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In this paper, a new scheme to reduce the positioning error is investigated for wireless sensor networks (WSN). To be specific, conventional Distance Vector-Hop (Dv-Hop) algorithm fail to calculate the average distance per-hop with high precision that caused by the random distribution of the irregular network topology, greatly leading to the positioning error in the Dv-Hop algorithm. To enhance the...
Condition monitoring and incipient fault diagnosis of rolling bearing is of great importance to detect failures and ensure reliable operations in rotating machinery. In this paper, a new multi-speed fault diagnostic approach is presented by using self-adaptive wavelet transform components generated from bearing vibration signals. The proposed approach is capable of discriminating signatures from four...
We propose a new population-based optimization algorithm, named Social Network-based Swarm Optimization algorithm (SNSO), for solving unconstrained single-objective optimization problems. In SNSO, the population topology, neighborhood structure and individual learning behavior are used to improve the search performance of a swarm. Specifically, a social network model is introduced to adjust the population...
The path planning problem for unmanned vehicle searching over the region of interest with obstacles is investigated in this paper. The path planning problem is decomposed into the sensor deployment problem and the travelling salesman problem based on the fundamental finding that the vehicle could search the region that covered by the sensor if the vehicle pass through the position where the sensor...
To handle multicriteria fuzzy decision-making problems, a new multicriteria decision-making method is proposed in which the information about criteria's weights is not completely certain, and the criteria values of alternatives are Atanassov's intuitionistic fuzzy sets (A-IFSs). Using evidential reasoning algorithms, the criteria values are aggregated; receiving the overall A-IFS for alternatives...
For the disadvantages of the traditional PSO algorithm, which global optimum and convergence speed and accuracy are difficult to take into account together, proposed an adaptive PSO algorithm using a inertia weight factor, and applied it to the PI controller parameters of HVDC optimization design to CIGRE Benchmark Model as an example, according to its structure and its electrical parameters, deduced...
To the problem of the premature convergence and lower searching precision of the standard particle swarm optimization (PSO), this paper provides niche chaotic mutation quantum-behaved particle swarm optimization (NCQPSO) algorithm for image elastic registration, through maximizing the value of JS measure to achieve. In this algorithm, niche methods and eliminating strategy are introduced to improve...
In the few years, several neural networks are proposed to image classification. Support vector machine classifier employs the structural risk minimization principles, which make support vector machine classifier have good generalization ability. In order to solve the problem of parameters selection of support vector machine, particle swarm optimization is applied to select the parameters of support...
The characteristic of instant customerization (IC) production model and its job-shop scheduling problem is described. Considering the conventional algorithmspsila low efficiency of search especially global search, PSO-based to job shop scheduling problem of IC is presented. According to the characteristics of the problem, the PSO coding and optimization are studied to determine the way of coding and...
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