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Particle swarm optimization (PSO) is a population-based stochastic search algorithm inspired from the natural behavior of bird flocking or fish schooling for searching their foods. Due to its easiness in numerical implantations, PSO has been widely applied to solve a variety of inverse and optimization problems. However, a PSO is often trapped into local optima while dealing with complex and real...
Landing footprint of an entry vehicle provides critical information for mission planning. Conventional methods calculate it through solving a family of multi-constraints optimal control problems. It is difficult to solve. To generate the boundary of it, we proposed a new scheme based on differential evolution(DE). Utilizing DE's parallelism, each run generates one side instead of one point of the...
Storage virtualization provides abstraction to pervasive storage graphs. Data management operations require pervasive search utilities to discovery entities and services. In search methods, algorithmic complexity, such as memory bound problems, error convergence issues and supervised training is prohibitive for large state and solution spaces or high dimensional state spaces. In addition, among popular...
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