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[Other resource] 模拟退火例子1 DL : 0: 模拟退火算法来源于固体退火原理，将固体加温至充分高，再让其徐徐冷却，加温时，固体内部粒子随温升变为无序状，内能增大，而徐徐冷却时粒子渐趋有序，在每个温度都达到平衡态，最后在常温时达到基态，内能减为最小。根据Metropolis准则，粒子在温度T时趋于平衡的概率为e-ΔE/(kT)，其中E为温度T时的内能，ΔE为其改变量，k为Boltzmann常数。用固体退火模拟组合优化问题，将内能E模拟为目标函数值f，温度T演化成控制参数t，即得到解组合优化问题的模拟退火算法：由初始解i和控制参数初值t开始，对当前解重复“产生新解→计算目标函数差→接受或舍弃”的迭代，并逐步衰减t值，算法终止时的当前解即为所得近似最优解，这是基于蒙特卡罗迭代求解法的一种启发式随机搜索过程。退火过程由冷却进度表(Cooling Schedule)控制，包括控制参数的初值t及其衰减因子Δt、每个t值时的迭代次数L和停止条件S。 -simulated annealing algorithm derived from solid annealing method, the heating to the full solid, let its slowly cooling, heating, solid particles with internal temperature rise-into disorder, which can increase, and slowly cooling gradual and orderly particles in each temperature has reached equilibrium, in the end when the temperature reached to ground state, which can be reduced to the minimum. According to the Metropolis criteria particles at a temperature T leveling the probability of e- E / (kT), in which the E-T when the temperature within, E capacity for change, for the Boltzmann constant k. Solid simulated annealing combinatorial optimization problems, will be able to target E simulation function f, T evolved temperature control parameters t, that is to be solving combinatorial o
Date : 2008-10-13 Size : 8.91kb User : 刘明
[Other resource] 模拟退火例子2 DL : 0: 模拟退火算法来源于固体退火原理，将固体加温至充分高，再让其徐徐冷却，加温时，固体内部粒子随温升变为无序状，内能增大，而徐徐冷却时粒子渐趋有序，在每个温度都达到平衡态，最后在常温时达到基态，内能减为最小。根据Metropolis准则，粒子在温度T时趋于平衡的概率为e-ΔE/(kT)，其中E为温度T时的内能，ΔE为其改变量，k为Boltzmann常数。用固体退火模拟组合优化问题，将内能E模拟为目标函数值f，温度T演化成控制参数t，即得到解组合优化问题的模拟退火算法：由初始解i和控制参数初值t开始，对当前解重复“产生新解→计算目标函数差→接受或舍弃”的迭代，并逐步衰减t值，算法终止时的当前解即为所得近似最优解，这是基于蒙特卡罗迭代求解法的一种启发式随机搜索过程。退火过程由冷却进度表(Cooling Schedule)控制，包括控制参数的初值t及其衰减因子Δt、每个t值时的迭代次数L和停止条件S。 -simulated annealing algorithm derived from solid annealing method, the heating to the full solid, let its slowly cooling, heating, solid particles with internal temperature rise-into disorder, which can increase, and slowly cooling gradual and orderly particles in each temperature has reached equilibrium, in the end when the temperature reached to ground state, which can be reduced to the minimum. According to the Metropolis criteria particles at a temperature T leveling the probability of e- E / (kT), in which the E-T when the temperature within, E capacity for change, for the Boltzmann constant k. Solid simulated annealing combinatorial optimization problems, will be able to target E simulation function f, T evolved temperature control parameters t, that is to be solving combinatorial o
Date : 2008-10-13 Size : 10.82kb User : 刘明
[Other resource] 模拟退火例子3 DL : 0: 模拟退火算法来源于固体退火原理，将固体加温至充分高，再让其徐徐冷却，加温时，固体内部粒子随温升变为无序状，内能增大，而徐徐冷却时粒子渐趋有序，在每个温度都达到平衡态，最后在常温时达到基态，内能减为最小。根据Metropolis准则，粒子在温度T时趋于平衡的概率为e-ΔE/(kT)，其中E为温度T时的内能，ΔE为其改变量，k为Boltzmann常数。用固体退火模拟组合优化问题，将内能E模拟为目标函数值f，温度T演化成控制参数t，即得到解组合优化问题的模拟退火算法：由初始解i和控制参数初值t开始，对当前解重复“产生新解→计算目标函数差→接受或舍弃”的迭代，并逐步衰减t值，算法终止时的当前解即为所得近似最优解，这是基于蒙特卡罗迭代求解法的一种启发式随机搜索过程。退火过程由冷却进度表(Cooling Schedule)控制，包括控制参数的初值t及其衰减因子Δt、每个t值时的迭代次数L和停止条件S。 -simulated annealing algorithm derived from solid annealing method, the heating to the full solid, let its slowly cooling, heating, solid particles with internal temperature rise-into disorder, which can increase, and slowly cooling gradual and orderly particles in each temperature has reached equilibrium, in the end when the temperature reached to ground state, which can be reduced to the minimum. According to the Metropolis criteria particles at a temperature T leveling the probability of e- E / (kT), in which the E-T when the temperature within, E capacity for change, for the Boltzmann constant k. Solid simulated annealing combinatorial optimization problems, will be able to target E simulation function f, T evolved temperature control parameters t, that is to be solving combinatorial o
Date : 2008-10-13 Size : 5.91kb User : 刘明
[Other resource] lbm_d2q920051201 DL : 1: 格子Boltzmann方法格子Boltzmann方法是为了保留格子气自动机方法的优点，克服其缺点而发展起来的方法。特别是1992年，钱跃弘、陈十一等的开创性工作(提出LBGK模型方法)，使该方法广泛地应用到计算流体力学(单相流、多相流、多孔介质流、热对流、磁流体、反应-扩散等)。 -lattice Boltzmann method lattice Boltzmann method is to retain the lattice gas automata the advantages and overcome its shortcomings and develop ways. In particular, in 1992, Qian Yue Wong Chan 11 the pioneering work (proposed Computational Model), the approach to the wider application of computational fluid dynamics (single-phase flow, multiphase flow, flow in porous media, thermal convection, MHD, the reaction - diffusion, etc.).
