MaplePrimes - comments on Post, Get help

MaplePrimes - comments on Post, Get help http://www.mapleprimes.com/posts/37139-Get-Help en-us 2026 Maplesoft, A Division of Waterloo Maple Inc. Maplesoft Document System Thu, 11 Jun 2026 09:05:28 GMT Thu, 11 Jun 2026 09:05:28 GMT The latest comments added to the Post, Get help http://www.mapleprimes.com/images/mapleprimeswhite.jpg MaplePrimes - comments on Post, Get help http://www.mapleprimes.com/posts/37139-Get-Help probably http://www.mapleprimes.com/posts/37139-Get-Help?ref=Feed:MaplePrimes:Get help:Comments#comment65261 probably you need to hire someone who knows both languages to do the translation --- G A Edgar The latest comments added to the Post, Get help 65261 Mon, 22 Jun 2009 18:08:40 Z edgar edgar FromMFile http://www.mapleprimes.com/posts/37139-Get-Help?ref=Feed:MaplePrimes:Get help:Comments#comment65262 I haven't done much translating back and forth with Maple and Matlab, but you might using <a href="http://www.maplesoft.com/support/help/view.aspx?path=Matlab/FromMFile">FromMFile.</a> The latest comments added to the Post, Get help 65262 Mon, 22 Jun 2009 18:26:25 Z Tim Vrablik Tim Vrablik Hello all, Thank you so http://www.mapleprimes.com/posts/37139-Get-Help?ref=Feed:MaplePrimes:Get help:Comments#comment65263 Hello all,   Thank you so much, but I have the algorithm of this method, could any one help to write it in maple. Regards. the algorithm:After finding the two best values, the particle updates its velocity and position according to equations (1) and (2) respectively. (vk+1) i =w(vk) i + c1 r1  (pbest i - (xk) i ) + c2 r2 (gbestk - (xk) i ) (xk+1) i= (xk)i + (vk+1) i where ( The 1 v k) i  is the velocity of ith particle at the kth iteration, (xk) is current the solution (or position) of the ith particle. r1 and r2 are random numbers generated uniformly between 0 and 1. c1 is the self-confidence (cognitive) factor and c2 is the swarm confidence (social) factor. Usually c1 and c2 are in the range from 1.5 to 2.5. Finally, w is the inertia factor that takes linearly decreasing values downward from 1 to 0 according to a predefined number of iterations as recommended by Haupt and Haupt [2004].st term in equation (1) represents the effect of the inertia of the particle, the 2nd term represents the particle memory influence, and the 3rd term represents the swarm (society)influence.. The velocities of the particles on each dimension may be clamped to a maximum velocity Vmax, which is a parameter specified by the user. If the sum of accelerations causes thevelocity on that dimension to exceed Vmax, then this velocity is limited to Vmax [Haupt and Haupt 2004]. Another type of clamping is to clamp the position of the current solution to a certain range in which the solution has valid value, otherwise the solution is meaningless [Haupt and Haupt 2004]. In this Chapter, position clamping is applied with no limitation on the velocity values.   PSO is initialized with a group of random particles (solutions) and then searches for optima by updating generations. During every iteration, each particle is updated by following two"best" values. The first one is the position vector of the best solution (fitness) this particle hasachieved so far. The fitness value is also stored. This position is called position that is tracked by the particle swarm optimizer is the best position, obtained so far, by any particle in the population. This best position is the current global best and is calledgbest   The latest comments added to the Post, Get help 65263 Tue, 23 Jun 2009 07:18:08 Z ahmedluss ahmedluss