资源列表
deepgaze
- 新的人脸识别调用库，包含中众多人脸的算法，python编程完成，主要涉及人脸姿态估计（图片和视频），人脸表情估计，人脸皮肤检测等等数十种。
power_dstatcom_pwmfinal
- The Wind Farm (DFIG detailed model demo of the Distributed Resources application library does not simulatethe demo that is missing. This file is normally d at the simulation start in order to define an initial state vector that starts the model in st
Intelligence-optimization-codes
- 智能优化算法汇总C语言大礼包 粒子群算法程序，是一种智能优化算法，1995年提出；-PSO algorithm
PSOtool
- 此为微粒群优化算法PSO工具箱，里面还有一些实例-This is the Particle Swarm Optimization PSO toolbox, along with some examples
DGPSO.rar
- 用于求解约束优化问题的算法，算法为差分进化/遗传算法/微粒群算法的融合。对于“[7] T. P. Runarsson and X. Yao, Stochastic ranking for constrained evolutionary optimization, IEEE Trans. Evol. Comput., vol. 4, no. 3, pp. 284-294, Sep. 2000”中给出的13个标准测试函数，均能得到问题最优解。如有任何疑问，请于http://2shi.phphube
PSO-noncon
- 粒子群算法，可以计算含非线性不等式约束和等式约束的优化问题。-PSO algorithm can be calculated with nonlinear inequality constrained optimization problems and equality constraints.
Cooperations_in_PSO_C
- 协同微粒群算法，期中举例了几种微粒群社会学习模型，We call these ve mechanisms, respectively, Reciprocity, Vicinity, Kin, Reputation, and Anybody.-Example several particle swarm cooperative particle swarm optimization, mid-term social learning model, We call these ve mecha
9grid
- 该程序在C++环境下实现，解决了人工智能中的经典的难题九宫问题。-This process is running at the C++ circumstance ,and accomplishing the classical problem ,9 grid problem.
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
梯度下降法 回溯直线搜索 python代码
- 梯度下降法 回溯直线搜索 python代码 包含回溯直线搜索，以及初始值相同时不同alpha,beta值对下降速度的影响测试 用jupyter notebook打开
hive1-2
- Ants performing 3 actions: searching ore , mining ore , returning ore basic Artificial Neurological Network working the learning proces to pick their state through Genetic Programming 人工智能中的蚁群算法
SVM-wine
- SVM神经网络的数据分类预测-葡萄酒种类识别-SVM neural network data classification forecast- wine species identification