e.g. for logical or computer processing, but other terms remain or need to remain without such precise formal definitions. The principles for comparing difference in understanding the meaning of a term by different subjects are examined. We specify principles for measuring and calculating difference in, and vagueness of, meaning. Then, variables and scaling methods are proposed to measure the difference in and vagueness of meaning. The presented measuring scales can be applied for example in the process of refinement, unifying or splitting BIM terms, or group consistency in understanding a BIM-oriented terms can be assessed using the concept of vagueness.

The Origin of the Moon

1962 ◽  
Vol 14 ◽  
pp. 149-155 ◽  
Author(s):  
E. L. Ruskol
Keyword(s):  
Chemical Composition ◽  
Solar System ◽  
The Moon ◽  
The Earth ◽  
The Difference ◽  
Origin Of The Moon

The difference between average densities of the Moon and Earth was interpreted in the preceding report by Professor H. Urey as indicating a difference in their chemical composition. Therefore, Urey assumes the Moon's formation to have taken place far away from the Earth, under conditions differing substantially from the conditions of Earth's formation. In such a case, the Earth should have captured the Moon. As is admitted by Professor Urey himself, such a capture is a very improbable event. In addition, an assumption that the “lunar” dimensions were representative of protoplanetary bodies in the entire solar system encounters great difficulties.

Influence of Cell Wall Composition on the Fossilisation of Bacteria and the Implications for the Search for Early Life Forms

1997 ◽  
Vol 161 ◽  
pp. 491-504 ◽  
Author(s):  
Frances Westall
Keyword(s):  
Cell Wall ◽  
Life Forms ◽  
Cation Binding ◽  
Positive Bacterium ◽  
Gram Positive ◽  
Gram Positive Bacteria ◽  
Transmission Electron ◽  
Hydrothermal Sediments ◽  
Identification Of Bacteria ◽  
The Difference

AbstractThe oldest cell-like structures on Earth are preserved in silicified lagoonal, shallow sea or hydrothermal sediments, such as some Archean formations in Western Australia and South Africa. Previous studies concentrated on the search for organic fossils in Archean rocks. Observations of silicified bacteria (as silica minerals) are scarce for both the Precambrian and the Phanerozoic, but reports of mineral bacteria finds, in general, are increasing. The problems associated with the identification of authentic fossil bacteria and, if possible, closer identification of bacteria type can, in part, be overcome by experimental fossilisation studies. These have shown that not all bacteria fossilise in the same way and, indeed, some seem to be very resistent to fossilisation. This paper deals with a transmission electron microscope investigation of the silicification of four species of bacteria commonly found in the environment. The Gram positiveBacillus laterosporusand its spore produced a robust, durable crust upon silicification, whereas the Gram negativePseudomonas fluorescens, Ps. vesicularis, andPs. acidovoranspresented delicately preserved walls. The greater amount of peptidoglycan, containing abundant metal cation binding sites, in the cell wall of the Gram positive bacterium, probably accounts for the difference in the mode of fossilisation. The Gram positive bacteria are, therefore, probably most likely to be preserved in the terrestrial and extraterrestrial rock record.

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