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Journal articles on the topic 'Uncertainty (Information theory)'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 July 2024

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1

Egghe, Leo. "Uncertainty and information: Foundations of generalized information theory." Journal of the American Society for Information Science and Technology 58, no. 5 (2007): 756–58. http://dx.doi.org/10.1002/asi.20519.

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2

Shokry, M., and Manar Omran. "The Information System by Uncertainty Theory." Journal of Engineering Research 3, no. 12 (December 1, 2019): 35–40. http://dx.doi.org/10.21608/erjeng.2019.125749.

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Tang, Yongchuan, Yong Chen, and Deyun Zhou. "Measuring Uncertainty in the Negation Evidence for Multi-Source Information Fusion." Entropy 24, no. 11 (November 2, 2022): 1596. http://dx.doi.org/10.3390/e24111596.

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Dempster–Shafer evidence theory is widely used in modeling and reasoning uncertain information in real applications. Recently, a new perspective of modeling uncertain information with the negation of evidence was proposed and has attracted a lot of attention. Both the basic probability assignment (BPA) and the negation of BPA in the evidence theory framework can model and reason uncertain information. However, how to address the uncertainty in the negation information modeled as the negation of BPA is still an open issue. Inspired by the uncertainty measures in Dempster–Shafer evidence theory,

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4

Yan, Xi-zu, and Zhong-min Song. "The portfolio models of contained grey profit under uncertainty." Grey Systems: Theory and Application 4, no. 3 (October 28, 2014): 487–94. http://dx.doi.org/10.1108/gs-09-2014-0035.

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Purpose – The purpose of this paper is to establish the portfolio models of contained grey profit under uncertainty, and the results are applied to solve uncertain investment problem. Design/methodology/approach – In investment problems, uncertainties may exist in model parameters and input data. For the investment problems contained grey profit and incomplete information about natural world state, according to the portfolio theory, the grey systems theory and the uncertainty decision theory, the paper puts forward portfolio models and the methods. Findings – Traditional uncertainty decision i

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Yang, Bin, Dingyi Gan, Yongchuan Tang, and Yan Lei. "Incomplete Information Management Using an Improved Belief Entropy in Dempster-Shafer Evidence Theory." Entropy 22, no. 9 (September 7, 2020): 993. http://dx.doi.org/10.3390/e22090993.

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Quantifying uncertainty is a hot topic for uncertain information processing in the framework of evidence theory, but there is limited research on belief entropy in the open world assumption. In this paper, an uncertainty measurement method that is based on Deng entropy, named Open Deng entropy (ODE), is proposed. In the open world assumption, the frame of discernment (FOD) may be incomplete, and ODE can reasonably and effectively quantify uncertain incomplete information. On the basis of Deng entropy, the ODE adopts the mass value of the empty set, the cardinality of FOD, and the natural const

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YOU, CUILIAN. "UNCERTAINTY EXTENSION THEOREM AND PRODUCT UNCERTAIN MEASURE." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 18, no. 02 (April 2010): 197–208. http://dx.doi.org/10.1142/s0218488510006489.

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The additivity axiom of classical measure theory has been challenged by many mathematicians. Different replacements of the additivity correspond with different theory. In uncertainty theory, the additivity is replaced with self-duality and countable subadditivity. Similar to classical measure theory, there are some properties studied in uncertainty theory. Given the measure of each singleton set, the measure can be fully and uniquely determined in the sense of the maximum uncertainty principle. Generally speaking, a product uncertain measure may be defined in many ways, in this paper, a kind o

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Li, Xihua, Fuqiang Wang, and Xiaohong Chen. "Trapezoidal Intuitionistic Fuzzy Multiattribute Decision Making Method Based on Cumulative Prospect Theory and Dempster-Shafer Theory." Journal of Applied Mathematics 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/279138.

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With respect to decision making problems under uncertainty, a trapezoidal intuitionistic fuzzy multiattribute decision making method based on cumulative prospect theory and Dempster-Shafer theory is developed. The proposed method reflects behavioral characteristics of decision makers, information fuzziness under uncertainty, and uncertain attribute weight information. Firstly, distance measurement and comparison rule of trapezoidal intuitionistic fuzzy numbers are used to derive value function under trapezoidal intuitionistic fuzzy environment. Secondly, the value function and decision weight

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Lee, Jejung, Abdallah Sayyed-Ahmad, and Dong-Hoon Sheen. "Basin model inversion using information theory and seismic data." GEOPHYSICS 72, no. 6 (November 2007): R99—R108. http://dx.doi.org/10.1190/1.2757738.

