標(biāo)題: Titlebook: Computational Intelligence and Bioinformatics; International Confer De-Shuang Huang,Kang Li,George William Irwin Conference proceedings 200 [打印本頁] 作者: tornado 時間: 2025-3-21 18:49
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
作者: Panacea 時間: 2025-3-21 20:38 作者: 毛細(xì)血管 時間: 2025-3-22 01:34
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.作者: 煤渣 時間: 2025-3-22 08:04
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.作者: 現(xiàn)實 時間: 2025-3-22 10:55
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.作者: Grating 時間: 2025-3-22 15:22 作者: Grating 時間: 2025-3-22 21:04 作者: 卷發(fā) 時間: 2025-3-22 21:22
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.作者: 迅速成長 時間: 2025-3-23 02:31
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.作者: 一起平行 時間: 2025-3-23 08:31
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.作者: 勉強 時間: 2025-3-23 11:18
Ambika Gopal Raj,Lauren G. McClanahanBPSO approach to deal with constrains. Numerical experiments show that the proposed algorithm outperforms both the existing exact approaches and recent state-of-the-art search heuristics on most of the hard knapsack problems.作者: contradict 時間: 2025-3-23 15:18
A Constrained Ant Colony Algorithm for Image Registration 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.作者: 疲勞 時間: 2025-3-23 20:23
A Hybrid Particle Swarm Optimization for Binary CSPsimprove 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.作者: Hdl348 時間: 2025-3-24 01:07
Adaptive Particle Swarm Optimization with Feedback Control of Diversity 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.作者: 放肆的你 時間: 2025-3-24 05:12
Solving the Hard Knapsack Problems with a Binary Particle Swarm ApproachBPSO approach to deal with constrains. Numerical experiments show that the proposed algorithm outperforms both the existing exact approaches and recent state-of-the-art search heuristics on most of the hard knapsack problems.作者: depreciate 時間: 2025-3-24 08:13 作者: stratum-corneum 時間: 2025-3-24 11:12
https://doi.org/10.1007/978-3-031-62003-4y selection and the roulette wheel selection. Four parameters are used, which are two control parameters of transition probability . and., pheromone decrease factor ., and proportion factor .. in building methods. By simulated result analysis, the parameter selection rule will be given.作者: 刪除 時間: 2025-3-24 15:27 作者: 沙漠 時間: 2025-3-24 20:22 作者: 我沒有強迫 時間: 2025-3-25 03:03
Study of Parametric Relation in Ant Colony Optimization Approach to Traveling Salesman Problemy selection and the roulette wheel selection. Four parameters are used, which are two control parameters of transition probability . and., pheromone decrease factor ., and proportion factor .. in building methods. By simulated result analysis, the parameter selection rule will be given.作者: 入會 時間: 2025-3-25 03:21
Ant Colony System for Optimizing Vehicle Routing Problem with Time Windows (VRPTW)nt colonies to successively achieve a multiple objective minimization. Experiments on a series of benchmark problems demonstrate the excellent performance of ACS when compared with other optimization methods.作者: 令人苦惱 時間: 2025-3-25 08:41
A New Hybrid Algorithm of Particle Swarm Optimizationces the ability of getting rid of local optimum and improves the speed and precision of convergence. The testing results of several benchmark functions with different dimensions show that the proposed algorithm is superior to standard PSO and the other PSO algorithms.作者: collateral 時間: 2025-3-25 11:43 作者: inscribe 時間: 2025-3-25 17:11 作者: 變化無常 時間: 2025-3-25 21:10 作者: 改革運動 時間: 2025-3-26 01:36
An Improved Particle Swarm Optimization Algorithm with Disturbance Terming structure effectively mends the defects. The convergence of the improved algorithm is analyzed. Simulation results demonstrated that the improved algorithm have a better performance than the standard one.作者: 能得到 時間: 2025-3-26 05:32 作者: hysterectomy 時間: 2025-3-26 09:37
Improving Quantum-Behaved Particle Swarm Optimization by Simulated Annealingloys both the ability to jump out of the local minima in Simulated Annealing and the capacity of searching the global optimum in QPSO algorithm. The experimental results show that the proposed hybrid algorithm increases the diversity of the population in the search process and improves its precision in the latter period of the search.作者: 機械 時間: 2025-3-26 14:04
Predicted-Velocity Particle Swarm Optimization Using Game-Theoretic Approachme-theoretic approach for designing particle swarm optimization with a mixed strategy. The approach is applied to design a mixed strategy using velocity and position vectors. The experimental results show the mixed strategy can obtain the better performance than the best of pure strategy.作者: SOBER 時間: 2025-3-26 19:37
Collective Behavior of an Anisotropic Swarm Model Based on Unbounded Repulsion in Social Potential Fits anisotropy coefficient, and the collective behavior of mass individuals emerges from combination of the inter-individual interactions and the interaction of the individual with outer circumstances.作者: inculpate 時間: 2025-3-27 00:09 作者: 調(diào)色板 時間: 2025-3-27 05:11 作者: LAY 時間: 2025-3-27 05:39 作者: 意見一致 時間: 2025-3-27 12:42
https://doi.org/10.1007/978-3-031-39888-9ing structure effectively mends the defects. The convergence of the improved algorithm is analyzed. Simulation results demonstrated that the improved algorithm have a better performance than the standard one.作者: Dissonance 時間: 2025-3-27 14:27 作者: modifier 時間: 2025-3-27 18:00
Louise Gwenneth Phillips,Tracey Bundaloys both the ability to jump out of the local minima in Simulated Annealing and the capacity of searching the global optimum in QPSO algorithm. The experimental results show that the proposed hybrid algorithm increases the diversity of the population in the search process and improves its precision in the latter period of the search.作者: WAX 時間: 2025-3-27 23:09
