... với thuậttoán tối ưu khác 51 2.1.4 Tính chất thuậttoánPSO 52 2.1.5 Ưu nhược điểm thuậttoánPSO 52 2.1.6 Ứng dụng thuậttoánPSO .52 2.2 ThuậttoánPSO song song PSO ... THOẬT TOÁN TỐI ƢU BẦY ĐÀN 47 2.1 Tổng quan thuậttoánParticleSwarmOptimization (PSO) 47 2.1.1 Giới thiệu 47 2.1.2 ThuậttoánPSO 48 2.1.3 Sự khác biệt thuậttoánPSO ... GIỚI THIỆU VỀ THOẬT TOÁN TỐI ƢU BẦY ĐÀN PARTICLESWARMOPTIMIZATION (TỐI ƯU HÓA BẦY ĐÀN) 2.1 Tổng quan thuậttoánParticleSwarmOptimization (PSO) Phương pháp tối ưu bầy đàn thuật tốn xây dựng...
... biệt thuậttoánPSO so với thuật tốn tối ưu khác 2.1.4 Tính chất thuậttoánPSO 2.1.5 Ưu nhược điểm thuậttoánPSO 2.1.6 Ứng dụng thuậttoánPSO 2.2 ThuậttoánPSO song song PSO nối tiếp 2.2.1 Thuật ... đo máy CMM - Cơ sở toán học cơng cụ tốn phép đo xử lý liệu - Tổng quan thuậttoánParticleSwarmOptimization (PSO) - Mơ hình tốn xác định sai số độ trụ - Sử dụng thuậttoánPSO đánh giá độ trụ ... “Sử dụng thuậttoánParticleSwarmOptimization đánh giá độ trụ từ liệu đo máy CMM C544” cấp thiết có ý nghĩa khoa học thực tiễn II Mục đích đề tài - Sử dụng thuậttoánParticleSwarm Optimization...
... với thuậttoán tối ưu khác 51 2.1.4 Tính chất thuật tốn PSO 52 2.1.5 Ưu nhược điểm thuậttoánPSO 52 2.1.6 Ứng dụng thuậttoánPSO .52 2.2 ThuậttoánPSO song song PSO ... THOẬT TOÁN TỐI ƢU BẦY ĐÀN 47 2.1 Tổng quan thuậttoánParticleSwarmOptimization (PSO) 47 2.1.1 Giới thiệu 47 2.1.2 ThuậttoánPSO 48 2.1.3 Sự khác biệt thuậttoánPSO ... chương trình PSO ứng dụng 78 4.4 So sánh thuậttoánPSO với thuậttoán Dhanish 82 4.4.1 Thuậttoán Dhanish xác định độ khơng tròn 82 4.4.2 Kết việc ứng dụng thuậttoán Dhanish...
... order to obtain this, the system is developed using an optimization framework based on PSOParticleSwarmOptimizationPSO is a stochastic optimization technique which was introduced recently based ... applying PSO is to define a fitness function, which could lead the swarm to the optimized particles based on the application and data The choice of this function is very crucial since, based on this, PSO ... PSO is one of the populationbased search methods which takes advantage of the concept of social sharing of information In this algorithm each particle can learn from the experience of other particles...
... pseudo inverse, tr(.) is trace, E(.) is expectation [9,10] Particleswarmoptimization The particleswarmoptimization (PSO) is an evolutionary optimization algorithm whose mechanics are inspired by ... channel estimation method are presented in next section followed by particleswarm optimization, objective function of particleswarm optimization, simulation results and discussion Finally, this article ... for PSO P Parameter Value FFT size L Ri = The parameters of particleswarmoptimization that has been used for the optimization of location and (or) power of pilot tones are given as follows: swarm...
... PFCEA algorithm (to be explained in Section 4), we propose to use particleswarmoptimization (PSO) as the optimization engine PSO was proposed by Kennedy and Eberhart to model birds flocking and ... Eberhart, Particleswarm optimization, ” in Proceedings of the IEEE International Conference on Neural Networks, pp 19421948, December 1995 B Brandstă tter and U Baumgartner, Particleswarm a optimization mass-spring ... of the PSO algorithm, all the particles vary their positions and velocities to search for the best solution The optimal position found by the particles swarm is the final solution of the optimization...
