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Whether the sampling subnets can accurately represent the topology and dynamics of the original networks is an important research topic. To improve the quality of network sampling, this paper attempts to convert the complex network sampling process to an optimization problem, and proposes a novel sampling algorithm which is based on Particle Swarm Optimization (PSO). Exponent of power-law degree distribution...
This paper discusses a novel method and check the effectiveness in combining deterministic generalized orthonormal basis filters (GOBF) with stochastic autoregressive moving average (ARMA) filters and its state space representation. The effectiveness of GOBF models can be improved by coupling an ARMA model in the presence of unmeasured disturbances. In this work particle swarm optimization (PSO) algorithm...
Inertia weight w and acceleration coefficients c are the most effective ways of improving the performance of particle swarm optimization (PSO). A improved PSO was proposed, in which w and c were set to be the function of fitness value and adapted itself in the way of fitness feedback at each iteration. In order to reduce the probability of trapping into a local minimum value, w was recalculated according...
This paper presents a BP network based on improved particle swarm optimization to solve the selective harmonic elimination technique of switch angles. One of the difficulties of selective harmonic elimination technique is solving the switch angles, the traditional method has shortcomings such as initial value selection is difficult and the iterative process complex. Traditional BP algorithm also has...
This paper discussed a take-off posture optimization method of the Locust-like Hopping Robot using particle swarm optimization. The kinematic model was first established based on DH method for the locustlike hopping robot, and the mapping relation of robot from the center of mass space to the joint space was obtained. The jumping performance of the hopping robot was evaluated by computing the velocity...
Node localization is a research hotspot in underwater wireless sensor networks (UWSN) because most applications are based on geographical position of nodes. Currently, most of node localization methods are based on the two-dimensional space and could not meet the requirement of location accuracy. A three-dimensional node localization method was proposed based on a ranging technology named RTOF (round-trip...
As a popular data driven method, Artificial Neural Networks (ANNs) are widely applied in building energy prediction field. In this paper, a hybrid prediction approach that combines Particle Swarm Optimization (PSO) and ANN is presented. Before the prediction model applied, the principal component analysis (PCA) is used for the selection of the input variables, which helps to reduce the input dimension...
The tank, as traditional land warfare equipment, has been playing an important role in the war. According to the problem that the real-time and high effectiveness are difficult to be met in target assignment of tank intelligent forces, an improved method named Population Explosion Particle Swarm Optimization (PE-PSO) is proposed. The PE-PSO introduces the "Population Explosion Operator"...
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