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We present a new approach to basin-model inversion in which uncertain parameters in a basin model are estimated using information theory and seismic data. We derive a probability function from information theory to quantify uncertainties in the estimated parameters in basin modeling. The derivation requires two constraints: a normalization and a misfit constraint. The misfit constraint uses seismic information by minimizing the difference between calculated seismograms from a basin simulator and observed seismograms. The information-theory approach emphasizes the relative difference between th

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9

Zhang, Shao Pu, and Tao Feng. "Uncertainty Measure Based on Evidence Theory." Applied Mechanics and Materials 329 (June 2013): 344–48. http://dx.doi.org/10.4028/www.scientific.net/amm.329.344.

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Evidence theory is an effective method to deal with uncertainty information. And uncertainty measure is to reflect the uncertainty of an information system. Thus we want to merge evidence theory with uncertainty method in order to measure the roughness of a rough approximation space. This paper discusses the information fusion and uncertainty measure based on rough set theory. First, we propose a new method of information fusion based on the Bayse function, and define a pair of belief function and plausibility function using the fused mass function in an information system. Then we construct e

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10

He, Rongheng, Hui Li, Bo Zhang, and Mei Chen. "The multi-level warehouse layout problem with uncertain information: uncertainty theory method." International Journal of General Systems 49, no. 5 (June 22, 2020): 497–520. http://dx.doi.org/10.1080/03081079.2020.1778681.

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11

Rains, Stephen A., and Riva Tukachinsky. "Information Seeking in Uncertainty Management Theory: Exposure to Information About Medical Uncertainty and Information-Processing Orientation as Predictors of Uncertainty Management Success." Journal of Health Communication 20, no. 11 (July 2015): 1275–86. http://dx.doi.org/10.1080/10810730.2015.1018641.

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12

Wright, Lesley F. "Information Gap Decision Theory: Decisions under Severe Uncertainty." Journal of the Royal Statistical Society: Series A (Statistics in Society) 167, no. 1 (February 2004): 185–86. http://dx.doi.org/10.1111/j.1467-985x.2004.298_4.x.

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13

Brennan, M. D., R. Cheong, and A. Levchenko. "How Information Theory Handles Cell Signaling and Uncertainty." Science 338, no. 6105 (October 18, 2012): 334–35. http://dx.doi.org/10.1126/science.1227946.

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14

Nearing, Grey S., and Hoshin V. Gupta. "Ensembles vs. information theory: supporting science under uncertainty." Frontiers of Earth Science 12, no. 4 (May 9, 2018): 653–60. http://dx.doi.org/10.1007/s11707-018-0709-9.

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15

Zhou, Honggeng. "An Empirical Test of the Information Processing Theory." International Journal of Information Systems and Supply Chain Management 4, no. 1 (January 2011): 45–59. http://dx.doi.org/10.4018/jisscm.2011010103.

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According to the propositions in the information processing theory, this study tests the relationship between task uncertainty and three organizational design strategies, i.e., creation of lateral relationships, investment in information systems, and creation of self-contained tasks. Data from 125 North American manufacturing firms are used and business environment uncertainty is employed to measure task uncertainty. Sourcing practice and delivery practice measure the creation of lateral relationships, while Information quality measures the investment in information systems. Also, just-in-time

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16

Menin, Boris. "Uncovering the Hidden Information: A Novel Approach to Modeling Physical Phenomena Through Information Theory." Applied Physics Research 15, no. 1 (April 13, 2023): 101. http://dx.doi.org/10.5539/apr.v15n1p101.

