包邮工业智能化知识基础

1数理统计基础..............................................................11.1概率论的基本概念...........................................11.2随机变量及其概率分布...................................71.3数字特征(含均值、期望、方差等).........151.4大数定律与中心极限定理.............................191.5统计量及其概率分布.....................................281.6参数估计.........................................................341.7假设检验.........................................................441.8参考文献......................................................... 502数据分析与建模........................................................512.1一元线性回归.................................................51l一元线性回归模型.................................52l*小二乘法.............................................52l回归方程的检验..................................... 56l宝钢案例.................................................612.2多元回归方法.................................................62l多元线性回归与*小二乘法.................62l回归方程的检验.....................................64l多项式回归.............................................70l非线性回归.............................................74l含虚拟(哑)变量的回归方法.............76l宝钢案例.................................................802.3时间序列分析.................................................80lAR以及ARMA模型............................82lMA模型................................................. 84l指数平滑模型.........................................882.4线性规划简介.................................................95l线性规划模型.........................................97l单纯形算法.............................................99l宝钢案例............................................... 1083人工智能基础..........................................................1093.1人工智能简介...............................................1093.2神经网络分析与建模...................................112l感知器与多层感知器...........................112lBP神经网络......................................... 115l后向传播算法.......................................120l深度学习概览.......................................122l宝钢案例...............................................1243.3现代启发式算法简介...................................124l遗传算法............................................... 124l群智能算法...........................................128l模拟退火算法.......................................130l宝钢案例...............................................1333.4机器学习简介...............................................133l聚类算法............................................... 134l分类算法...............................................143l决策树算法...........................................148lSVM算法.............................................1534数字仿真原理与应用..............................................1564.1基于MATLAB的仿真介绍与实例............1574.2基于Simulink的仿真与实例......................1584.3离散事件仿真原理.......................................159l基于工具软件的离散事件仿真与举例160l宝钢案例...............................................160参考文献...................................................................... 160附录一：教材Python代码........................................163例2.1代码...........................................................163例2.2代码...........................................................165例2.3代码........................................................... 166例2.4代码...........................................................168例2.5代码...........................................................169例2.6代码...........................................................171例3.1代码........................................................... 173例3.2代码(添加csv数据)...........................174例3.3代码...........................................................176例3.4代码...........................................................177例3.5代码...........................................................182附件2：宝钢案例......................................................184案例1锌耗预测(一元线性回归).................184案例2转炉钢液温度建模(一元线性回归).188案例3转炉钢液碳含量建模(多元回归方法)190案例4炼钢组炉问题(线性规划).................193案例5生产计划问题(线性规划).................195案例6转炉钢液碳含量建模(神经网络分析与建模) 197案例7炼钢组炉问题(现代启发式算法)198