scholarly journals A QUANTUM INSPIRED MADM METHOD AND THE APPLICATION IN E-COMMERCE RECOMMENDATION

2018 ◽  
Vol 24 (5) ◽  
pp. 1941-1954
Author(s):  
Shuli Liu
Keyword(s):  
Quantum Theory ◽  
Decision Process ◽  
Quantum Probability ◽  
Final Decision ◽  
Probability System

In this paper, a quantum inspired MADM method is proposed. Inspired by quantum theory, the decision process is considered as a quantum probability system. Before the decision is made, the preference state is considered as the superposition from the sub-states with respect to various attributes. Each sub-state is regarded as the entanglement from the alternatives. Once the final decision is made, the preference state collapses into a definite state corresponding to an alternative. Based on the proposed method, the decision steps are provided. Ultimately, the feasibility is illustrated through an application in E-commerce recommendation.

scholarly journals PREVISIONI INCERTE DECISIONI DIFFICILI

2015 ◽  
Author(s):  
Elisa Guagenti Grandori
Keyword(s):  
Risk Reduction ◽  
Case Studies ◽  
Decision Process ◽  
Decision Problems ◽  
Final Decision ◽  
Acceptable Risk ◽  
Short Term ◽  
Catastrophic Events ◽  
Competing Models ◽  
Short Term Prediction

This work focuses on decision problems concerning risk reduction in the case of catastrophic events, which are scarsely predictable but associated to severe expected damage. A cryterium is outlined in order to judge the relative credibility of competing models. The knowledge-decision process is dissected in its components. The steps of the procedure from knowledge to final decision are analyzed. The effectiveness of short-term prediction and the choice of the acceptable risk are also discussed. A few case studies, related to earthquakes, landslides and pollution, are exposed.

scholarly journals Early Fusion of Low Level Features for Emotion Mining

2012 ◽  
Vol 5s1 ◽  
pp. BII.S8973 ◽  
Author(s):  
Fabon Dzogang ◽  
Marie-Jeanne Lesot ◽  
Maria Rifqi ◽  
Bernadette Bouchon-Meunier
Keyword(s):  
Decision Process ◽  
Opinion Mining ◽  
Entropy Measure ◽  
Final Decision ◽  
Low Level ◽  
Shannon's Entropy ◽  
Early Fusion ◽  
Sentence Level ◽  
Emotion Mining ◽  
Testing Set

We study the discrimination of emotions annotated in free texts at the sentence level: a sentence can either be associated with no emotion (neutral) or multiple labels of emotion. The proposed system relies on three characteristics. We implement an early fusion of grams of increasing orders transposing an approach successfully employed in the related task of opinion mining. We apply a filtering process that consists in extracting frequent n-grams and making use of the Shannon's entropy measure to respectively maintain dictionaries at balanced sizes and keep emotion specific features. Finally the overall system is implemented as a 2-step decision process: a first classifier discriminates between neutral and emotion bearing sentences, then one classifier per emotion is applied on emotion bearing sentences. The final decision is given by the classifier holding the maximum confidence. Results obtained on the testing set are promising.

scholarly journals Quantum Bayesian perspective for intelligence reservoir characterization, monitoring and management

2017 ◽  
Vol 375 (2106) ◽  
pp. 20160398 ◽  
Author(s):  
Miguel Ángel Lozada Aguilar ◽  
Andrei Khrennikov ◽  
Klaudia Oleschko ◽  
María de Jesús Correa
Keyword(s):  
Decision Making ◽  
Quantum Theory ◽  
Reservoir Characterization ◽  
Quantum Probability ◽  
Geophysical Data ◽  
Interpretation Of Quantum Mechanics ◽  
Review Of The Literature ◽  
Classical Probability ◽  
Hydrocarbon Reservoir ◽  
Quantum Revolution

The paper starts with a brief review of the literature about uncertainty in geological, geophysical and petrophysical data. In particular, we present the viewpoints of experts in geophysics on the application of Bayesian inference and subjective probability. Then we present arguments that the use of classical probability theory (CP) does not match completely the structure of geophysical data. We emphasize that such data are characterized by contextuality and non-Kolmogorovness (the impossibility to use the CP model), incompleteness as well as incompatibility of some geophysical measurements. These characteristics of geophysical data are similar to the characteristics of quantum physical data. Notwithstanding all this, contextuality can be seen as a major deviation of quantum theory from classical physics. In particular, the contextual probability viewpoint is the essence of the Växjö interpretation of quantum mechanics. We propose to use quantum probability (QP) for decision-making during the characterization, modelling, exploring and management of the intelligent hydrocarbon reservoir . Quantum Bayesianism (QBism), one of the recently developed information interpretations of quantum theory, can be used as the interpretational basis for such QP decision-making in geology, geophysics and petroleum projects design and management. This article is part of the themed issue ‘Second quantum revolution: foundational questions’.

scholarly journals A hierarchical decomposition of decision process Petri nets for modeling complex systems

2010 ◽  
Vol 20 (2) ◽  
pp. 349-366 ◽  
Author(s):  
Julio Clempner
Keyword(s):  
Complex Systems ◽  
Petri Nets ◽  
Decision Process ◽  
Dynamic Properties ◽  
Decomposition Process ◽  
Final Decision ◽  
Hierarchical Decomposition ◽  
Decision Points ◽  
Hierarchical Decision ◽  
Global Equilibrium

A hierarchical decomposition of decision process Petri nets for modeling complex systemsWe provide a framework for hierarchical specification called Hierarchical Decision Process Petri Nets (HDPPNs). It is an extension of Decision Process Petri Nets (DPPNs) including a hierarchical decomposition process that generates less complex nets with equivalent behavior. As a result, the complexity of the analysis for a sophisticated system is drastically reduced. In the HDPPN, we represent the mark-dynamic and trajectory-dynamic properties of a DPPN. Within the framework of the mark-dynamic properties, we show that the HDPPN theoretic notions of (local and global) equilibrium and stability are those of the DPPN. As a result in the trajectory-dynamic properties framework, we obtain equivalent characterizations of that of the DPPN for final decision points and stability. We show that the HDPPN mark-dynamic and trajectory-dynamic properties of equilibrium, stability and final decision points coincide under some restrictions. We propose an algorithm for optimum hierarchical trajectory planning. The hierarchical decomposition process is presented under a formal treatment and is illustrated with application examples.

scholarly journals Socio-Economic Sciences: Beyond Quantum Math-like Formalisms

2021 ◽  
Vol 3 (4) ◽  
pp. 656-663
Author(s):  
Vikram Athalye ◽  
Emmanuel Haven
Keyword(s):  
Decision Making ◽  
Quantum Theory ◽  
21St Century ◽  
Interdisciplinary Research ◽  
Decision Process ◽  
Human Behaviour ◽  
Foundations Of Quantum Theory ◽  
Economic Decision ◽  
Modelling Approach

Since the beginning of the 21st century, a new interdisciplinary research movement has started, which aims at developing quantum math-like (or simply quantum-like) models to provide an explanation for a variety of socio-economic processes and human behaviour. By making use of mainly the probabilistic aspects of quantum theory, this research movement has led to many important results in the areas of decision-making and finance. In this article, we introduce a novel and more exhaustive approach, to analyze the socio-economic processes and activities, than the pure quantum math-like modelling approach, by taking into account the physical foundations of quantum theory. We also provide a plausibility argument for its exhaustiveness in terms of what we can expect from such an approach, when it is applied to, for example, a generic socio-economic decision process.

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