the mathematical modeling of fracture networks is critical for the exploration and development ofnatural resources. fractures can help the production of petroleum, water, and geothermal energy. theyalso greatly influence the drainage and production of methane gas from coal beds. orientation andspatial distribution of fractures in rocks are important factors in controlling fluid flow. the object...

Accurate determination of the input function is essential for absolute quantification of physiological parameters in PET and SPECT imaging but it requires an invasive and tedious procedure of blood sampling that is impractical in clinical studies. We previously proposed a technique that simultaneously estimates kinetic parameters and the input function from the tissue impulse response functions...

Simulated Annealing is a family of randomized algorithms used to solve many combinatorial optimization problems. In practice they have been applied to solve some presumably hard (e.g., NP-complete) problems. The level of performance obtained has been promising [5, 2, 6, 14]. The success of this heuristic technique has motivated analysis of this algorithm from a theoretical point of view. In par...

We study errors of quantum annealing and simulated annealing to highlight better performance of quantum annealing over simulated annealing. Quantum annealing and simulated annealing perform optimization through a quantum adiabatic evolution and a quasi-static evolution respectively. In both methods, dynamics across a phase transition plays a crucial role. The Kibble-Zurek mechanism is known as ...

Category decomposition method for un-mixing of mixels (Mixed Pixels) which is acquired with spaceborne based visible to near infrared radiometers by means of Maximum Entropy Method (MEM) with parameter estimation based on Simulated Annealing: SA is proposed. Through simulation studies with spectral characteristics of the ground cover targets which are derived from spectral library and actual re...

Method for noise suppressing edge enhancement based on genetic algorithm taking into account complexity of target images measured with fractal dimension is proposed. Through experiments with satellite remote sensing imagery data with additive noise, it is found that the proposed method shows appropriate edge enhancing performance with suppressing the additive noise in accordance with complexity...

In this paper the problem of minimum cost communication network design is considered where the costs are piecewise linear concave. Several methods are compared: Simulated Annealing method, a heuristic based on the method proposed by Minoux, and a lagrangian method based on lower bounding procedure.

the markowitz issue of optimization can’t be solved by precise mathematical methods such as second order schematization, when real world condition and limitations are considered. on the other hand, most managers prefer to manage a small portfolio of available assets in place of a huge portfolio. it can be analogized to cardinal constrains, that is, constrains related to minimum and maximum curr...

This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of variables is very large, which makes well-known classification techniques impractical. The number of variables might be reduced via principal component analysis or some robust analog, but these methods are usually unsat...

The purpose of this paper is to improve the simulated annealing method with a variable neighborhood search to solve the resource-constrained scheduling problem. We also compare numerically this method with other neighborhood search (local search) techniques: threshold accepting methods and tabu search. Furthermore, we combine these techniques with multistart diversification strategies and with ...