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NEA
- 针对现有遗传算法在多维非线性优选方面的不足，本文提出了一种基于小生境进化算法（NEA）的非线性优选模型，探讨了NEA算法的参数选择原则。通过大量仿真和比较，表明算法在复杂非线性优选中具有快速、高效、鲁棒性强的特点，并能在全局范围内有效搜索所有最优解。 -against existing genetic algorithms in three-dimensional nonlinear optimization for the shortage, the paper presents a ni
biome-0.0.4.tar
- Biome是一个c++库，它的目的是个人_基于代理的模拟器（象 Swarm 或EcoSim）。它试图尽可能达到高效并且同时有好的设计-PROJECT is a c library, it is aimed at individual _ Agent-based simulator (like Swarm or EcoSim). It seeks to achieve efficient as possible while it is good design
模拟退火法计算最短路径
- 用模拟退火法高效的计算图论中哈密顿贿赂的最短路径-simulated annealing method of calculating efficient graph theory Hamiltonian bribery Shortest Path
libsvm-2.81
- Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It can solve C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic
遗传算法算例
- 文中详细介绍了函数优化（有无约束均可）、组合优化算法的原理和源程序，算法效率极高，欢迎下载。附件有更多的遗传算法算例，共研究算法用。 -paper describes in detail the function optimization (there may be bound), combinatorial optimization algorithms and the principle source, the algorithm very efficient and welcome to
apriori-rules
- 关联规则挖掘，一种改进了的APRIORI算法，效率较原有算法大大提高-mining association rules, an improved algorithm for the analysis and efficient than the original algorithm greatly enhanced
epc2d-update
- 一个投影聚类算法及其数据集生成源码。 参考文献： Eric K.K. Ng, A. Fu : Efficient algorithm for Projected Clustering,-a clustering algorithm and its projection data sets generated source. References : Eric K. K. Ng, A. Fu : Projected Efficient algorithm for clustering,
wdbsmyx
- 八数码游戏的不同实现方法! 1.八数码游戏与A*算法的结合! 本程序主要是给出一个A*算法的示例!效率并不高 2.广度算法 这个效率还可以的!-eight digital games of different methods! 1. Eight digital game with the A * algorithm combined! This process is essentially to an A * algorithm examples! two efficiency
ParticleSwarmOptimization
- 粒子群优化算法的源代码。以一个实例演示了基本粒子群算法的实现，是很高效的智能算法-PSO algorithm source code. An example to demonstrate the algorithm group of elementary particles, were very smart and efficient algorithm
RaoBlackwellisedParticleFilteringforDynamicConditi
- The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient stat
SA_TSP001
- 模拟退火算法解决TSP问题，该算法效率高，能很好地解决路径优化问题。-simulated annealing algorithm to solve TSP problem, the algorithm is highly efficient and very good path to solve optimization problems.
hhm
- 这是一个改进混合遗产算法的C语言源程序，将遗传算法与局部优化算法相混合，杨长避短，算法的效率有明显的提高-This is a mixed legacy algorithm to improve the C language source files, Genetic Algorithm and local optimization algorithms mixed, Yang longer hide weaknesses, efficient algorithm significantly im
Eight_Num_Fengart
- 本代码是为了应付人工智能的实验而编写的，写的潦草请不要介意。我又是通过这代码来“引玉”，相信看过我编写的黑白棋源代码的人应该知道“引玉”是什么意思。如果你有“玉”（什么更高效的算法能在更短的时间内求得结果，或者博弈方面的），就欢迎“砸”过来－－fengart@126.com，我会很感激！（A* 算法解决八数码问题我已经研究过了，不要砸这个来）在 赛扬D2.1G 的机器上测试，算法的解答时间不超过0.1秒。 最好优先搜索算法的解答时间一般在0.05秒左右。 里面还可以演示八数码问题的从初始态到目标
DGCL
- DGCL （An Efficient Density and Grid Based Clustering Algorithm for Large Spatial Database）的实现代码，费了很长时间才实现的-DGCL (An Efficient Density and Grid Based C. lustering Algorithm for Large Spatial Databas e) the realization of code, and a very long time to
TabuSearch
- 用禁忌搜索解决TSP问题，程序中使用对路径长度禁忌的方法，运行效率比较高。-Tabu search solution TSP, procedures for the use of the taboo path length, operating more efficient.
SimulateAnnealing
- 使用模拟退火算法解决TSP问题，该程序中的模拟退火没有采用复杂的运算，实现了一个比较简单但运行高效的算法-using simulated annealing algorithm to solve TSP, the process of simulated annealing without the use of complex arithmetic, achieve a relatively simple but efficient operation of the algorithm
icsiboost-0.3.tar
- Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the
Boosting-beta2
- AdaBoost is an efficient tool in machine learning. It can combine a series of weak learners into a strong learner. Besides pattern classification, it also can be applied into feature selection. This document explains the use of AdaBoost.
Energy_Aware_Hierarchical_Clustering_Algorithm_for
- 无线传感器网络中一种能量有效的分簇组网算法对研究无线传感器网络的研究者有用-Wireless sensor networks energy efficient clustering algorithm of network researchers useful for wireless sensor networks
power-efficient-fuzzy-algorithm
- power efficient clustering algorithm