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zishiyingguolvfa
- 自适应过滤法是根据一组给定的权数对时间数列的历史观察值进行加权平均计算一个预测值，然后根据预测误差调整权数以减少误差，这样反复进行直至找出一组“最佳”权数，使误差减少到最低限度，再利用最佳权数进行加权平均预测。-Adaptive filtering method is based on the number of a given set of rights to compute a weighted average of the predicted value of historical tim
guanliandu
- 是计算关联度的软件，调试过，可以执行。对学习时间序列预测很有意义-Is to calculate correlation software, debugging, you can perform. Time series prediction is very meaningful to learn
multiverso-master
- Multiverso is a parameter server based framework for training machine learning models on big data with numbers of machines. It is currently a standard C++ library and provides a series of friendly programming interfaces. With such easy-to-use APIs, m
Keywords
- 通过TF-IDF的方式找到一系列文章的关键词-find the keywords of a series of articles
P1-s2.0-S0957417410001107-main
- Business cycle predictions face various sources of uncertainty and imprecision. The uncertainty is usually linguistically determined by the beliefs of decision makers. Thus, the fuzzy set theory is ideally suited to depict vague and uncertain feature
bp
- 可以采用神经网络对时间序列进行预测，具有较好的效果-The neural network can be used to predict the time series, which has better effect.
hctsa-master
- matlab，时间序列分析，分类，数据挖掘，聚类-time series classification
SVM
- 支持向量机神经网络的信息粒化时序回归预测代码案列，代码易于修改-Support Vector Machines Neural Network Information granulated series regression predictive code text column, easy to modify the code
holt_winters
- holt-winters 三次指数平滑算法,时间序列预测算法，带测试数据及Demo-Triple Order Exponential Smoothing, Holt-Winters algorithm, time series prediction algorithm with test data and Demo
clean
- 用于量化挖掘股票投资中，股票时间价格Tick序列数据的单位转换与数据清洗-Stock investment for quantifying mining, stock price time series data Tick unit conversion and data cleansing
Wind-Speed-Combined-Prediction
- 针对风电场短期风速的预测提出一种基于小波变换的组合预测方法。首先利用Mallat 算法对短期风速时间序列进行db3 小波三层分解与重构，得到短期风速时间序列的近似分量和细节分量。针对近似分量和细节分量的不同特性，对近似分量利用粒子群算法优化的最小二乘支持向量机进行预测，对细节分量利用自回归求和滑动平均模型进行预测。最后各预测模型预测值组合叠加得到最终的短期风速预测值。仿真结果表明该方法具有较高的预测准确度。-In order to improve short-term wind speed pr
OpenTSTOOL
- 时间序列处理工具箱，大量丰富的处理函数，可供选择。(Time series processing toolbox, a large number of processing functions, available for selection.)
数据挖掘pro
- 本项目的具体问题是关于时间序列数据趋势预测。具体的应用场景是电子商务。现在要求您对118天到146天的每天100个关键产品进行销售量预测。(In this project, you are asked to study the general topic of time-series data mining, and specifically for time-series data trend prediction.)
arima
- 时间序列法，通过过去数据来建立相应模型来预测未来数据(Time series, using past data to establish corresponding models to predict future data)
DTW
- 时间序列的动态时间规整python算法，用于对不同长度的两个时间序列进行等长处理(Time-series dynamic time warping python algorithm for equal length processing of two time sequences of different lengths.)
多重分形去趋势波动分析模型
- 用于不同时间序列的重分形交叉相关性分析的多重分形去趋势交叉相关模型，整合了多重分形去趋势交叉相关系数于其中(A multifractal de-trend cross-correlation model for multifractal cross-correlation analysis of different time series is proposed, in which multifractal de-trend cross-correlation coefficients are
Chaotic Systems Toolbox
- 这个工具箱包含一组函数，可以用来模拟一些最著名的混沌系统，其为相空间重构、模拟时间序列的线性特性、尺寸和噪声估计以及降噪提供了额外的功能。(This toolbox contains a set of functions which can be used to simulate some of the most known chaotic systems, such as: - The Henon map - The Ikeda map - The Logistic map - The
Python for Data Analysis
- 利用python进行数据分析，英文书籍，从pandas库的数据分析工具开始利用高性能工具对数据进行加载、清理、转换、合并以及重塑；利用matpIotlib创建散点图以及静态或交互式的可视化结果；利用pandas的groupby功能对数据集进行切片、切块和汇总操作；处理各种各样的时间序列数据。(Starting from the data analysis tools of pandas database, high performance tools are used to load, clea
stock-prediction-master
- SARIMA时序预测代码示例。无论我们是想预测金融市场的趋势还是用电量，时间都是我们模型中必须考虑的一个重要因素。例如，预测一天中什么时候会出现用电高峰是很有趣的，可以以此为依据调整电价或发电量。(SARIMA time series prediction code example)