1,721,060 research outputs found
Simulated annealing: Practice versus theory
No full textSimulated annealing (SA) presents an optimization technique with several striking positive and negative features. Perhaps its most salient feature, statistically promising to deliver anoptimal solution, in current practice is often spurned to use instead modified faster algorithms, “simulated quenching ” (SQ). Using the author’s Adaptive Simulated Annealing (ASA) code, some examples are given which demonstrate how SQcan be much faster than SA without sacrificing accuracy. Ke ywords: Simulated annealing, random algorithm, optimization technique SA Practice vs Theory-2- Lester Ingber 1
Statistical Mechanical Aids to Calculating Term Structure Models
No full textThis paper describes application of the very fast simulated reannealing and path-integral methodologies to the estimation of the Brennan and Schwartz two-factor term-structure (time-dependent) model of bond prices. It is shown that these methodologies can be utilized to estimate more complicated n-factor nonlinear models. Applications to other systems are stressed. Statistical mechanical aids-2- Lester Ingber 1. INTRODUCTIO
Statistical mechanics of neocortical interactions (SMNI): Testing theories with multiple imaging data
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Statistical mechanics of neocortical interactions: Portfolio of physiological indicators
Full text linkModelling multi-scale microstructures with combined Boolean random sets: A practical contribution
Full text linkBoolean random sets are versatile tools to match morphological and topological properties of real structures of materials and particulate systems. Moreover, they can be combined in any number of ways to produce an even wider range of structures that cover a range of scales of microstructures through intersection and union. Based on well-established theory of Boolean random sets, this work provides scientists and engineers with simple and readily applicable results for matching combinations of Boolean random sets to observed microstructures. Once calibrated, such models yield straightforward three-dimensional simulation of materials, a powerful aid for investigating microstructure property relationships. Application of the proposed results to a real case situation yield convincing realisations of the observed microstructure in two and three dimensions
Adaptive Simulated Annealing (ASA): Lessons Learned
No full textAdaptive simulated annealing (ASA) is a global optimization algorithm based on an associated proof that the parameter space can be sampled much more efficiently than by using other previous simulated annealing algorithms. The author's ASA code has been publicly available for over two years. During this time the author has volunteered to help people via e-mail, and the feedback obtained has been used to further develop the code. Some lesson
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