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wavePredict
- 随着新的数学工具小波分析的实用化为基于NN负荷预测模型性能的改善提供了理论依据对于电力系统负荷非线性时间序列的辨识在预测方法研究中应给予重视在本文所用的基于小波原理和NN融合的预测原理是具有强的非线性时间序列的辩能力由研究和仿真表明它能有效提高预测的精度-with new mathematical tools wavelet analysis based on NN into practical load forecasting model to improve the performance
zhb
- 基于云模型的短期电价预测。一种基于云模型的时间序列预测的新型算法。-Based on cloud model of short-term price forecasting. A cloud-based model of the new algorithm for time series prediction.
yefu_tuoluo_jianmofenxi
- 采用时间序列分析理论,利用实际测量的数据,建立了液浮陀螺随机漂移的ARMA模型。最终,为便于将模型应用于卡尔曼滤波器中,本文给出了一种实际可行的液浮陀螺漂移模型 -Using time series analysis theory, the use of actual measurement data, the establishment of a liquid floating gyro random drift of the ARMA model. Ultimately, in orde
tuoluo_piaoyi_feipingwenshijian
- 将非平稳时间序列的状态空间建模方法用于陀螺过渡过程的分析.基于平滑先验约束的概念，使用卡尔曼滤波和赤池的AIC方法拟合全局模型，得到陀螺漂移模型的若干数值结果并用于陀螺系统分析.由于观测序列的趋势项、不规则分量可同时建模，因此比分别建模在统计上更加准确有效.-Will be non-stationary time series state space modeling method for the analysis of the transition process gyro. Priori s
chuanyong_tuoluo_wuchamoxing
- 在对船用陀螺漂移数据建立时间序列模型的基础上，采用卡尔曼滤波算法对捷联陀螺漂移数 据进行了处理，以提高陀螺静态漂移误差系数的估计精度，并把得到的陀螺漂移误差模型实时补偿到捷联系统中，得到了满意的效果。-Marine gyro drift in the data time series model based on the Kalman filter algorithm using inertial gyro drift data were processed to enhance the g
Patterns_for_timetriggered_embedded_systems
- 文件中包含时间触发嵌入式系统设计模式 8051系列微控制器开发可靠应用的英文原版，中文翻译版和C++实例。本书前所未有地提出一整套软件模式，为开发嵌入式软件系统提供帮助。书中讨论了基于广为使用的8051系列微控制器进行设计并应用软件 的方法。此外还重点关注了其可靠性。本书从简单系列复杂系统。列举了大量详尽的的实例。-File contains a time-triggered embedded system design 8051 series micro-controller developm
theuseofmatlabinthetimeseries
- 介绍使用MATLAB软件对时间序列进行编程，里面有AR模型的建立方法-Describes the time series using MATLAB software programming, which has AR model method
Time-series-analysis-model
- 对个数较多的数据运用灰色系统模型时， 本论文提出了一种新的灰色系统建模方法，即分离建模方法。 -Number of more data, the gray system model, proposed in this paper a new modeling method of gray system, namely, separation of the modeling approach.
8
- 基于模型的时间序列数据挖掘---聚类和预测相关问题研究 ---- Clustering and forecasting issues related to model-based time-series data mining
fractal-predict-pdf
- 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 ti
markovchainmodel
- Markov Chain model for regime switching time series
THE-TIME-SERIES
- 该文介绍了时间序列经典方法，ARMA,ARIMA,AR模型用于解决各种平稳预测问题，并且附上了相应的程序，方便读者运用-This paper introduces the classical time series methods, ARMA, ARIMA, AR model is used to solve a variety of stationary prediction problem, and attach the appropriate procedures to facilitat
grey
- to implement the grey forecasting model for time series prediction
ARFIMA_SIM
- The code performs the simulation of time series with autoregressive fractionally integrated moving average (ARFIMA) models that generalize ARIMA (autoregressive integrated moving average) and ARMA autoregressive moving average models. ARFIMA models a
short-term-electrical-load
- 电力负荷预测，多变量时间序列线性回归预测方法-the research of local linear model of short-term electrical load on multivariate time series
Water-Supply-System-
- 本文分别采用基于时间序列分析的方法和人工神经网络方法建立了天级需水量预报模型-Based on time series analysis method and artificial neural network method, the model of water demand forecasting is established in this paper.