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ai_predict_analysis / 工业蒸汽量预测

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MulanPSL-2.0

**# 工业蒸汽量预测

介绍

根据脱敏后的锅炉传感器采集的数据,根据锅炉的工况预测产生的蒸汽量。

软件架构

环境Tensorflow2.0+Python3.8

使用说明

  1. zhengqi_train.txt是训练集数据,此训练集数据共有2888个样本,数据中有V0~V37共38个特征变量,变量类型都为数值型,所有数据特征没有缺失值。数据字段采用了脱敏处理,删除了特征数据的具体含义。target字段为标签变量。
  2. zhengqi_test.txt是测试集数据,数据共有1925个样本,数据中同样包含V0~V37共38个特征变量,变量类型都为数值型。测试集中没有target字段,需要预测。
  3. 训练模型包含多元线性回归模型、k近邻回归模型、随机森林回归模型、LGB回归模型。主要使用随机森林回归模型(对应RandomForestRegressor.py程序)、LGB回归模型(对应LGB.py程序)。code程序中主要包含对数据预处理过程(比如:通过KDE分布图删除训练集和测试集中分布不一致的特征变量、用过PCA方法去除数据的多重共线性,并进行降维处理)。
  4. 使用者可以下载训练集和测试集,更换回归预测模型,如逻辑回归模型、决策树回归模型、SVR回归模型等,为了方便学习,我同时上传了部分机器学习算法PDF文件。

**

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简介

根据脱敏后的锅炉传感器采集的数据,根据锅炉的工况预测产生的蒸汽量。 展开 收起
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