Description: 本程序时基于混沌理论和ELMAN神经网络的短期负荷预测，能取得很好的预测效果，直接使用该程序就能实现电力短期负荷预测，同样使用于其他类型的时间序列预测-the procedures based on chaos theory and neural networks ELMAN short-term load forecasts, can be achieved very good results forecast, the direct use of the procedure we will be able to realize short-term power load forecasting, the same used in other types of time series prediction Platform: |
Size: 1666 |
Author:sunyan |
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Description: 本程序时基于混沌理论和ELMAN神经网络的短期负荷预测，能取得很好的预测效果，直接使用该程序就能实现电力短期负荷预测，同样使用于其他类型的时间序列预测-the procedures based on chaos theory and neural networks ELMAN short-term load forecasts, can be achieved very good results forecast, the direct use of the procedure we will be able to realize short-term power load forecasting, the same used in other types of time series prediction Platform: |
Size: 1024 |
Author:sunyan |
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Description: 混沌时间序列分析与预测工具箱 Version1.0
(Chaotic Time Series Analysis and Prediction Matlab Toolbox - version 1.0)
-chaotic time series analysis and forecasting toolbox Version1.0 (Chaotic Time Series Analysis and Prediction of Matlab Toolbox- version 1.0) Platform: |
Size: 429056 |
Author:xujia |
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Description: 混沌时间序列工具箱，有常有的混沌时间序列预测的方法和混沌判别方法-Chaotic time series toolbox, has often chaotic time series prediction methods and Chaos Method Platform: |
Size: 413696 |
Author:华清 |
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Description: 混沌工具箱
C-C方法计算时间延迟和嵌入维数
混沌时间序列预测-Chaos Toolbox CC method to calculate time delay and embedding dimension of chaotic time series prediction Platform: |
Size: 14336 |
Author:潘水洋 |
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Description: SOM-BASED TIME SERIES PREDICTION
Training Time Series
Testing Time Series
Local Linear Mapping (LLM)
Vector-Quantized Temporal Associative Memory (VQTAM)
Global RBF (GRBF, download here) and Local RBF (KRBF)
Local AR predictors using data vectors (LARD)
Local AR predictors using weigth vectors (LARW) Platform: |
Size: 39936 |
Author:Carlos Wilson |
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Description: 混沌时间序列预测程序与文档
包括CC方法、GP方法、Lyapunov指数预测等-Chaotic time series prediction method procedures and documentation, including CC, GP method, Lyapunov index prediction Platform: |
Size: 685056 |
Author: |
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Description: 混沌时间序列 吸引子 分形 程序 工具包
混沌时间序列分析与预测工具箱 Version1.2
chaotic time series analysis and prediction matlab toolbox - version 1.2
-Chaotic attractor of fractal time series Toolkit chaotic time series analysis and prediction toolbox Version1.2 chaotic time series analysis and prediction matlab toolbox- version 1.2 Platform: |
Size: 451584 |
Author:李阳 |
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Description: 基于混沌理论的时间序列的系统多步预测函数-Based on the theory of chaos time series prediction function of the system Platform: |
Size: 227328 |
Author:王菲茵 |
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Description: 该文章从混沌和分形的关系出发，基于奇异吸引子的分形结构和时间序列的自仿射特性，提出了一种混沌时间序列的预测方法。采用迭代函数系统跟踪混沌的局部运动轨迹，由此确定统计意义上放射性能最优的时间序列段，并分局吸引子定力和拼贴定理建立预测模型。-This article from the chaos and fractal relationship starting, based on the characteristics of self-affine fractal structure and time sequence of strange attractor, a chaotic time series prediction method. Iterated function systems chaotic local trajectory tracking radioactive energy optimal time sequence segment, thereby determining the statistical significance and branch attractor anyone, and collage theorem to establish prediction model. Platform: |
Size: 707584 |
Author:诸葛亮 |
