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- W41019358 abstract "Research focussed on the relatively new and little explored concept of interval-valued or upper and lower probability (U/LP). The axiomatic structure of U/LP is presented in Section 3 below, but roughly we may think of it as a pair of nonnegative numbers in the unit interval that simultaneously represent the tendency for an event in question (interval midpoint, say) to occur and our lack of knowledge concerning this tendency (interval width). We have contributed to the development of the theory associated with U/LP in such areas as the generation of useful and tractable specific models (e.g., analogues to specific probability models like the Gaussian), the calculus of the random quantities described by U/LP (e.g., sums of random variables), and attempted to develop better definitions of independence and conditioning (learning from experience). We have applied the concept of U/LP to the problem of aggregating group/expert opinion so as to better represent the state of knowledge of an electric utility planning group doing long range planning and forecasting. We believe that our research has been successful in this area in that we can formally represent both consensus and disagreement in the opinions of a group of experts whereas the approaches based uponmore » the conventional notion of numerical probability can not display disagreement. Work can be the basis of a distinct improvement in the utilization of expert opinion, and the use of expert opinion is unavoidable in planning and forecasting. We have studied in some detail the possibilities for new time series models better able to model sporadically fluctuating processes having long-term dependencies. We anticipate that several of the economic time series of interest to a utility might be of this nature and we may eventually be better able to model them than is currently possible with econometric models.« less" @default.
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- W41019358 date "1985-08-01" @default.
- W41019358 modified "2023-09-27" @default.
- W41019358 title "Research on uncertainty for industry functional modeling" @default.
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