How I Met My Contributing Authors,me-theoretic approach for designing particle swarm optimization with a mixed strategy. The approach is applied to design a mixed strategy using velocity and position vectors. The experimental results show the mixed strategy can obtain the better performance than the best of pure strategy.作者: 苦惱 時間: 2025-3-28 04:09 作者: 現(xiàn)任者 時間: 2025-3-28 08:19
0302-9743 a key role in pursuing for novel technology in recent years. The resulting techniques vitalize life science engineering and daily life applications. In light of978-3-540-37277-6978-3-540-37282-0Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Abutment 時間: 2025-3-28 11:16 作者: 正式演說 時間: 2025-3-28 15:57 作者: Bronchial-Tubes 時間: 2025-3-28 19:39
The Pre-History of Storyboarding,y model and present a parallel constrained ant colony model to solve the image registration problem. The problem is represented by a directed graph so that the objective of the original problem becomes to find the shortest closed circuit on the graph under the problem-specific constraints. A number 作者: dialect 時間: 2025-3-29 01:31 作者: Overthrow 時間: 2025-3-29 05:50
https://doi.org/10.1007/978-3-031-62003-4 of algorithms performance and the different control parameter settings. Two tour building methods are used in this paper including the max probability selection and the roulette wheel selection. Four parameters are used, which are two control parameters of transition probability . and., pheromone d作者: Finasteride 時間: 2025-3-29 08:22 作者: 制度 時間: 2025-3-29 12:52 作者: 藥物 時間: 2025-3-29 17:25
https://doi.org/10.1007/978-981-99-4246-6SA) is embedded into standard PSO algorithm. The proposed algorithm not only keeps the characters of simple and easy to be implemented, but also enhances the ability of getting rid of local optimum and improves the speed and precision of convergence. The testing results of several benchmark function作者: 誘使 時間: 2025-3-29 23:28
https://doi.org/10.1007/978-3-031-39888-9SPSO). The resulting algorithm is known as PSOOFT that makes use of two mechanisms of OFT: a reproduction strategy to enhance the ability to converge rapidly to good solutions and a patch-choice based scheme to keep a right balance of exploration and exploitation. In the simulation studies, several 作者: Proclaim 時間: 2025-3-30 01:15
Nicole Kennedy,Melanie Duckworthems(MOP). While accelerating the computing speed is important for algorithms to solve real-life MOP also. A Smart Particle Swarm Optimization algorithm for MOP(SMOPSO) is proposed. By setting the cooperative action of all the objective functions as the global best guide of swarm and selecting the cl作者: 反抗者 時間: 2025-3-30 08:03
Nicole Kennedy,Melanie Duckworthvergence, the paper introduced a negative feedback mechanism into particle swarm optimization and developed an adaptive PSO. The improved method takes advantage of the swarm-diversity to control the tuning of the inertia weight (PSO-DCIW), which in turn can adjust the swarm-diversity adaptively and 作者: Obliterate 時間: 2025-3-30 11:46
Critical Approaches to Children‘s Literaturecheme that takes both objective and constraint into account is adopted to evaluate the survival chance of any particle, thus avoid the drawbacks of traditional penalty method. In the evolution process, if the population best particle has no update during a prescribed number of consecutive generation作者: Gene408 時間: 2025-3-30 15:01 作者: Accrue 時間: 2025-3-30 17:13
https://doi.org/10.1007/978-3-031-39888-9olution for blending scheduling, especially under uncertainty. As a novel evolutionary computing technique, particle swarm optimization (PSO) has powerful ability to solve nonlinear optimization problems with both continuous and discrete variables. In this paper, the performance of PSO under uncerta作者: tenuous 時間: 2025-3-30 21:29
Critical Approaches to Children‘s Literaturety characteristic between particles may be lost because the higher weighted particles will be replicated and the lower weighted particles will be discarded. For parameter-fixed application cases, the standard particle filter is invalid as no importance density function can be sampled for new particl作者: cornucopia 時間: 2025-3-31 02:32 作者: abreast 時間: 2025-3-31 08:13
Tracey Bunda,Louise Gwenneth Phillipshas been one of the major subjects for both the research community and the automotive industry. In this paper, a CRS, which includes a child booster and an adult seatbelt with load limiting function, is optimized for a ten-year child dummy. The model is built and simulated using MADYMO. Several key 作者: 發(fā)酵劑 時間: 2025-3-31 09:29 作者: Firefly 時間: 2025-3-31 14:45
Ambika Gopal Raj,Lauren G. McClanahanolynomial time nowadays, yet there are a variety of test problems which are hard to solve for the existing algorithms. In this paper we propose a new approach based upon binary particle swarm optimization algorithm (BPSO) to find solutions of these hard knapsack problems. The standard PSO iteration 作者: Hallowed 時間: 2025-3-31 21:32
https://doi.org/10.1007/978-3-658-06253-8epulsion and social potential fields. The unbounded repulsion ensures the independence among autonomous agents in social potential fields, which consist of obstacles to avoid and targets to move towards. Simulation results show that the aggregating swarm can construct various formations by changing 作者: RECUR 時間: 2025-3-31 21:46
Schlussbetrachtung und Ausblick,s (ANN) for the diagnosis of unexplained syncope. Compared with BP and GA based training techniques, PSO based learning method improves the diagnosis accuracy and speeds up the convergence process. Experimental results show that PSO is a robust training algorithm and should be extended to other real