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Description: 混沌时间序列的Volterra级数多步预测研究，混沌理论认为在混沌系统中，初始条件的十分微小的变化经过不断放大，对其未来状态会造成极其巨大的差别。 -Volterra series of chaotic time series multi-step prediction, chaos theory is that in the chaotic system, the initial conditions of very small changes through continuous zoom, its future status will cause a very huge difference. Platform: |
Size: 2737152 |
Author:杜金 |
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Description: 吕金虎《 混沌时间序列分析及其应用》，对混沌和预测相关的有很大帮助-Lu Jinhu "chaotic time series analysis and its applications," chaos and prediction of great help related Platform: |
Size: 4165632 |
Author:张泽宇 |
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Description: 质量非常好的一篇博士论文。冲击破坏过程十分复杂，很难建立精确的数学模型，但目前具有冲击危险性的矿井都采取了多种监测措施，可以获得大量冲击地压监测数据。本论文以获取的冲击地压监测历史时间序列数据为基础，在相空间重构出的动力学空间中分析其混沌特性，基于混沌预测理论，采用智能算法对多个冲击地压监测变量进行预测研究，并采用集成分类方法对冲击危险性进行识别预测研究。-Quality is very good a doctoral dissertation. The impact of the destruction process is very complex, it is difficult to establish a precise mathematical model, but with the impact of hazardous mine have taken a variety of measures to monitor, you can get a lot of bumping monitoring data. In this paper, the impact of pressure to get the monitoring of historical time series data, analyze its characteristics in phase space reconstruction of chaotic dynamics of the space prediction based on chaos theory, the use of intelligent algorithms to press multiple variables to predict the impact of monitoring Research and integrated classification method to identify the impact of risk prediction. Platform: |
Size: 2359296 |
Author:李其龙 |
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Description: 韩敏版混沌时间序列理论与预测，内容详实，不错的一本好书。-Han Min version of chaos theory and time series forecasting, informative, good a good book. Platform: |
Size: 5186560 |
Author:李云 |
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Description: 用matlab实现利用统计混沌方法解决非线性系统时间序列预测的问题-Matlab to make use of statistical chaos method to solve the problem of nonlinear system time series prediction Platform: |
Size: 27648 |
Author:EZ!2625 |
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Description: 用matlab实现利用统计混沌方法解决非线性系统时间序列预测的问题-Matlab to make use of statistical chaos method to solve the problem of nonlinear system time series prediction Platform: |
Size: 18432 |
Author:oriehajd |
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Description: 用matlab实现利用统计混沌方法解决非线性系统时间序列预测的问题(Matlab to make use of statistical chaos method to solve the problem of nonlinear system time series prediction) Platform: |
Size: 17408 |
Author:VYFhrwny%267188
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Description: 应用小波变换和混沌理论相结合的方法对股票市场进行预测 ,即先对股指时序进行小波分解 ,然后对分解得到的高、低频部分分别进行混沌预测 ,再将预测的结果进行小波重构 ,得到原时序的预测结果。 在此基础上应用小波和混沌理论提出进一步提高预测精度的方法 ,即通过对高频部分再进行小分解、混沌预测和小波重构而使高频部分的预测精度得以提高 ,进而提高原始时序的预测精度。(The method of combining wavelet transform and chaos theory is used to forecast the stock market, that is, first to perform wavelet decomposition on the time series of the stock index, and then to perform chaotic prediction on the high and low frequency parts obtained by the decomposition, and then to reconstruct the prediction result by wavelet. The prediction result of the original time series. On this basis, wavelet and chaos theory is used to propose a method for further improving the prediction accuracy, that is, the high-frequency portion is further subjected to wavelet decomposition, chaotic prediction, and wavelet reconstruction to improve the prediction accuracy of the high-frequency portion, thereby improving the original time series. Prediction accuracy.) Platform: |
Size: 235520 |
Author:南嘉 |
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Search - time series* chaos* prediction