Date : 2008-10-13 Size : 469.49kb User : 张翟
[Other resource] LBM_Linux20051208 DL : 1: 格子Boltzmann方法格子Boltzmann方法是为了保留格子气自动机方法的优点，克服其缺点而发展起来的方法。特别是1992年，钱跃弘、陈十一等的开创性工作(提出LBGK模型方法)，使该方法广泛地应用到计算流体力学(单相流、多相流、多孔介质流、热对流、磁流体、反应-扩散等)。这是“格子模型”的并行处理，在LINUX下调试通过-lattice Boltzmann method lattice Boltzmann method is to retain the lattice gas automata the advantages and overcome its shortcomings and develop ways. In particular, in 1992, Qian Yue Wong Chan 11 the pioneering work (proposed Computational Model), the approach to the wider application of computational fluid dynamics (single-phase flow, multiphase flow, flow in porous media, thermal convection, MHD, the reaction - diffusion, etc.). This is the "lattice model" of parallel processing, the adoption of Linux Debugging
Date : 2008-10-13 Size : 17.53kb User : 张翟
[Other resource] Boltzmann DL : 0: vb的波尔兹曼机（含模拟退火算法），有需要的可参考一下 -vb the Boltzmann machine (with simulated annealing algorithm), the need of a reference
Date : 2008-10-13 Size : 1.38kb User : 张耀天
[Other resource] D1Q5_c DL : 1: 用于液体模拟，是研究cfd的一种新方法，称之为lattice boltzmann方法。本程序是d105模型的编码。这类编码网上很少，几近没有。如果哪们朋友有这方面的还希望能共用-for liquid simulation study cfd a new method, boltzmann called the lattice method. The procedure is d105 model coding. Few of these online coding, there was virtually no. If what they have friends in this area also hope to share
Date : 2008-10-13 Size : 2.64kb User : 刘品
[Other resource] LBM_HUST(C++) DL : 1: 是格子boltzmann中的一段代码,希望对做多相流的朋友有所帮助.-lattice boltzmann is the section of code, and I hope to do multiphase flow friends help.
Date : 2008-10-13 Size : 2.5kb User : 刘品
[Other resource] lbmval DL : 1: Lattice Boltzmann 程序，使用D2Q9模型，模拟流体在多孔介质中的渗流。-procedures, the use of D2Q9 model Simulation of Fluid in the porous medium flow.
Date : 2008-10-13 Size : 1.83kb User : he fengjiang
[Other resource] anb.tar DL : 0: the free lattice Boltzmann code anb ，一段lattice Boltzmann Method程序源码
Date : 2008-10-13 Size : 22.52kb User : 成军
[Other resource] Boltzmann Machin DL : 0: 仿真1：首先把网络温度参数T固定在100，按工作规则共进行1000次状态更新,把这1000次状态转移中网络中的各个状态出现的次数Si（i＝1，2，…，16）记录下来按下式计算各个状态出现的实际频率： Pi=Si/∑i=1,NSi=Si/M 同时按照Bo1tzmann分布计算网络各个状态出现概率的理论值： Q（Ei）=（1/Z）exp（-Ei/T）仿真2：实施降温方案，重新计算采用快速降温方案：T（t）= T0/（1+t） T从1000降到0.01，按工作规则更新网络状态当T=0.01时结束降温，再让T保持在0.01进行1000次状态转移，比较两种概率-a simulation : First of all network parameters temperature T fixed at 100 and, according to the rules for a total of 1000 to update the state, this state of the 1000 network transfer of all states for the number of Si (i = 1, 2, ..., 16) all recorded determined by the formula state-of the actual frequency : Pi = Si / i = 1, NSi = Si / M in accordance with Bo1tzmann distributed computing network of states all probability the theoretical value : Q (Ei) = (1 / Z) exp (- Ei / T) Simulation 2 : implementation of cooling, re-using rapid cooling programs : T (t) = T0 / (1 t) T dropped to 0.01 from 1000 and, according to the rules updated network state when T = 0.01 at the end of cooling, let T at 0.01 for the 1000 state transfer, the probability of two more
Date : 2008-10-13 Size : 4.79kb User : 韵子