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The growing need to study more complex physical phenomena and technological processes determines the importance of reducing the uncertainty of formulated models. However, measurement theory does not provide a clear answer to the question of how to calculate and use model structure uncertainty: the presence of certain base quantities and derived variables. The key novelty of this research lies in the informational method, which allows you to find the value of the uncertainty of the model of the phenomenon that has a certain structure. This uncertainty is initial and precedes the definition of u

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17

Szmidt, Eulalia. "Uncertainty and Information: Foundations of Generalized Information Theory (Klir, G.J.; 2006)." IEEE Transactions on Neural Networks 18, no. 5 (September 2007): 1551. http://dx.doi.org/10.1109/tnn.2007.906888.

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18

Saldanha, Terence, Mariana Andrade-Rojas, Abhishek Kathuria, Jiban Khuntia, and Mayuram Krishnan. "How the Locus of Uncertainty Shapes the Influence of CEO Long-term Compensation on Information Technology Capital Investments." MIS Quarterly 48, no. 2 (June 1, 2024): 459–90. http://dx.doi.org/10.25300/misq/2023/17433.

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Firms must allocate resources effectively to cope with uncertainty, which can manifest as a disruption and an opportunity. Although information technology (IT) is a means to cope with uncertainty, chief executive officers (CEOs) may not always support IT investments due to the risky nature of IT, especially when facing uncertain conditions. While prior research suggests that CEO long-term compensation positively incentivizes IT investments, little is known about how different loci of uncertainty impact this relationship. To address this research gap, we study how firm-specific uncertainty and

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19

Westover, M. Brandon, Nathaniel A. Eiseman, Sydney S. Cash, and Matt T. Bianchi. "Information Theoretic Quantification of Diagnostic Uncertainty." Open Medical Informatics Journal 6, no. 1 (December 14, 2012): 36–50. http://dx.doi.org/10.2174/1874431101206010036.

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Diagnostic test interpretation remains a challenge in clinical practice. Most physicians receive training in the use of Bayes’ rule, which specifies how the sensitivity and specificity of a test for a given disease combine with the pre-test probability to quantify the change in disease probability incurred by a new test result. However, multiple studies demonstrate physicians’ deficiencies in probabilistic reasoning, especially with unexpected test results. Information theory, a branch of probability theory dealing explicitly with the quantification of uncertainty, has been proposed as an alte

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20

Yan, Ruixia, Liangui Peng, Yanxi Xie, and Xiaoli Wang. "Rough Set-Game Theory Information Mining Model Considering Opponents’ Information." Electronics 11, no. 2 (January 13, 2022): 244. http://dx.doi.org/10.3390/electronics11020244.

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In multi-strategy games, the increase in the number of strategies makes it difficult to make a solution. To maintain the competition advantage and obtain maximal profits, one side of the game hopes to predict the opponent’s behavior. Building a model to predict an opponent’s behavior is helpful. In this paper, we propose a rough set-game theory model (RS-GT) considering uncertain information and the opponent’s decision rules. The uncertainty of strategies is obtained based on the rough set method, and an accurate solution is obtained based on game theory from the rough set-game theory model. T

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21

Wang, Jing, Jing Wang, Jingfeng Guo, Liya Wang, Chunying Zhang, and Bin Liu. "Research Progress of Complex Network Modeling Methods Based on Uncertainty Theory." Mathematics 11, no. 5 (March 1, 2023): 1212. http://dx.doi.org/10.3390/math11051212.

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A complex network in reality contains a large amount of information, but some information cannot be obtained accurately or is missing due to various reasons. An uncertain complex network is an effective mathematical model to deal with this problem, but its related research is still in its infancy. In order to facilitate the research into uncertainty theory in complex network modeling, this paper summarizes and analyzes the research hotspots of set pair analysis, rough set theory and fuzzy set theory in complex network modeling. This paper firstly introduces three kinds of uncertainty theories:

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22

REED, WILLIAM. "Information, Power, and War." American Political Science Review 97, no. 4 (November 2003): 633–41. http://dx.doi.org/10.1017/s0003055403000923.

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Ultimatum bargaining models of international interactions suggest that when conflict is costly and the actors are fully informed, the probability of conflict goes to zero. However, conflict occurs with some positive probability when the challenger is uncertain about the defender's reservation value. I employ a simple ultimatum game of bargaining to evaluate two traditional power-centric theories of world politics, balance of power, and power transition theory. The formal and empirical analyses demonstrate that as states approach power parity, information asymmetries are greatest, thus enhancin

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23

Beresford‐Smith, Bryan, and Colin J. Thompson. "An info‐gap approach to managing portfolios of assets with uncertain returns." Journal of Risk Finance 10, no. 3 (May 22, 2009): 277–87. http://dx.doi.org/10.1108/15265940910959393.

