186 research outputs found

    Advances and Applications of Dezert-Smarandache Theory (DSmT) for Information Fusion (Collected works), Vol. 2

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    This second volume dedicated to Dezert-Smarandache Theory (DSmT) in Information Fusion brings in new fusion quantitative rules (such as the PCR1-6, where PCR5 for two sources does the most mathematically exact redistribution of conflicting masses to the non-empty sets in the fusion literature), qualitative fusion rules, and the Belief Conditioning Rule (BCR) which is different from the classical conditioning rule used by the fusion community working with the Mathematical Theory of Evidence. Other fusion rules are constructed based on T-norm and T-conorm (hence using fuzzy logic and fuzzy set in information fusion), or more general fusion rules based on N-norm and N-conorm (hence using neutrosophic logic and neutrosophic set in information fusion), and an attempt to unify the fusion rules and fusion theories. The known fusion rules are extended from the power set to the hyper-power set and comparison between rules are made on many examples. One defines the degree of intersection of two sets, degree of union of two sets, and degree of inclusion of two sets which all help in improving the all existing fusion rules as well as the credibility, plausibility, and communality functions. The book chapters are written by Frederic Dambreville, Milan Daniel, Jean Dezert, Pascal Djiknavorian, Dominic Grenier, Xinhan Huang, Pavlina Dimitrova Konstantinova, Xinde Li, Arnaud Martin, Christophe Osswald, Andrew Schumann, Tzvetan Atanasov Semerdjiev, Florentin Smarandache, Albena Tchamova, and Min Wang

    Advances and Applications of DSmT for Information Fusion

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    This book is devoted to an emerging branch of Information Fusion based on new approach for modelling the fusion problematic when the information provided by the sources is both uncertain and (highly) conflicting. This approach, known in literature as DSmT (standing for Dezert-Smarandache Theory), proposes new useful rules of combinations

    Advances and Applications of Dezert-Smarandache Theory (DSmT), Vol. 1

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    The Dezert-Smarandache Theory (DSmT) of plausible and paradoxical reasoning is a natural extension of the classical Dempster-Shafer Theory (DST) but includes fundamental differences with the DST. DSmT allows to formally combine any types of independent sources of information represented in term of belief functions, but is mainly focused on the fusion of uncertain, highly conflicting and imprecise quantitative or qualitative sources of evidence. DSmT is able to solve complex, static or dynamic fusion problems beyond the limits of the DST framework, especially when conflicts between sources become large and when the refinement of the frame of the problem under consideration becomes inaccessible because of vague, relative and imprecise nature of elements of it. DSmT is used in cybernetics, robotics, medicine, military, and other engineering applications where the fusion of sensors\u27 information is required

    Dependently Sorted Theorem Proving for Mathematical Foundations

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    Essays on Portfolio Risk Management and Weather Derivatives

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    Denne avhandlingen handler om utvikling og praktisk implementering av risikostyringsmetoder for investeringsporteføljer, energiporteføljer, og håndtering av vær- og forurensningsrisiko. Avhandlingen inkluderer tre vitenskapelige artikler som hver tar for seg ulike aspekter av finansiell risikostyring. Den første fokuserer på metoder for aktivaallokering når det eksisterer asymmetrisk avhengighet mellom avkastningene for eiendelene i en investeringsportefølje. Den andre artikkelen omhandler energiprisrisikostyring, og introduserer et åpen kildekodeverktøy for energiporteføljeforvaltning som er utviklet som en del av doktorgradsprosjektet. Den siste artikkelen presenterer et teoretisk rammeverk for håndtering av forurensningsrisiko ved hjelp av finansielle derivatkontrakter, som bygger på den eksisterende teorien om værderivater. Disse arbeidene bidrar alle til det overordnede temaet for avhandlingen, som er utvikling av risikostyringsmetoder for ulike typer porteføljer og utforskingen av rollen til finansielle derivater i håndtering av risiko knyttet til markedspriser, vær og forurensning. For å sette bidragene inn i en teoretisk kontekst har vi inkludert et kort kapittel som presenterer alternative metoder for avhengighetsmodellering, og hvordan disse kan utnyttes når man forvalter investeringsporteføljer. Ett av disse målene, lokal gaussisk korrelasjon, brukes til å utvide det klassiske mean-variance-rammeverket for aktivaallokering i den første artikkelen. Deretter følger et kort introduksjonskapittel til spot- og forwardmarkeder for energi. Hovedfokuset her er råvareprisrisiko, og hvordan denne kan håndteres med finansielle derivatkontrakter. Vi demonstrerer hvordan forvaltning av energiporteføljer kan gjennomføres med vårt åpen kildekodeverktøy ved bruk av data fra det europeiske kraftmarkedet. Til slutt inkluderes et kapittel om værderivater. Dette inneholder en introduksjon til værrelatert risiko, en kort introduksjon til værmarkedet, vanlige kontraktstyper og alternative metoder for prising. For å sikre reproduserbarhet har vi også lagt til et kapittel om programkode. Her finnes lenker til Git-repositorier med alle data og R-kode for å gjennomføre analysene som presenteres i avhandlingen.This thesis is concerned with the development and practical implementation of risk management methods for investment portfolios, energy portfolios, and weather and pollution risk. The thesis includes three scientific papers that each address different aspects of financial risk management. The first paper focuses on portfolio allocation in the presence of asymmetric dependence between asset returns. The second paper examines energy price risk management, and introduces an open source toolkit for energy portfolio management which has been developed as a part of the PhD project. The final paper present a theoretical framework for managing pollution risk using financial derivatives contracts, which builds upon the existing theory of weather derivatives. These papers all contribute to the overall theme, which is the development of risk management methods for various types of portfolios and the exploration of the role of financial derivatives in managing risks related to market prices, weather and pollution. In order to provide a theoretical context, we have included a brief chapter exploring alternative methods for dependence modelling and how these may be utilized when managing investment portfolios. One of these measures, the local Gaussian correlation, is used to extend the classical mean-variance framework for asset allocation in the first paper. Thereafter, a short introduction to spot and forward energy markets is provided. The primary focus here is commodity market price risk, and how this can be managed with financial derivatives contracts. We demonstrate how portfolio management may be performed with our open source toolkit using European energy market data. Finally, we include a chapter on weather derivatives. This contains a introduction to weather related risk, a brief introduction to the weather markets, frequently used contract types and pricing methods. To ensure reproducibility, we have also added a chapter on computer code, where the interested reader may find links to Git repositories with all data and the R code needed to run the analysis presented in the thesis.Doktorgradsavhandlin

    Algorithmic Processes And Social Values

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    In this thesis, we study several problems at the interface of algorithmic decision-making and society, focusing on the tensions that arise between these processes and social values like fairness and privacy. In the first chapter, we examine the design of financial portfolios which adequately serve all segments of the population. In the second, we examine an allocation setting where the allocator wishes to distribute a scarce resource across many groups fairly, but does not know ahead of time which groups have a need for the resource. In the third, we study a game-theoretic model of information aggregation and the effects of individuals acting to preserve the privacy of their personal beliefs on the collective welfare of the population. Finally, we look at some of the issues that arise from the desire to apply automated techniques to problems in redistricting, including fundamental flaws in the definitions and frameworks typically used
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