... 10 15 Particle number PSO traffic TPSO traffic 20 25 30 35 40 Particle number PSO TPSO (a) (b) Figure 11: (a) TPSO traffic overhead in relation to PSO based on Table and (b) convergence speed of particles ... Networking Layer PSO Layer n − Layer n − Layer n PSOPSO Layer n + Layer n Layer n − Layer n PSO Layer n + Layer n + Layer Layer Layer Category Category PSO Layer Optimization layer ... super particle is treated in a similar way to normal particles, using super particles in TPSO reduces the number of required packets In Figure 11(b) the average convergence time for PSO and TPSO...
... value of the current best particle 10−2 10−4 10 12 14 PAPR0 (dB) Original OFDM PSO Gn = PSO Gn = PSO Gn = 10 PSO Gn = 20 PSO Gn = 30 PSO Gn = 40 OPTS Figure 3: CCDF of PSO technique for different ... Original OFDM PSO- PTS (M = 2, W PSO- PTS (M = 2, W PSO- PTS (M = 2, W PSO- PTS (M = 2, W 10 12 PAPR0 (dB) = 2) = 4) = 8) = 16) 14 16 18 10−4 PSO- PTS (M = 4, W PSO- PTS (M = 4, W PSO- PTS (M = 4, W PSO- PTS ... antenna using a particleswarmoptimization approach,” IEEE Transactions on Antennas and Propagation, vol 53, no 10, pp 1–7, 2005 [24] J Robinson and Y Rahmat-Samii, Particleswarm optimization...
... Coevolutionary MOPSO: A distributed coevolutionary particleswarmoptimization algorithm (DCPSO) is implemented to exploit the inherent parallelism of coevolutionary particleswarmoptimization DCPSO is ... advanced and efficient optimization techniques This thesis investigates the application of an efficient optimization method, known as ParticleSwarmOptimization (PSO) , to the field of MO optimization CHAPTER ... vi A Distributed Co-evolutionary ParticleSwarmOptimization Algorithm 93 5.1 Review of Existing Distributed MO Algorithms 5.2 Co-evolutionary ParticleSwarmOptimization Algorithm 5.2.1 5.3...
... Cooperation Multi-Agents System Multi-level ParticleSwarmOptimization Multi-level Multi-step ParticleSwarmOptimization Neural Network ParticleSwarmOptimization x Chapter Introduction 1.1 Overview: ... occur in the population, survive and generate their offspring 2.3.4 ParticleSwarmOptimizationParticleSwarmOptimization (PSO) is also a fruit of careful and minded observance of natural existence ... application, PSO has been used in several areas Two kinds of typically usages of PSO are: Power system control using PSO [11] and Neural networks training using PSO [12] [13] ParticleSwarm Optimization...
... algorithm and PSO (GA -PSO) , evolutionary PSO (EPSO) and differential evolution PSO (DEPSO and C -PSO) which are discussed in this section 1) Hybrid of Genetic Algorithm and PSO (GA -PSO) : GA -PSO combines ... Lamont, “Visualizing particleswarmoptimization Gaussian particleswarm optimization, ” in Proc IEEE Swarm Intell Symp., Apr 2003, pp 198–204 [153] R Krohling, “Gaussian particleswarm with jumps,” ... advances in particle swarm, ” in Proc IEEE Congr Evol Comput., Jun 2004, vol 1, pp 90–97 [88] H Fan and Y Shi, “Study on Vmax of particleswarm optimization, ” in Proc Workshop on ParticleSwarm Optimization, ...
... Polprasert et al.: Optimal Reactive Power Dispatch Using Improved Pseudo-gradient Search ParticleSwarmOptimization Downloaded by [New York University] at 00:10 06 March 2016 Input/control variables ... (Artificial Intelligence in Power System Optimization) His research interests are in power system operation, artificial intelligence applications in power system optimization, smart grids, and microgrids ... interests are in power system operation, planning and analysis, and artificial intelligence-based optimization applications in power systems Weerakorn Ongsakul obtained his B.Eng (electrical engineering)...
