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Sequential optimization and reliability assessment (SORA) has been widely used in reliability-based design optimization (RBDO), but it is hindered by the unaffordable computational burden of high dimensional cases. In this work, we propose a new strategy to improve the efficiency of the SORA while performing high dimensional RBDO. The dimension-adaptive tensor-product (DATP) algorithm and hierarchical...
Particle filters perform the nonlinear estimation and have been proven to be a powerful tool in solving visual tracking problems. However, the problem of sample impoverishment is still a drawback of particle filter. To solve this problem, a bat-inspired particle filter is proposed in this work. The particles in the particle filter are optimized using a new biologically inspired optimization algorithm,...
Traveling salesman problem (TSP) which is a classic combinational optimization problem has a wide range of applications in many areas. Many researchers focus on this problem and propose several algorithms. However, it was proved to be NP-hard, which is very difficult to be solved. No algorithm can solve any types of this problem effectively. In order to propose an effective algorithm for TSP, this...
Outlier detection is an important data mining task, LOF(local outlier factor) was proposed to indicate the degree of outlierness, which is practical for finding local outliers. However, it is difficult to decide the neighborhood size. In this paper a multi-granularity local outlier detection(MLOD) method is proposed to organize the outlierness under multi-granularity. It finds local outliers in varying...
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