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Data mining and knowledge discovery via statistical mechanics in nonlinear stochastic systems

Ingber, L.

Mathematical and computer modelling, 1998-02, Vol.27 (3), p.9-31 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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Título:
Data mining and knowledge discovery via statistical mechanics in nonlinear stochastic systems
Autor: Ingber, L.
Assuntos: Combat analysis ; Electroencephalography ; Exact sciences and technology ; Financial markets ; Mathematical methods in physics ; Mathematics ; Path integration ; Physics ; Probability and statistics ; Probability theory and stochastic processes ; Probability theory, stochastic processes, and statistics ; Sciences and techniques of general use ; Simulated annealing ; Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications) ; Stochastic analysis
É parte de: Mathematical and computer modelling, 1998-02, Vol.27 (3), p.9-31
Descrição: A modern calculus of multivariate nonlinear multiplicative Gaussian-Markovian systems provides models of many complex systems faithful to their nature, e.g., by not prematurely applying quasi-linear approximations for the sole purpose of easing analysis. To handle these complex algebraic constructs, sophisticated numerical tools have been developed, e.g., methods of adaptive simulated annealing (ASA) global optimization and of path integration (PATHINT). In-depth application to three quite different complex systems have yielded some insights into the benefits to be obtained by application of these algorithms and tools, in statistical mechanical descriptions of neocortex (short-term memory and electroencephalography), financial markets (interest-rate and trading models), and combat analysis (baselining simulations to exercise data).
Editor: Oxford: Elsevier Ltd
Idioma: Inglês

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Data mining and knowledge discovery via statistical mechanics in nonlinear stochastic systems

Ingber, L.

Oxford: Elsevier Ltd

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