Simulated ANNealing 統計算法
上傳時間： 2016-08-07
上傳用戶：xymbian
通用模擬退火優化算法 General simulated ANNealing algorithm 模擬退火優化算法能過較大限度的避免局部最優解
標簽： simulated ANNealing algorithm General
上傳時間： 2014-07-24
上傳用戶：tianyi223
Simulated ANNealing Impelemtation in MATLAB
標簽： Impelemtation Simulated ANNealing MATLAB
上傳時間： 2013-11-29
上傳用戶：Zxcvbnm
Simulated ANNealing (SA) for the Symmetric Euclidean TSP
標簽： Simulated Euclidean ANNealing Symmetric
上傳時間： 2014-11-27
上傳用戶：極客
a matlab code for solving TSP using simulated ANNealing (SA)
標簽： ANNealing simulated solving matlab
上傳時間： 2017-06-18
上傳用戶：tyler
Simulated ANNealing SA Hill Climbing HC Local Beam Search LBS Genetic Algorithm GA
標簽： Simulated ANNealing Algorithm Climbing
上傳時間： 2014-01-01
上傳用戶：wfeel
The BYY ANNealing learning algorithm for Gaussian mixture with automated model selection
標簽： ANNealing algorithm automated selection
上傳時間： 2014-09-05
上傳用戶：小碼農lz
For the incomplete methods, we kept the representation of the queens by a table and the method of calculation to determine if two queens are in conflict, which is much faster for this kind of problems than the representation by a matrix. heuristics: descent. Tests: 100 queens in less than 1 second and 67 iterations. 500 queens in 1 second and 257 iterations. 1000 queens in 11 seconds and 492 iterations. heuristics: Simulated ANNealing. Tests: 100 queens in less than 1 second and 47 iterations. 500 queens in 5 seconds and 243 iterations. 1000 queens in 13 seconds and 497 iterations. heuristics: based on Simulated ANNealing. Tests: 100 queens in less than 1 second and 60 iterations. 500 queens in 1 second and 224 iterations. 1000 queens in 5 seconds and 459 iterations. 10 000 queens in 20 minutes 30 seconds and 4885 iterations.
標簽： the representation incomplete methods
上傳時間： 2015-05-05
上傳用戶：1159797854
使用matlab編寫.一個模擬退火算法的程序，實現了tsp問題的求解-a simulated ANNealing procedures, the use of Matlab prepared.
上傳時間： 2013-12-24
上傳用戶：erkuizhang
The package includes 3 Matlab-interfaces to the c-code: 1. inference.m An interface to the full inference package, includes several methods for approximate inference: Loopy Belief Propagation, Generalized Belief Propagation, Mean-Field approximation, and 4 monte-carlo sampling methods (Metropolis, Gibbs, Wolff, Swendsen-Wang). Use "help inference" from Matlab to see all options for usage. 2. gbp_preprocess.m and gbp.m These 2 interfaces split Generalized Belief Propagation into the pre-process stage (gbp_preprocess.m) and the inference stage (gbp.m), so the user may use only one of them, or changing some parameters in between. Use "help gbp_preprocess" and "help gbp" from Matlab. 3. simulatedANNealing.m An interface to the simulated-ANNealing c-code. This code uses Metropolis sampling method, the same one used for inference. Use "help simulatedANNealing" from Matlab.
標簽： Matlab-interfaces inference interface the
上傳時間： 2016-08-27
上傳用戶：gxrui1991
