7,934 research outputs found
Intertemporal Choice of Fuzzy Soft Sets
This paper first merges two noteworthy aspects of choice. On the one hand, soft sets and fuzzy soft sets are popular models that have been largely applied to decision making problems, such as real estate valuation, medical diagnosis (glaucoma, prostate cancer, etc.), data mining, or international trade. They provide crisp or fuzzy parameterized descriptions of the universe of alternatives. On the other hand, in many decisions, costs and benefits occur at different points in time. This brings about intertemporal choices, which may involve an indefinitely large number of periods. However, the literature does not provide a model, let alone a solution, to the intertemporal problem when the alternatives are described by (fuzzy) parameterizations. In this paper, we propose a novel soft set inspired model that applies to the intertemporal framework, hence it fills an important gap in the development of fuzzy soft set theory. An algorithm allows the selection of the optimal option in intertemporal choice problems with an infinite time horizon. We illustrate its application with a numerical example involving alternative portfolios of projects that a public administration may undertake. This allows us to establish a pioneering intertemporal model of choice in the framework of extended fuzzy set theorie
Soft computing techniques applied to finance
Soft computing is progressively gaining presence in the financial world. The number of real and potential applications is very large and, accordingly, so is the presence of applied research papers in the literature. The aim of this paper is both to present relevant application areas, and to serve as an introduction to the subject. This paper provides arguments that justify the growing interest in these techniques among the financial community and introduces domains of application such as stock and currency market prediction, trading, portfolio management, credit scoring or financial distress prediction areas.Publicad
Fuzzy Topology, Quantization and Gauge Invariance
Dodson-Zeeman fuzzy topology considered as the possible mathematical
framework of quantum geometric formalism. In such formalism the states of
massive particle m correspond to elements of fuzzy manifold called fuzzy
points. Due to their weak (partial) ordering, m space coordinate x acquires
principal uncertainty dx. It's shown that m evolution with minimal number of
additional assumptions obeys to schroedinger and dirac formalisms in
norelativistic and relativistic cases correspondingly. It's argued that
particle's interactions on such fuzzy manifold should be gauge invariant.Comment: 12 pages, Talk given on 'Geometry and Field Theory' conference,
Porto, July 2012. To be published in Int. J. Theor. Phys. (2015
On Vague Computers
Vagueness is something everyone is familiar with. In fact, most people think
that vagueness is closely related to language and exists only there. However,
vagueness is a property of the physical world. Quantum computers harness
superposition and entanglement to perform their computational tasks. Both
superposition and entanglement are vague processes. Thus quantum computers,
which process exact data without "exploiting" vagueness, are actually vague
computers
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