本文選題：人工魚(yú)群算法 + 應(yīng)急疏散　； 參考：《湖北工業(yè)大學(xué)》2017年碩士論文

【摘要】：隨著國(guó)民經(jīng)濟(jì)的繁榮,大型公共場(chǎng)所越來(lái)越密集化和規(guī)�；�。公共娛樂(lè)場(chǎng)所具有公共性、結(jié)構(gòu)復(fù)雜性、內(nèi)部財(cái)產(chǎn)高度集中等特點(diǎn),導(dǎo)致各種人員傷亡事故正呈不斷上升的趨勢(shì)。因此,為了保障建筑物內(nèi)人員生命安全,我們需要研究疏散者的行為規(guī)律和影響疏散效率的各種因素等,為制定科學(xué)有效的人員疏散方案提供重要依據(jù),有著重大的現(xiàn)實(shí)意義。本文以武漢沌口體育場(chǎng)內(nèi)人員疏散方案為研究對(duì)象,主要圍繞人工魚(yú)群算法疏散模型及其優(yōu)化展開(kāi)了研究,主要工作如下:(1)本文利用人工智能領(lǐng)域中的仿生學(xué)群智能優(yōu)化算法—人工魚(yú)群算法(AFSA)作為人員疏散模型的基礎(chǔ)建模方式,將宏觀微觀相結(jié)合,把疏散個(gè)體看做人工魚(yú)智能體,定義其離散視野、步長(zhǎng)等,并用魚(yú)的覓食、追尾、聚群等行為模擬疏散個(gè)體的心理活動(dòng)、路徑選擇、行為傾向等,對(duì)人員疏散過(guò)程進(jìn)行仿真,最后形成整體疏散路徑方案。(2)為了模擬更加細(xì)節(jié)化更加貼近于實(shí)際的疏散過(guò)程,同時(shí)也為了避免盲目疏散,本文對(duì)魚(yú)群算法進(jìn)行完善,為人工魚(yú)定義新的行為——等待行為,構(gòu)建更為科學(xué)的疏散網(wǎng)絡(luò),建立疏散場(chǎng)所三維邏輯網(wǎng)絡(luò),加入層次化路徑引導(dǎo)策略,解決了以往以節(jié)點(diǎn)和出口直線距離作為判斷依據(jù)的不現(xiàn)實(shí)性;并用更精確的數(shù)學(xué)表達(dá)式來(lái)刻畫(huà)真實(shí)疏散環(huán)境以及人的行為和運(yùn)動(dòng)過(guò)程,對(duì)擁擠度、逆行、同層移動(dòng)、堵塞耗時(shí)、等待時(shí)間等因素對(duì)疏散速度和路徑選擇的影響進(jìn)行定義并均衡考慮,以疏散用時(shí)間作為目標(biāo)函數(shù)提高了疏散效率。(3)人工魚(yú)群算法疏散模型迭代完畢是將所有人疏散清空,得到一個(gè)較優(yōu)解,本文令所有人工魚(yú)回到起點(diǎn)進(jìn)行多次循環(huán),在每次循環(huán)結(jié)束后引入蟻群信息素,通過(guò)擁擠度繁忙度以及疏散耗時(shí)等因素綜合影響的更新策略在每條邊上釋放一定量的信息素,改進(jìn)公共板,使其在下一次循環(huán)過(guò)程中的決策受到信息素影響。在不降低疏散效率的同時(shí)提高了疏散資源的利用率,分?jǐn)偝隹谪?fù)荷,降低路徑的繁忙程度。
[Abstract]:With the prosperity of national economy, large-scale public places become more and more intensive and scale. Public entertainment places are characterized by publicity, complexity of structure and high concentration of internal property, which leads to a rising trend of casualties. Therefore, in order to ensure the safety of people in buildings, we need to study the behavior of evacuees and the factors that affect the evacuation efficiency, which provides an important basis for the formulation of scientific and effective evacuation plan, which has great practical significance. In this paper, the evacuation scheme of Wuhan Zhankou Stadium is taken as the research object, and the evacuation model of artificial fish swarm algorithm and its optimization are studied. The main work is as follows: 1) in this paper, the artificial fish swarm optimization algorithm (AFSAA) is used as the basic modeling method of the evacuation model, and the evacuation individual is regarded as the artificial fish agent. The discrete field of vision, step size and so on are defined, and the psychological activities, path selection, behavior tendency of evacuees are simulated by fish foraging, rear-end, clustering and so on, and the evacuation process is simulated. Finally, in order to simulate the actual evacuation process in more detail, and to avoid the blind evacuation, this paper improves the fish swarm algorithm and defines a new behavior-waiting behavior for artificial fish. Constructing a more scientific evacuation network, establishing a three-dimensional logical network of evacuation sites, and adding a hierarchical path guidance strategy to solve the problem of using the distance between node and exit straight line as the basis of judgment. And more accurate mathematical expressions are used to describe the real evacuation environment and the behavior and movement of people. The factors such as waiting time define and consider the influence of evacuation speed and path selection. The evacuation efficiency is improved by using evacuation time as objective function. An optimal solution is obtained. In this paper, all workers go back to the starting point for several cycles, and the ant colony pheromone is introduced at the end of each cycle. Through the update strategy which is influenced by crowded degree of busy and evacuation time, a certain amount of pheromone is released on each edge, and the common board is improved so that its decision in the next cycle is affected by pheromone. The efficiency of evacuation is not reduced, and the utilization of evacuation resources is improved, the load of exit is shared, and the busy degree of route is reduced.
【學(xué)位授予單位】：湖北工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP18

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