资源列表
斯坦福大学-深度学习基础教程
- 斯坦福大学的深度学习，基础教程。ps:要求先学完吴恩达的机器学习基础再来看，不然看不懂(Depth study of Stanford University, basic course. Ps: needs to learn the basis of Wu Enda's machine learning first, or you can't understand it.)
预测
- BP神经网络模型预测的Python代码实现，测试有效(BP neural network model forecast Python code implementation, test effectiveness)
遗传算法-电源规划
- 遗传算法-计算电源规划用，将低碳要素引入电源规划决策之中，在充分考虑传统电力系统安全、经济运行要求的前提下，建立了含碳捕集电厂的低碳电源规划模型(The ycsf genetic algorithm is used to calculate the power supply plan. The low-carbon elements are introduced into the power planning decision-making. Under the premise of fully
4人工势场法路径规划程序
- 多机器人系统的群集编队控制理论仿真程序，采用人工势场法，使多个机器人在向目标点运动过程中能保持队形，并能适应环境约束(The simulation program of cluster formation control for multi robot system is based on artificial potential field method, which enables multiple robots to maintain formation in the process of
人工智能：人工智能选股之朴素贝叶斯模型
- 本报告对 朴素贝叶斯模型及线性判别分析、二次判别分析 进行系统测试 “生成模型”是机器学习中监督学习方法的一类。与“判别模型”学习决 策函数和条件概率不同，生成模型主要学习的是联合概率分布??(??,??)。本 文中，我们从朴素贝叶斯算法入手，分析比较了几种常见的生成模型（包 括线性判别分析和二次判别分析）应用于多因子选股的异同，希望对本领 域的投资者产生有实用意义的参考价值。(This report gives a systematic test of naive Bayesian
PSO_ELM
- 运用粒子群算法对ELM算法进行优化，以达到算法的最优性。(Particle swarm optimization (PSO) is applied to optimize the ELM algorithm to achieve the optimality of the algorithm.)
ART2py-master
- ART2（自适应共振理论）的python实现(Python implementation of ART2 (Adaptive Resonance Theory))
bp和maltab的车牌识别
- 实现了灰度处理，锐化，边缘检测，神经网络(Grayscale processing, sharpening, edge detection, neural network)
LSTM
- LSTM对价格的预测 利用最新的神经网络 希望大家能够喜欢(29/5000 The LSTM's prediction of prices USES the latest neural networks to please everyone)
DTLZ_PF_Generator
- DTLZ测试函数生成真实Pareto前端(DTLZ test function to generate true Pareto front)
KOSELM-standalone
- kerne online sequential Extreme learning machine
convLSTM_minimum-master
- 卷积长短期机器模型用于预测空间上与时间上的值，是基于LSTM模型的改进算法(Convolutional long-term and short-term machine model is an improved algorithm based on LSTM model for predicting spatial and temporal values.)