Titlebook: Computational Intelligence and Bioinformatics; International Confer De-Shuang Huang,Kang Li,George William Irwin Conference proceedings 200

tornado

書目名稱Computational Intelligence and Bioinformatics影響因子(影響力)




書目名稱Computational Intelligence and Bioinformatics影響因子(影響力)學(xué)科排名




書目名稱Computational Intelligence and Bioinformatics網(wǎng)絡(luò)公開度




書目名稱Computational Intelligence and Bioinformatics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Intelligence and Bioinformatics被引頻次




書目名稱Computational Intelligence and Bioinformatics被引頻次學(xué)科排名




書目名稱Computational Intelligence and Bioinformatics年度引用




書目名稱Computational Intelligence and Bioinformatics年度引用學(xué)科排名




書目名稱Computational Intelligence and Bioinformatics讀者反饋




書目名稱Computational Intelligence and Bioinformatics讀者反饋學(xué)科排名

Panacea

毛細(xì)血管

Tracey Bunda,Louise Gwenneth Phillipsn method, AutoDOE, a built-in subroutine of MADYMO, is also utilized for comparison. The results indicate that the particle swarm algorithm has certain advantages over the AutoDOE method in terms of the solution quality. Moreover, regarding the computational efficiency, for this particular problem the particle swarm algorithm outperforms AutoDOE.

煤渣

An Improved Particle Swarm Algorithm and Its Application to Power System Transfer Capability Optimizticle the optimum value can be obtained. This improved particle swarm algorithm is then successfully applied to IEEE118 bus system optimization problem. Compared with a traditional well-known method, sequential quadratic programming, our proposal obtains better solutions for this problem.

現(xiàn)實(shí)

Fixed Parameter Estimation Method Using Gaussian Particle Filtermple of Direction of Arrived (DOA) estimation for coherent signals propagated in space with multi-path fading, the computer simulation has been performed. The simulation results have indicated that the performance of the new method is rather than general particle filtering.

Grating

Grating

卷發(fā)

The Pre-History of Storyboarding, guiding the future exploration of the graph. The algorithm supports the parallel computation and facilitates quick convergence to the optimal solution. The performance of the proposed method as compared to those of the genetic-based approaches is very promising.

迅速成長

https://doi.org/10.1007/978-981-99-4246-6improve the activities of particles. Tabu list is used to avoid cycling in the global best particle. We experiment with random constraint satisfaction problem instances based on phase transition theory. Experimental results indicate that the hybrid algorithm has advantages on the search capability and the iterative number.

一起平行

Nicole Kennedy,Melanie Duckworth methods for PSO. The relative experimental results show PSO-DCIW is a robust global optimization method for the complex multimodal functions, which can improve the performance of the standard PSO and alleviate the premature convergence validly.