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PurposeThe purpose of this paper is to provide a quantitative methodology based on information‐gap decision theory for dealing with (true) Knightian uncertainty in the management of portfolios of assets with uncertain returns.Design/methodology/approachPortfolio managers aim to maximize returns for given levels of risk. Since future returns on assets are uncertain the expected return on a portfolio of assets can be subject to significant uncertainty. Information‐gap decision theory is used to construct portfolios that are robust against uncertainty.FindingsUsing the added dimensions of aspirat

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24

HAN, DEQIANG, CHONGZHAO HAN, and YONG DENG. "NOVEL APPROACHES FOR THE TRANSFORMATION OF FUZZY MEMBERSHIP FUNCTION INTO BASIC PROBABILITY ASSIGNMENT BASED ON UNCERTAINTY OPTIMIZATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21, no. 02 (April 2013): 289–322. http://dx.doi.org/10.1142/s0218488513500165.

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With the development of uncertainty reasoning and information fusion, there have emerged several theories including fuzzy set theory, Dempster-Shafer evidence theory, probability theory and rough set theory, etc., for representing and dealing with the uncertain information. When the fusion of the uncertain information originated from different sources is needed, how to construct a general framework for different theories of uncertainty or how to establish the connection between different theoretical frameworks has become a crucial problem. Particularly, to combine two kinds of information repr

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25

Li, Yuchen, and Zaoli Yang. "Games with incomplete information and uncertain payoff: from the perspective of uncertainty theory." Soft Computing 23, no. 24 (March 22, 2019): 13669–78. http://dx.doi.org/10.1007/s00500-019-03906-7.

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26

Cui, Yuquan, Xiaolin Zhang, and Xi Lu. "Supply Chain Commitment Contract Model Based on Uncertainty Theory under Uncertain Market Information." Applied Mathematics 06, no. 10 (2015): 1727–39. http://dx.doi.org/10.4236/am.2015.610153.

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27

Keyes, Laura M., and Abraham David Benavides. "Chaos theory, uncertainty, and organizational learning." International Journal of Organization Theory & Behavior 21, no. 4 (November 12, 2018): 226–41. http://dx.doi.org/10.1108/ijotb-04-2018-0050.

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Purpose The purpose of this paper is to juxtapose chaos theory with organizational learning theory to examine whether public organizations co-evolve into a new order or rather institutionalize newly gained knowledge in times of a highly complex public health crisis. Design/methodology/approach The research design utilizes the results from a survey administered to 200 emergency management and public health officials in the Dallas–Fort Worth metroplex. Findings The findings of this paper suggest that public entities were more likely to represent organizational learning through the coordination o

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Peng, Jin, Bo Zhang, and Kiki Ariyanti Sugeng. "Uncertain Hypergraphs: A Conceptual Framework and Some Topological Characteristics Indexes." Symmetry 14, no. 2 (February 5, 2022): 330. http://dx.doi.org/10.3390/sym14020330.

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In practical applications of hypergraph theory, we are usually surrounded by the state of indeterminacy. This paper employs uncertainty theory to address indeterministic information. We initially put forward the idea of an uncertain hypergraph by combining hypergraph theory with uncertainty theory in order to provide a useful tool to deal with a variety of uncertain complex systems and to create a new interdisciplinary research field. The main focus of this paper is to propose a conceptual framework of uncertain hypergraphs and to study the operations of uncertain hypergraphs. Moreover, some t

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29

OBLOW, E. M. "O-THEORY—A HYBRID UNCERTAINTY THEORY." International Journal of General Systems 13, no. 2 (January 1987): 95–106. http://dx.doi.org/10.1080/03081078708934960.

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30

Lin, Guoping, Jiye Liang, and Yuhua Qian. "Uncertainty Measures for Multigranulation Approximation Space." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 23, no. 03 (June 2015): 443–57. http://dx.doi.org/10.1142/s0218488515500191.

