本文關(guān)鍵詞：基于到達(dá)時刻的航班滑行時間預(yù)測方法研究　出處：《中國民航大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 拓?fù)鋱D 滑行路由設(shè)計(jì) 自適應(yīng)蟻群算法 非參數(shù)回歸模型

【摘要】：對航空器滑行時間作出準(zhǔn)確預(yù)測,是降低延誤時間、減少延誤波及、提升機(jī)場場面交通容量的手段之一。本文所研究的到達(dá)時刻航班的滑行時間預(yù)測,對其后續(xù)的航班保障服務(wù)時間安排、離港航班時刻計(jì)劃等都有著重要的參考意義。本文通過蟻群算法(ACA:ant colony algorithm)設(shè)計(jì)到港航班的滑行路由,并對蟻群算法作出自適應(yīng)性改進(jìn)以改善所設(shè)計(jì)的路由,利用此算法采集到相關(guān)數(shù)據(jù),采用非參數(shù)回歸模型預(yù)測該滑行路徑上后續(xù)滑行節(jié)點(diǎn)的時間。首先對到港航班的調(diào)度流程進(jìn)行闡述,分析了影響滑行時間的三個重要因素:滑行道容量、滑行路徑設(shè)計(jì)和場面沖突。并建立到港航班場面滑行的數(shù)學(xué)仿真模型,為后續(xù)的路由設(shè)計(jì)和時間預(yù)測研究奠定基礎(chǔ)。其次,選中某大型樞紐機(jī)場的部分區(qū)域抽象為帶鏈路與節(jié)點(diǎn)的網(wǎng)絡(luò)拓?fù)鋱D,關(guān)鍵的滑行節(jié)點(diǎn)與停機(jī)位用不同的符號標(biāo)識。以此為依托,引用ACA初步設(shè)計(jì)到港航班的滑行軌跡。對ACA中信息素的更新規(guī)則作出自適應(yīng)性改善,即為自適應(yīng)蟻群算法(Adaptive ACA),重新設(shè)計(jì)抵達(dá)航班的滑行軌跡。采集智能算法得到的時間信息,與場面監(jiān)控的數(shù)據(jù)一起處理后,建立非參數(shù)回歸模型的數(shù)據(jù)庫,按照算法模型預(yù)測到港航空器的后續(xù)滑行時間。最后,按照停機(jī)位分配計(jì)劃,對比智能算法與依據(jù)經(jīng)驗(yàn)安排的滑行軌跡仿真結(jié)果,從迭代過程、滑行距離、滑行時間與等待時間等方面分別作出分析。對比分析兩種方法的平均相對誤差,評估時間預(yù)測的結(jié)果。
[Abstract]:To make an accurate prediction of aircraft taxiing time is to reduce delay time, reduce the delay spread, one of the means to enhance the capacity of the airport surface traffic prediction. The arrival time of flight taxiing time, arrangements for the subsequent flight security Business Hours, outgoing class time program have important reference significance. This paper ant colony algorithm (ACA:ant colony algorithm) taxi route design flights to Hong Kong, and the ant colony algorithm for improving the adaptability to improve from the designed route, using this algorithm to collect relevant data, using the glide path prediction time subsequent sliding node nonparametric regression model. Firstly, the scheduling process of flights to Hong Kong this analysis of the three important factors that influence the sliding time: taxiway capacity, glide path design and scene conflict. And the establishment of class field surface sliding to port number Simulation model, lay the foundation for the prediction of subsequent design and routing time. Secondly, the selection of a large regional hub airport is abstracted as a network topology with link and node, node and key taxi stands with different symbol. On this basis, guiding sliding track preliminary design of flights to Hong Kong ACA the improvement of the rules. By adaptive pheromone updating ACA, namely adaptive ant colony algorithm (Adaptive ACA), sliding track re design. Flight arrival time information acquisition of intelligent algorithm, and the scene monitoring data processing together after the establishment of nonparametric regression model database, according to the algorithm model to predict the subsequent the sliding time of Hong Kong aircraft. Finally, according to the gate assignment plan, comparison of intelligent algorithm and on the basis of experience for the sliding track of the simulation results from the iterative process, sliding distance, sliding. The average relative error of the two methods is compared and analyzed, and the results of the time prediction are evaluated.

【學(xué)位授予單位】：中國民航大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：V355;TP18

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本文編號：1371924