發(fā)布時(shí)間：2018-03-03 04:37

  本文選題：Android平臺(tái)　切入點(diǎn)：數(shù)據(jù)采集終端　出處：《中國(guó)民航大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：隨著機(jī)場(chǎng)特種車(chē)輛數(shù)量越來(lái)越多及其日常運(yùn)行保障工作的特殊性和獨(dú)立性,現(xiàn)有系統(tǒng)無(wú)法滿足管理單位對(duì)特種車(chē)輛的特殊管理需求。絕大部分的特種車(chē)輛的日常運(yùn)營(yíng)管理依舊依靠音頻通話的方式及人工手動(dòng)簽單的模式,監(jiān)控效率低,準(zhǔn)確性差。機(jī)場(chǎng)日常運(yùn)營(yíng)智能化與信息化建設(shè)滯后的問(wèn)題正成為制約機(jī)場(chǎng)保障能力提升的重要因素。為解決上述問(wèn)題,本課題以Android平臺(tái)和無(wú)線局域網(wǎng)技術(shù)為基礎(chǔ),設(shè)計(jì)了針對(duì)機(jī)場(chǎng)特種車(chē)輛的監(jiān)控網(wǎng)絡(luò)系統(tǒng),描述了Android采集終端、無(wú)線局域網(wǎng)絡(luò)及UCMap移動(dòng)GIS系統(tǒng)三個(gè)重要組成部分。針對(duì)無(wú)線局域網(wǎng)絡(luò)傳輸數(shù)據(jù)過(guò)程中延時(shí)和網(wǎng)絡(luò)堵塞現(xiàn)象,本文對(duì)離散型粒子群算法進(jìn)行改進(jìn),設(shè)計(jì)了基于改進(jìn)型粒子群算法的無(wú)線數(shù)據(jù)幀格式,完成了網(wǎng)絡(luò)層路由協(xié)議中路由擇域信息庫(kù)(路由表)的設(shè)計(jì)工作,將改進(jìn)型粒子群優(yōu)化算法中的控制因子和參數(shù)影響到整個(gè)路由節(jié)點(diǎn)路徑選擇的過(guò)程中,解決了網(wǎng)絡(luò)堵塞問(wèn)題的同時(shí)降低了傳輸延遲時(shí)間。通過(guò)仿真軟件在兩種實(shí)際情況下同時(shí)對(duì)本文改進(jìn)型粒子群算法、隨機(jī)法以及遺傳算法進(jìn)行仿真,比較三種算法的流量負(fù)載指標(biāo),進(jìn)一步驗(yàn)證改進(jìn)型粒子群優(yōu)化算法對(duì)于解決路由負(fù)載不平衡問(wèn)題相比于現(xiàn)有算法的優(yōu)越性。實(shí)驗(yàn)和仿真結(jié)果顯示,本文設(shè)計(jì)的機(jī)場(chǎng)特種車(chē)輛監(jiān)控網(wǎng)路系統(tǒng)能夠有效的完善機(jī)場(chǎng)原有的運(yùn)營(yíng)管理系統(tǒng),提升機(jī)場(chǎng)智能化與信息化水平,具有一定的創(chuàng)新性和應(yīng)用價(jià)值。
[Abstract]:With the increasing number of special vehicles in the airport and the particularity and independence of the daily operation support work, The existing system can not meet the special management needs of special vehicles. Most of the daily operation and management of special vehicles still rely on the mode of audio call and manual signing orders, so the monitoring efficiency is low. The problem of the intelligence of airport daily operation and the lag of information construction is becoming an important factor that restricts the promotion of airport support ability. In order to solve the above problems, this subject is based on Android platform and wireless LAN technology. The monitoring network system for special vehicles in airport is designed, and three important components of Android acquisition terminal, wireless local area network and UCMap mobile GIS system are described. In this paper, the discrete particle swarm optimization algorithm is improved, the wireless data frame format based on the improved particle swarm optimization algorithm is designed, and the routing alternative information base (routing table) in the network layer routing protocol is designed. The control factors and parameters in the improved particle swarm optimization (PSO) algorithm affect the path selection of the whole routing node. The network clogging problem is solved and the transmission delay time is reduced. The improved particle swarm optimization algorithm, stochastic algorithm and genetic algorithm are simulated by simulation software. By comparing the traffic load indexes of the three algorithms, the superiority of the improved particle swarm optimization algorithm in solving the problem of routing load imbalance is further verified. The experimental and simulation results show that the improved PSO algorithm is more effective than the existing algorithms in solving the problem of routing load imbalance. The airport special vehicle monitoring network system designed in this paper can effectively improve the original airport operation management system, improve the airport intelligence and information level, and has certain innovative and application value.
【學(xué)位授予單位】：中國(guó)民航大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TN925.93;TP277

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