本文選題：集卡到達時間 + GPS��； 參考：《大連海事大學(xué)》2015年碩士論文

【摘要】：隨著港口之間的競爭日益激烈,集裝箱碼頭越來越注重提高港口的服務(wù)水平。傳統(tǒng)的集中到達方式方便了碼頭布置裝卸作業(yè)調(diào)度計劃,但對貨主和集卡車隊安排運輸造成不便,并引發(fā)了集裝箱碼頭閘口排隊擁堵和港區(qū)及周邊交通壓力過大等問題。因此,一些碼頭采取出口箱隨機到達的策略,以提高自身競爭力和提供便利服務(wù)。在隨機到達模式下,集裝箱到達港口的時間和到達順序都是未知狀態(tài),出口箱集中到達模式的傳統(tǒng)集裝箱碼頭的“泊位計劃→配載計劃→堆場計劃→集裝箱入港計劃”順序式計劃調(diào)度方法將不再適用。由于碼頭無法確定特定航次出口箱每天的到達量和到達時段,無法事先預(yù)留整塊箱區(qū)集中堆放,只能根據(jù)集卡實際到達情況和堆場空閑情況進行分散堆放,這無疑對集裝箱碼頭堆場箱位分配帶來巨大的難度。因此,在隨機到達模式下,把握外部集卡到達規(guī)律及預(yù)測到達時間有利于提高集裝箱碼頭集卡調(diào)度的運營效率和服務(wù)水平。本文分別建立了集卡到達時間靜態(tài)和動態(tài)預(yù)測模型。靜態(tài)預(yù)測模型以集卡運行的歷史數(shù)據(jù)為依據(jù),通過v-SVM模型預(yù)測集卡的行駛路徑和行駛時間；動態(tài)預(yù)測模型使用v-SVM預(yù)測集卡的行駛路徑和路段基線行駛時間,以集卡實際運行數(shù)據(jù)為系統(tǒng)輸入,使用Kalman更新預(yù)測值,通過迭代得到集卡到達時間動態(tài)預(yù)測的結(jié)果。計算結(jié)果表明,靜態(tài)預(yù)測模型對暢通路段的預(yù)測結(jié)果較好,長距離易擁堵的路段預(yù)測誤差往往較大：動態(tài)預(yù)測模型能夠根據(jù)實際運行情況對預(yù)測結(jié)果動態(tài)更新,在所有路段上的預(yù)測精度均較高,因此集卡到達時間動態(tài)預(yù)測模型具有較高的預(yù)測精確度和魯棒性。
[Abstract]:With the increasingly fierce competition among ports, the container terminal is paying more and more attention to improving the service level of the port. The traditional centralized arrival method facilitates the scheduling of the loading and unloading operations of the wharf, but is inconvenient for the transportation of the cargo owners and the caravan fleet, and causes the congestion of the container head gate and the traffic pressure in the port area and the surrounding area. Therefore, some wharves take the strategy of random arrival of the export boxes to improve their competitiveness and provide convenience services. In the random arrival mode, the time and order of arrival of the container to the port are unknown, and the "berth plan, the loading plan, and the heap" of the traditional container terminal of the container terminal are concentrated in the mode of the container. The sequential planning and scheduling method of field plan to container entry plan will no longer apply. Because the terminal can not determine the daily arrival and arrival time of the specific voyage, it can not be reserved in the whole box area in advance. It can only be distributed according to the actual arrival situation of the container and the idle situation of the yard. This will undoubtedly be the container for the container. In the random arrival mode, it is beneficial to improve the operation efficiency and service level of the container terminal scheduling. In this paper, the static and dynamic prediction models of the arrival time of the container terminal are established. On the basis of the historical data of the line, the v-SVM model is used to predict the driving path and travel time of the collection card. The dynamic prediction model uses v-SVM to predict the driving path and the travel time of the base line, and uses the actual running data as the system input, updates the prediction value by Kalman, and obtains the dynamic prediction of the arrival time of the collection card by iteration. The calculation results show that the prediction results of the static prediction model are better for the unblocked section, and the prediction error of the long distance easily congestion is often larger: the dynamic prediction model can dynamically update the prediction results according to the actual operation conditions, and the prediction accuracy on all sections is high, so the dynamic prediction model of the arrival time of the collection card is of great importance. High accuracy and robustness.

【學(xué)位授予單位】：大連海事大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U691.3

【參考文獻】

相關(guān)期刊論文 前4條

1 劉敬賢;李云斌;;天津港主航道船舶到達規(guī)律的統(tǒng)計分析[J];武漢理工大學(xué)學(xué)報(交通科學(xué)與工程版);2008年02期

2 陳光英,張千里,李星;特征選擇和SVM訓(xùn)練模型的聯(lián)合優(yōu)化[J];清華大學(xué)學(xué)報(自然科學(xué)版);2004年01期

3 黃海軍,顧昌耀;Fisk隨機配流模型的特性和參數(shù)校正[J];系統(tǒng)科學(xué)與數(shù)學(xué);1997年04期

4 陳旭梅;龔輝波;王景楠;;基于SVM和Kalman濾波的BRT行程時間預(yù)測模型研究[J];交通運輸系統(tǒng)工程與信息;2012年04期

相關(guān)博士學(xué)位論文 前1條

1 于濱;城市公交系統(tǒng)模型與算法研究[D];大連理工大學(xué);2006年

相關(guān)碩士學(xué)位論文 前1條

1 馬振良;信息融合預(yù)測估計理論及其交通導(dǎo)航應(yīng)用研究[D];山東大學(xué);2012年

，

本文編號：1782597