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Uncertainty theory[electronic resour...
~
Liu, Baoding.
Uncertainty theory[electronic resource] /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
杜威分類號:
003.54
書名/作者:
Uncertainty theory/ by Baoding Liu.
作者:
Liu, Baoding.
出版者:
Berlin, Heidelberg : : Springer Berlin Heidelberg :, 2015.
面頁冊數:
xvii, 487 p. : : ill., digital ;; 24 cm.
Contained By:
Springer eBooks
標題:
Uncertainty (Information theory)
標題:
Fuzzy statistics.
標題:
Probabilities.
標題:
Engineering.
標題:
Computational Intelligence.
標題:
Probability Theory and Stochastic Processes.
標題:
Probability and Statistics in Computer Science.
標題:
Operation Research/Decision Theory.
ISBN:
9783662443545 (electronic bk.)
ISBN:
9783662443538 (paper)
內容註:
Uncertain measure -- Uncertain variable -- Uncertain Programming -- Uncertain Statistics -- Uncertain Risk Analysis -- Uncertain Reliability Analysis -- Uncertain Logic -- Uncertain Entailment -- Uncertain Set -- Uncertain Inference -- Uncertain Process -- Uncertain Renewal Process -- Uncertain Calculus -- Uncertain Differential Equation -- Uncertain Finance.
摘要、提要註:
When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, control, and finance.
電子資源:
http://dx.doi.org/10.1007/978-3-662-44354-5
Uncertainty theory[electronic resource] /
Liu, Baoding.
Uncertainty theory
[electronic resource] /by Baoding Liu. - 4th ed. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xvii, 487 p. :ill., digital ;24 cm. - Springer uncertainty research,2199-3807. - Springer uncertainty research..
Uncertain measure -- Uncertain variable -- Uncertain Programming -- Uncertain Statistics -- Uncertain Risk Analysis -- Uncertain Reliability Analysis -- Uncertain Logic -- Uncertain Entailment -- Uncertain Set -- Uncertain Inference -- Uncertain Process -- Uncertain Renewal Process -- Uncertain Calculus -- Uncertain Differential Equation -- Uncertain Finance.
When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, control, and finance.
ISBN: 9783662443545 (electronic bk.)
Standard No.: 10.1007/978-3-662-44354-5doiSubjects--Topical Terms:
369777
Uncertainty (Information theory)
LC Class. No.: Q375
Dewey Class. No.: 003.54
Uncertainty theory[electronic resource] /
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When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, control, and finance.
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