volume forecasting 中文意思是什麼

volume forecasting 解釋
流量預測
  • volume : n. 1. 卷,冊;書籍;【歷史】書卷,卷軸。2. 〈常 pl. 〉大塊,大量,許多。3. 體積;容積;分量,額;【物、樂】音量;強度,響度。
  • forecasting : (勞動力供求)預測
  1. Forecasting the downstream intersection traffic volume by bp neural network

    神經網路預測下游交叉口進口交通量
  2. Forecasting flight segment volume is important step and forecasting result is important basis in formulating flight scheduling

    航段運量預測是制定航班計劃的重要步驟,其預測結果是制定航班計劃的重要依據。
  3. First, the characteristic of flight segment volume is analyzed, existing model selection method is discussed, forecasting model selection method based on support vector machine is described

    首先,本文分析了航段運量特點,討論了現有模型選擇方法,在此基礎上闡明了基於支持向量機的航段運量預測模型選擇方法。
  4. Three kind of forecasting model and their application in the system of " air flight scheduling & optimizing management simulator " are presented and evaluated. the result indicates that the method has the good effect in model selection for forecasting of flight segment volume

    同時,針對「航班計劃及其性能優化管理」系統中的三種預測模型進行了實驗,結果表明該方法在航段運量預測模型選擇方面具有較好的效果。
  5. This thesis systematically analyzes the characteristic of flight segment volume and existing model selection method, and discusses theory and algorithm of support vector machine in details, makes research on model selection in forecasting of flight segment volume combined with support vector machine

    本文系統地分析了航段運量的特點及現有的模型選擇方法,詳細探討了支持向量機相關理論和演算法,結合支持向量機對航段運量預測模型選擇方法進行了深入研究。
  6. This paper firstly analyzed the character and setting forth of international dry and bulk cargo market, then according to the variety of cargo analyzed the transport volume on different routs. on the basis of them forecasting the transport volume of international bulk cargo, trying to find the the orderliness of international dry and bulk cargos market ; the following part study the scale and configuration of international dry and bulk fleet, and analyzed the actuality of cosbulk compare with it

    本文首先分析了國際干散貨航運市場的基本特徵和基本規律,並進一步根據不同的貨種、貨類分析了不同航線上運量狀況;並在此基礎上,對未來幾年的國際干散貨運量進行了預測,力圖尋找干散貨航運市場的發展趨勢;接著又研究了國際干散貨船隊的規模、結構等特徵,並將中散船隊現狀與之進行對照分析。
  7. Market conditions are changing fast. uncertainties in forecasting port cargo volume mean that timely knowledge is critical to successful port planning

    港口貨運量的預測存在很多不明朗因素,因此在進行港口規劃時,掌握市場變化的資訊是成功的關鍵。
  8. In the paper, the following main factors are studied, such as developing the expert knowledge - base based on the special knowledge of the explosive demolition of frame building, designing the object - oriented expert system of the explosive demolition of frame building, developing the neural network training example base based on projects, developing the forecasting mode of blast effects with matlab 6. 1, developing the expert system of explosive demolition of frame building with visual b 6. 0, carrying out the connection of the expert system and forecast mode. the system consisted of eleven functional modules, such as the input of initial parameters module, the choice of the blasting method module, the choice of blast mode module, the design of blasting parameters module, the design of charge module, the verifying blasting safety module, the calculating safety of tumble module, the design of detonating net module, the blast effects forecasting module and the calculating volume module

    本文的研究內容有:以框架結構樓房拆除爆破領域的專業知識為基礎製作專家系統知識庫;設計一般面向對象的框架結構樓房爆破拆除設計的專家系統;搜集相關爆破工程實例製作用於爆堆效果預測神經網路訓練的樣本數據庫;選取適當的輸入輸出因素,用matlav6 . 1構建爆破效果預測神經網路模型;用vb6 . 0編程開發出框架結構樓房拆除爆破專家系統,並實現爆破效果預測神經網路模型和專家系統的鏈接。該系統由初始參數輸入、倒塌方法選取、倒塌方案確定、孔網參數設計、缺口形狀及參數、爆破安全校核、傾倒安全校核、爆破網路、爆破效果預測、工程量計算、計算設計說明書等十一大功能模塊組成。
  9. ( 6 ) it studies the time serial neural network forecast model and discusses how to determine the dimension of input data and how to smooth the unsteady time serial data. also this paper uses the time serial neural network model to forecast the volume of freight of shenzhen airport air logistics park. finally, this paper attains higher accuracy in using the forecasting model and gets a good forecast effect

    ( 6 )對基於時間序列的神經網路預測模型進行了研究,並研究了輸入維數的確定及非平穩時間序列如何平穩化的問題,並利用時間序列神經網路預武漢理工大學博士學位論文測模型進行深圳航空物流園區的貨流量的預測,從而提高了預測模型的精度。
  10. The connotation, limit and characteristics of pcee is discussed. based on that, it is argued that two kinds of maneuver and model of pcee traffic volume forecasting, the calculating of pcee capacity and the referenced criterion and dimension used for carving out pcee service level are advanced

    首先闡明了出入口道路的內涵、外延及特徵,在此基礎上論述了出入口道路交通量預測的兩類模型和方法,對出入口道路通行能力進行確定,研究出入口道路服務水平劃分的依據與標準。
  11. After analyzing the data on railway freight volume of recent years, the authors establish the railway freight volume forecasting model by use of grey theory

    摘要通過對近年全國鐵路貨運量的統計數據進行分析,運用灰色理論建立了鐵路貨運量預測模型。
  12. This part concentrates on the analysis of the demand and price index in the container shipping market by means of forecasting and decision technology, and also a fitting forecasting analysis of the container transportation volume in shanghai port and china export container freight index ( cecfi ), etc, by means of the multi - elemental dynamic related coefficient and the rbf neural network

    第二部分,運用預測決策方法對集裝箱航運市場的主要供需和運價指數進行研究分析,利用多因素動態相關系數法和rbf (徑向基)神經網路預測法等技術分別對上海港集裝箱運量和中國出口集裝箱運價指數等進行擬合預測分析。
  13. Contrasting the changes in the total sales volume, the annual growth, the chain rate of increase, and forecasting the sales volume in 2006 and the uptrend, it ' s obvious that there was prominent improvement in 2003 - 2005 after adjusting and would have a confident prospect, though bad in 2002

    文章通過對岳陽正泰2002 - 2005年營銷業績變化分析,比較年增長率、環比增長率等一系列指標並預測岳陽正泰2006年的銷售量及以後趨勢后發現重組后的營銷業績雖在2002年不理想,但經過調整后2003 - 2005年有了顯著的提高,並且前景較好。
  14. 5 ). the traffic volume forecasting is carried out on the background of a highway. it indicates that it is feasible using flexibility modulus method in forecasting trip production and generation, the convergence is quickly using fratar method in forecasting origin and destination table and it is convenience using multiroute method in forecasting assignment

    經分析,在進行交通量發生吸引量預測時,採用彈性系數法較為可行;進行趨勢交通量分佈預測時,採用費雷特法進行分析計算收斂較快;進行交通量分配預測時,採用多路徑交通分配比較可靠。
  15. Optimization model for forecasting district transportation volume

    交通量預測的優化模型
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