... algorithms (EA) uses some sorts of Ant Colony Optimization (ACO) Ismail & Loh, 2009; Karadimas, Papatzelou, & Loumos, 2007b, ParticleSwarmOptimization (PSO) , Genetic Algorithm (GA) Fan et al., 2010 ... outcomes CPSO was proven to converge to the global optimum rather than PSO (Kennedy & Eberhart, 1995) or PSO with Passive Congregation (PSOPC) He & et al., 2004 The pseudo-code of CPSO procedure ... also employs a variant of PSO named as CPSO, which was proven to converge to the global optimum rather than PSO and PSOPC As such, the total collected waste quantity of CPSO-ArcGIS is the largest...
... Maximal number of iteration steps in PSO – MaxStep PSO - Final center V(0) Output ParticleSwarmOptimization (PSO) 1: 2: 3: 4: Initialization Repeat For each particle Assign remaining patterns ... to converge quickly to the (sub-) optima solutions, a meta-heuristic optimization method namely ParticleSwarmOptimization – PSO [18] is used to determine good initial centers for CFGWC2 • Since ... threshold ε1 For the problem (5)–(7), we use PSO [18] to determine the (sub) optima solutions with the beginning population being initiated with P particles Each particle is a vector z = (z1 , z2 , ,...
... calculated by (4) XIA et al.: A GLOBAL OPTIMIZATION ALGORITHM FOR ELECTROMAGNETIC DEVICES 2063 Fig Flow chart of global optimization algorithm III GLOBAL OPTIMIZATION ALGORITHM EMPLOYING MULTIPLE ... find optimum solution of this problem using typical optimization techniques Therefore, proposed global optimization by Taylor Kriging and PSO is employed to resolve the difficulties Electromagnetic ... tool for electromagnetic device optimization, ” IEEE Trans Magn., vol 40, no 2, pp 1196–1199, Mar 2001 [8] M T Pham, M H Song, and C S Koh, “Coupling particles swam optimization for multimodal electromagnetic...
... Calculate particle velocity according to (6.a) (or (6.b)) II PARTICLESWARMOPTIMIZATION FOR SOLVING GRAPH COLORING PROBLEM A ParticleswarmoptimizationParticleswarmoptimization is a stochastic optimization ... Choose the particle with the best fitness value of all the particles as the gBest (or Choose the particle with the best fitness value of all the neighbors particles as the lBest) For each particle ... that is tracked by the particleswarm optimizer is the best value, obtained so far by any particle in the population This best value is a global best and called gbest When a particle takes part...
... with joining a heuristic optimizer (particle swarmoptimization [PSO] ) and a feedforward ANN method to estimate natural gas water content The main task of PSO is to decide an optimal CONTACT ... October 27 Kennedy, J (1997) The particle swarm: social adaptation of knowledge Proc IEEE Int Conf Evol Comput 303–308 Kennedy, J., and Eberhart, R (1995) Particleswarmoptimization Proc IEEE Int ... oil well production performance using artificial neural network (ANN) linked to the particleswarmoptimization (PSO) tool Petroleum 1:118–132 Ahmadi, M A., and Ebadi, M (2014) Evolving smart approach...
... giải nhiều toán lý thuyết thực tế Đề tài Thuậttoán bầy đàn PSO, giải thuật di truyền ứng dụng giải toán tối ưu đa mục tiêu” nhằm tìm hiểu khả ứng dụng thuậttoán PSO, GA việc giải toán tối ưu ... t phân bố đột biến miền [0, x] 2.4 Thuậttoán tối ƣu bầy đàn PSO 2.4.1 Giới thiệu Thuật tốn tối ưu hóa bầy đàn (Particle SwarmOptimization – PSO) thuậttoán nhằm giải tốn tối ưu hóa mơ hình ... SỞ THUẬTTOÁN DI TRUYỀN Trong chương 2, luận văn trình bày kiến thức lĩnh vực tính tốn mềm bao gồm thuật tốn di truyền (GA) thuậttoán bầy đàn (PSO) giải toán đa mục tiêu Các kiến thức thuật toán...