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Multigranulation rough set theory is a relatively new mathematical tool for solving complex problems in the multigranulation or distributed circumstances which are characterized by vagueness and uncertainty. In this paper, we first introduce the multigranulation approximation space. According to the idea of fusing uncertain, imprecise information, we then present three uncertainty measures: fusing information entropy, fusing rough entropy, and fusing knowledge granulation in the multigranulation approximation space. Furthermore, several essential properties (equivalence, maximum, minimum) are

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Jizba, Petr, Jacob A. Dunningham, and Jaewoo Joo. "Role of information theoretic uncertainty relations in quantum theory." Annals of Physics 355 (April 2015): 87–114. http://dx.doi.org/10.1016/j.aop.2015.01.031.

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32

Sun, Lin, and Jiucheng Xu. "Information Entropy and Mutual Information-based Uncertainty Measures in Rough Set Theory." Applied Mathematics & Information Sciences 8, no. 4 (July 1, 2014): 1973–85. http://dx.doi.org/10.12785/amis/080456.

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33

Weijs, S. V., G. Schoups, and N. van de Giesen. "Why hydrological forecasts should be evaluated using information theory." Hydrology and Earth System Sciences Discussions 7, no. 4 (July 16, 2010): 4657–85. http://dx.doi.org/10.5194/hessd-7-4657-2010.

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Abstract. Probabilistic forecasting is becoming increasingly popular in hydrology. Equally important are methods to evaluate such forecasts. There is still debate about which scores to use for this evaluation. In this paper we distinguish two scales for evaluation: information-uncertainty and utility-risk. We claim that the information-uncertainty scale is to be preferred for forecast evaluation. We propose a Kullback-Leibler divergence as the appropriate measure for forecast quality. Interpreting a decomposition of this measure into uncertainty, correct information and wrong information, it f

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34

Mobekk, Hilde, and Asle Fagerstrøm. "Escalation in Information Technology Projects." International Journal of Information Technology Project Management 6, no. 4 (October 2015): 1–19. http://dx.doi.org/10.4018/ijitpm.2015100101.

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According to the information systems literature, many information technology (IT) projects go wildly over budget, drag on long past their originally scheduled completion date, and do not deliver according to initial specification. Theories that have been used to understand the escalation phenomenon in general are the self-justification theory, the prospect theory, the agency theory, and the approach avoidance theory. These theories have contributed to a considerable insight in the phenomenon of escalation, but divergence among them indicates that there are still some unanswered questions. Disc

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35

Vigo, Ronaldo. "Complexity over Uncertainty in Generalized Representational Information Theory (GRIT): A Structure-Sensitive General Theory of Information." Information 4, no. 1 (December 20, 2012): 1–30. http://dx.doi.org/10.3390/info4010001.

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36

Mat Saad, Mohd Zuwairi, and Sharifah Nor Atiqah Syed Lokman Hakim. "The Preference of Social Networking Sites and Uncertainty Reduction Strategies Towards Information on COVID-19 Vaccination." Jurnal Komunikasi: Malaysian Journal of Communication 39, no. 3 (September 30, 2023): 501–14. http://dx.doi.org/10.17576/jkmjc-2023-3903-27.

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At the end of 2019, the world showcased a lethal outbreak of COVID-19, which was announced by the World Health Organization (WHO) as a pandemic in March 2020. As this outbreak has spread worldwide, including in Malaysia, several alternatives were undertaken by the government to curb this spread including introduce a vaccination program for the community. This program is believed to make most of the community worried or uncertain since it is still newly introduced. In reducing people's worries and uncertainties regarding COVID-19 vaccination, searching for information via social networking site

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37

Blevins, James. "The information-theoretic turn." Psihologija 46, no. 4 (2013): 355–75. http://dx.doi.org/10.2298/psi1304355b.

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Over the past decade, information theory has been applied to the analysis of a successively broader range of morphological phenomena. Interestingly, this tradition has arisen independently of the linguistic applications of information theory dating from the 1950?s. Instead, the point of origin for current work lies in a series of studies of morphological processing in which Kostic and associates develop a statistical notion of ?morphological information? based on ?uncertainty? and ?uncertainty reduction?. From these initial studies, analyses based on statistical notions of information have bee

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Wu, Lei, Yongchuan Tang, Liuyuan Zhang, and Yubo Huang. "Uncertainty Management in Assessment of FMEA Expert Based on Negation Information and Belief Entropy." Entropy 25, no. 5 (May 15, 2023): 800. http://dx.doi.org/10.3390/e25050800.

