Due to the limitation of the local spatial information in an image, fuzzy c-means clustering algorithms with the local spatial information cannot obtain the satisfying segmentation performance on the image heavily contaminated by noise. In order to compensate this drawback of the local spatial information, an effective kind of non-local spatial information is extracted from the image in this pa...

bamdezh wetland with the geographical coordinates of   north longitude, east latitude and an area of 44 square kilometers, is located in about 40 km northwest of ahvaz and shavur river is the main source of its supply. this wetland is not only a habitat and suitable food source for aquatic and migratory birds, but as well a significant resource of income for the locals. today, with the arrival ...

concentrations of heavy metals (ni, co, zn, cd, pb and cu) in the reservoir of shahid rajaeidam, one of the main water reservoirs in north part of iran, were determined using a differential pulse polarography(metrohm 797 va) and compared with the national and international specified maximum contaminant levels(mcl) for different purposes of water use. the results showed that concentrations of cd...

One of the main distinctions between geomaterials and other engineering materials is the spatial variation of their properties in different directions. This characteristic of geomaterials -so called heterogeneity- is studied herewith. Several spatial distributions are introduced to describe probabilistic variation of geotechnical properties of soils. Among all, the absolute normal distribution ...

This paper proposes a new crossover method for parallel distributed genetic algorithms (PDGAs). PDGAs with multiple subpopulations provide better solutions than conventional GAs with a single population. The proposed method, including the hybridization crossover and the best combinatorial crossover, is designed to increase the performance of PDGAs. The proposed method, which provides high local...

Multi-mode resource-constrained project scheduling problems (MRCPSPs) are classified as NP-hard problems, in which a task has different execution modes characterized by different resource requirements. Estimation of distribution algorithm (EDA) has shown an effective performance for solving such real-world optimization problems but it fails to find the desired optima. This paper integrates a no...

This paper presents a parallel genetic simulated annealing (PGSA) algorithm that has been developed and applied to optimize continuous problems. In PGSA, the entire population is divided into subpopulations, and in each subpopulation the algorithm uses the local search ability of simulated annealing after crossover and mutation. The best individuals of each subpopulation are migrated to neighbo...

The UMDA algorithm is a type of Estimation of Distribution Algorithms. This algorithm has better performance compared to others such as genetic algorithm in terms of speed, memory consumption and accuracy of solutions. It can explore unknown parts of search space well. It uses a probability vector and individuals of the population are created through the sampling. Furthermore, EO algorithm is s...

Estimation of distribution algorithms (EDAs) guide the search for the optimum by building and sampling explicit probabilistic models of promising candidate solutions. However, EDAs are not only optimization techniques; besides the optimum or its approximation, EDAs provide practitioners with a series of probabilistic models that reveal a lot of information about the problem being solved. This i...

One of the most promising research directions that focus on eliminating the drawbacks of fixed, problem-independent genetic algorithms, is to look at the generation of new candidate solutions as a learning problem, and use a probabilistic model of selected solutions to generate the new ones [5,9,10]. The algorithms based on learning and sampling a probabilistic model of promising solutions to g...