time series forecast造句
例句與造句
- Financial time series forecasting based on nonlinear tracking - differentiator
微分器的金融時(shí)間序列預(yù)測(cè) - The maximum lyapunov index is a common used method in the chaos time series forecast
最大lyapunov指數(shù)預(yù)測(cè)是混沌時(shí)間序列預(yù)測(cè)中一種常用方法。 - Ann based on trend identify and the application in hydrological time series forecast
基于趨勢(shì)辨識(shí)理論的神經(jīng)網(wǎng)絡(luò)及其在水文時(shí)間序列預(yù)報(bào)中的應(yīng)用 - Chaotic time series forecasting using online least squares support vector machine regression
基于在線最小二乘支持向量機(jī)回歸的混沌時(shí)間序列預(yù)測(cè) - The method of time series forecast is one of the important parts of research on science , economy , engineering , and so on
時(shí)間序列預(yù)測(cè)方法是科學(xué)、經(jīng)濟(jì)、工程等領(lǐng)域的研究重點(diǎn)之一。 - It's difficult to find time series forecast in a sentence. 用time series forecast造句挺難的
- Integrating kernel principal component analysis with least squares support vector machines for time series forecasting problems
基于核主成分分析與最小二乘支持向量機(jī)結(jié)合處理時(shí)間序列預(yù)測(cè)問(wèn)題 - This paper discusses the structure of time series forecast system , algorithm design and analytic method of results
文中簡(jiǎn)要介紹電信行業(yè)時(shí)間序列預(yù)測(cè)系統(tǒng)的結(jié)構(gòu)設(shè)計(jì)，算法設(shè)計(jì)以及預(yù)測(cè)結(jié)果的分析方法。 - Mackey - glass ( mg ) chaotic time series is one of benchmark problems in nonlinear time series forecast , which is representative
Mackey - glass ( mg )混沌時(shí)間序列具有非線性特性,是時(shí)間序列預(yù)測(cè)問(wèn)題中的基準(zhǔn)問(wèn)題之一,具有代表性。 - The research results show that neural networks have good performance in prediction , which providing an effective approach for highly nonlinear and dynamic time series forecasting
研究結(jié)果表明，神經(jīng)網(wǎng)絡(luò)用于預(yù)測(cè)效果好，為一類高度非線性動(dòng)態(tài)關(guān)系的時(shí)間序列預(yù)測(cè)提供了一條有效途徑。 - Time series forecasting models of food - grain consumption per capita in china were scanned and selected by using spss , and were built based on the correlative relationship between quantity of consumption and time
利用糧食消費(fèi)量與時(shí)間之間的相關(guān)關(guān)系，采用spss程序包進(jìn)行篩選，建立我國(guó)人均食用糧食消費(fèi)的時(shí)序預(yù)測(cè)模型。 - Time series forecast is a important research aspect in forecast fieldo research on forecast of nonlinear time series takes on important practical significance because practical system is mostly nonlinear
時(shí)間序列預(yù)測(cè)是預(yù)測(cè)領(lǐng)域內(nèi)的一個(gè)重要研究方向。因?yàn)楝F(xiàn)實(shí)系統(tǒng)大多是非線性的，使得非線性時(shí)間序列預(yù)測(cè)具有重要的現(xiàn)實(shí)意義。 - It is difficult for traditional method of time series forecast to predict the nonlinear system . the neural network has good nonlinear characteristic , and has offered a new approach for time series forecast
經(jīng)典的時(shí)間序列預(yù)測(cè)方法在用于非線性系統(tǒng)預(yù)測(cè)時(shí)有一定的困難,而神經(jīng)網(wǎng)絡(luò)具有較好的非線性特性,為時(shí)間序列預(yù)測(cè)開辟了新的途徑。 - The main research contents include : 1 、 this paper constructs the mixed collaborative sale forecasting model based on cpfr via integrating time series forecasting , multivariate regression and ridge regression . in addition , the model takes sale information as explanation variable
具體研究?jī)?nèi)容包括: 1 、將時(shí)間序列預(yù)測(cè)、多元回歸、嶺回歸相結(jié)合,并將銷售信息作為銷售量的解釋變量,構(gòu)建了cpfr流程下的混合協(xié)同預(yù)測(cè)模型。 - Based on selective learning of data mining and analysis of characteristics of data or information in rock mechanics and engineering , some data mining algorithm models are applied to analysis problems of rock engineering and the research is combined with practical engineering projects . relevance analysis to slope rock rheological test , rock mass quality assessment of dam foundation rock mass and displacement time series forecasting analysis to underground opening are performed by using data mining technique in this paper
本文在較全面的探討現(xiàn)有數(shù)據(jù)挖掘技術(shù)以及分析了巖體工程有關(guān)數(shù)據(jù)和信息特點(diǎn)基礎(chǔ)上，結(jié)合具體工程問(wèn)題，基于數(shù)據(jù)挖掘技術(shù)進(jìn)行了邊坡巖體流變?cè)囼?yàn)成果的相關(guān)性分析、壩基巖體的巖體質(zhì)量評(píng)價(jià)分級(jí)研究和地下洞室監(jiān)測(cè)位移序列時(shí)序預(yù)測(cè)分析。 - Firstly , the forecast problem based on vendor managed inventory ( vmi , for short ) model is talked about . according to inventory demand changing with season and some random factors existing in actual problem , a new algorithm composed of a random time series forecast method and gm ( 1 , 1 ) is put forward , and a mathematic model is constructed to analyze history data . as a result , the precision of the requirement forecast is increased greatly
本文首先研究了供應(yīng)商管理庫(kù)存( vendormanagedinventory ,簡(jiǎn)稱vmi )模式下分布式庫(kù)存需求的預(yù)測(cè)方法,根據(jù)庫(kù)存需求數(shù)據(jù)具有季節(jié)性變化的特點(diǎn),并考慮到這一變化的不確定性,采用基于隨機(jī)時(shí)間序列和灰度預(yù)測(cè)的組合預(yù)測(cè)算法對(duì)問(wèn)題進(jìn)行建模,并在此基礎(chǔ)上進(jìn)行分析預(yù)測(cè),從而使數(shù)據(jù)擬合有很大程度的提高。
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