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The failure mode and effects analysis (FMEA) is a commonly adopted approach in engineering failure analysis, wherein the risk priority number (RPN) is utilized to rank failure modes. However, assessments made by FMEA experts are full of uncertainty. To deal with this issue, we propose a new uncertainty management approach for the assessments given by experts based on negation information and belief entropy in the Dempster–Shafer evidence theory framework. First, the assessments of FMEA experts are modeled as basic probability assignments (BPA) in evidence theory. Next, the negation of BPA is c

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Slayton, Rebecca. "Governing Uncertainty or Uncertain Governance? Information Security and the Challenge of Cutting Ties." Science, Technology, & Human Values 46, no. 1 (January 29, 2020): 81–111. http://dx.doi.org/10.1177/0162243919901159.

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Information security governance has become an elusive goal and a murky concept. This paper problematizes both information security governance and the broader concept of governance. What does it mean to govern information security, or for that matter, anything? Why have information technologies proven difficult to govern? And what assurances can governance provide for the billions of people who rely on information technologies every day? Drawing together several distinct bodies of literature—including multiple strands of governance theory, actor–network theory, and scholarship on sociotechnical

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Hall, Jim W. "Handling uncertainty in the hydroinformatic process." Journal of Hydroinformatics 5, no. 4 (October 1, 2003): 215–32. http://dx.doi.org/10.2166/hydro.2003.0019.

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Hydroinformatics combines topics of modelling and decision-making, both of which have attracted a great deal of attention outside hydroinformatics from the point of view of uncertainty. Epistemic uncertainties are due to the inevitably incomplete evidence about the dependability of a model or set of competing models. Inherent uncertainties are due to the varying information content inherent in measurements or model predictions, be they probabilistic or fuzzy. Decision-making in management of the aquatic environment is, more often than not, a complex, discursive, multi-player process. The requi

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Ver Steeg, G., and S. Wehner. "Relaxed uncertainty relations and information processing." Quantum Information and Computation 9, no. 9&10 (September 2009): 801–32. http://dx.doi.org/10.26421/qic9.9-10-6.

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We consider a range of "theories'' that violate the uncertainty relation for anti-commuting observables derived. We first show that Tsirelson's bound for the CHSH inequality can be derived from this uncertainty relation, and that relaxing this relation allows for non-local correlations that are stronger than what can be obtained in quantum mechanics. We continue to construct a hierarchy of related non-signaling theories, and show that on one hand they admit superstrong random access encodings and exponential savings for a particular communication problem, while on the other hand it becomes muc

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CAO, TRU H., and HOA NGUYEN. "UNCERTAIN AND FUZZY OBJECT BASES: A DATA MODEL AND ALGEBRAIC OPERATIONS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 19, no. 02 (April 2011): 275–305. http://dx.doi.org/10.1142/s0218488511007003.

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Fuzzy set theory and probability theory are complementary for soft computing, in particular object-oriented systems with imprecise and uncertain object properties. However, current fuzzy object-oriented data models are mainly based on fuzzy set theory or possibility theory, and lack of a rigorous algebra for querying and managing uncertain and fuzzy object bases. In this paper, we develop an object base model that incorporates both fuzzy set values and probability degrees to handle imprecision and uncertainty. A probabilistic interpretation of relations on fuzzy sets is introduced as a formal

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Wu, Haotian, Guo Dong Bai, Shuo Liu, Lianlin Li, Xiang Wan, Qiang Cheng, and Tie Jun Cui. "Information theory of metasurfaces." National Science Review 7, no. 3 (November 27, 2019): 561–71. http://dx.doi.org/10.1093/nsr/nwz195.

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Abstract We propose a theory to characterize the information and information processing abilities of metasurfaces, and demonstrate the relation between the information of the metasurface and its radiation pattern in the far-field region. By incorporating a general aperture model with uncertainty relation in L2-space, we propose a theory to predict the upper bound of information contained in the radiation pattern of a metasurface, and reveal the theoretical upper limit of orthogonal radiation states. The proposed theory also provides guidance for inverse design of the metasurface with respect t

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Ziyang Chen, Ziyang Chen, and Yang Zhang Ziyang Chen. "Conflict Evidence Fusion Algorithm Based on Cosine Distance and Information Entropy." 電腦學刊 34, no. 3 (June 2023): 343–55. http://dx.doi.org/10.53106/199115992023063403026.

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<p>Dealing with high conflict evidence, traditional evidence theory sometimes has certain limitations, and results in fusion results contrary to common sense. In order to solve the problem of high conflict evidence fusion, this paper analyzes traditional evidence theory and proposes an evidence fusion method that combines cosine distance and information entropy. Cosine distance can measure the directionality between two vectors. The better the directionality, the more similar the two vectors are. Therefore, this article uses cosine distance to determine the similarity between evidences,

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Yang, Yuhong. "Elements of Information Theory." Journal of the American Statistical Association 103, no. 481 (March 1, 2008): 429. http://dx.doi.org/10.1198/jasa.2008.s218.

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Chen, Yutong, and Yongchuan Tang. "Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion." Entropy 23, no. 4 (March 28, 2021): 402. http://dx.doi.org/10.3390/e23040402.

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Dempster-Shafer (DS) evidence theory is widely used in various fields of uncertain information processing, but it may produce counterintuitive results when dealing with conflicting data. Therefore, this paper proposes a new data fusion method which combines the Deng entropy and the negation of basic probability assignment (BPA). In this method, the uncertain degree in the original BPA and the negation of BPA are considered simultaneously. The degree of uncertainty of BPA and negation of BPA is measured by the Deng entropy, and the two uncertain measurement results are integrated as the final u

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Wang, Jinjing (Jenny), Yang Yang, Carla Macias, and Elizabeth Bonawitz. "Children With More Uncertainty in Their Intuitive Theories Seek Domain-Relevant Information." Psychological Science 32, no. 7 (June 28, 2021): 1147–56. http://dx.doi.org/10.1177/0956797621994230.

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How do changes in learners’ knowledge influence information seeking? We showed preschoolers ( N = 100) uncertain outcomes for events and let them choose which event to resolve. We found that children whose intuitive theories were at immature stages were more likely to seek information to resolve uncertainty about an outcome in the related domains, but children with more mature knowledge were not. This result was replicated in a second experiment but with the nuance that children at intermediate stages of belief development—when the causal outcome would be most ambiguous—were the most motivated

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Crump, Matthew J. C., Walter Lai, and Nicholaus P. Brosowsky. "Instance theory predicts information theory: Episodic uncertainty as a determinant of keystroke dynamics." Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale 73, no. 4 (December 2019): 203–15. http://dx.doi.org/10.1037/cep0000182.

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Weijs, S. V., G. Schoups, and N. van de Giesen. "Why hydrological predictions should be evaluated using information theory." Hydrology and Earth System Sciences 14, no. 12 (December 13, 2010): 2545–58. http://dx.doi.org/10.5194/hess-14-2545-2010.

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Abstract. Probabilistic predictions are becoming increasingly popular in hydrology. Equally important are methods to test such predictions, given the topical debate on uncertainty analysis in hydrology. Also in the special case of hydrological forecasting, there is still discussion about which scores to use for their evaluation. In this paper, we propose to use information theory as the central framework to evaluate predictions. From this perspective, we hope to shed some light on what verification scores measure and should measure. We start from the ''divergence score'', a relative entropy me

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Li, Ming, and Kefeng Liu. "Probabilistic Prediction of Significant Wave Height Using Dynamic Bayesian Network and Information Flow." Water 12, no. 8 (July 22, 2020): 2075. http://dx.doi.org/10.3390/w12082075.

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Short-term prediction of wave height is paramount in oceanic operation-related activities. Statistical models have advantages in short-term wave prediction as complex physical process is substantially simplified. However, previous statistical models have no consideration in selection of predictive variables and dealing with prediction uncertainty. This paper develops a machine learning model by combining the dynamic Bayesian network (DBN) with the information flow (IF) designated as DBN-IF. IF is focused on selecting the best predictive variables for DBN by causal analysis instead of correlati

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