本文選題：流行病傳播 + 社交關(guān)系��； 參考：《蘭州理工大學(xué)》2017年碩士論文

【摘要】：現(xiàn)實(shí)中,每個(gè)人都身處多個(gè)不同的社交關(guān)系網(wǎng)絡(luò),并且在這些社交網(wǎng)絡(luò)中扮演著各種角色。各種各樣的社交關(guān)系相互之間交疊的同時(shí)又彼此隔離,例如在某個(gè)人朋友圈內(nèi)的人們之間并不都是相互認(rèn)識(shí);同事之間也可能彼此又是同學(xué)關(guān)系;同一個(gè)人的朋友和親戚之間可能完全不認(rèn)識(shí)。無(wú)論是消息還是傳染病都可以通過(guò)這些錯(cuò)綜復(fù)雜的關(guān)系網(wǎng)傳播和流行。而包含有傳染病信息的消息與該傳染病同時(shí)在人群中傳播時(shí),對(duì)傳染病的傳播到底會(huì)產(chǎn)生什么樣的影響呢?毫無(wú)疑問(wèn),研究伴有信息傳播的流行病傳播過(guò)程是十分必要的。研究這些復(fù)雜的社交關(guān)系及其上流行的消息對(duì)傳染病傳播的影響,要先研究社交關(guān)系之間的信息交流特點(diǎn)。真實(shí)網(wǎng)絡(luò)中個(gè)體獲得疾病消息后,會(huì)根據(jù)以往的染病經(jīng)歷做出相應(yīng)的規(guī)避行為,在本文中稱其為個(gè)體應(yīng)激性規(guī)避行為。網(wǎng)絡(luò)中社交消息傳播必然會(huì)對(duì)流行病傳播過(guò)程產(chǎn)生影響。基于這個(gè)特點(diǎn),本文運(yùn)用統(tǒng)計(jì)物理、運(yùn)籌學(xué)和計(jì)算機(jī)仿真等方法著重研究由疾病消息引起的個(gè)體應(yīng)激性規(guī)避行為和由社交網(wǎng)絡(luò)交疊產(chǎn)生的個(gè)體多關(guān)系角色特點(diǎn)兩方面對(duì)流行病傳播的影響:(1)本文在單群體內(nèi)部基于個(gè)體應(yīng)激性規(guī)避行為,分別在WS小世界和BA無(wú)標(biāo)度網(wǎng)絡(luò)上改進(jìn)了SIS流行病傳播模型,并進(jìn)行理論分析和實(shí)驗(yàn)仿真。結(jié)果表明,由疾病消息引起的個(gè)體應(yīng)激性規(guī)避行為能夠促使網(wǎng)絡(luò)在整體層面上具有適應(yīng)、抑制流行病傳播的能力。這個(gè)現(xiàn)象說(shuō)明,個(gè)體可以通過(guò)自我學(xué)習(xí)獲得預(yù)防被感染的能力,同時(shí),網(wǎng)絡(luò)也能夠通過(guò)這種個(gè)體的特殊能力獲得對(duì)流行病的網(wǎng)絡(luò)整體防控能力。這種網(wǎng)絡(luò)整體層面上學(xué)習(xí)如何適應(yīng)疾病并逐漸調(diào)節(jié)健壯自己的行為,對(duì)快速應(yīng)對(duì)未來(lái)流行病爆發(fā)和有效控制流行病再傳播具有十分積極的作用。(2)為了更好地論述復(fù)雜的社交關(guān)系對(duì)流行病傳播的影響,本文中構(gòu)建一個(gè)不同于傳統(tǒng)多社團(tuán)網(wǎng)絡(luò)的疊加社交網(wǎng)絡(luò),同時(shí)提出了全新的MR-SIS流行病傳播模型,并進(jìn)行理論分析和試驗(yàn)仿真。結(jié)果表明,網(wǎng)絡(luò)中子網(wǎng)絡(luò)的組成結(jié)構(gòu)能夠?qū)α餍胁〉膫鞑ミ^(guò)程產(chǎn)生影響,尤其是疊加子網(wǎng)絡(luò)中的節(jié)點(diǎn),控制這些節(jié)點(diǎn)可以有效地抑制疫情的傳播蔓延。在這個(gè)基礎(chǔ)上,本文提出基于疊加子網(wǎng)的熟人免疫策略,實(shí)驗(yàn)結(jié)果也表明該策略是切實(shí)可行的。
[Abstract]:In reality, everyone lives in multiple social networks and plays a variety of roles in them. All kinds of social relationships overlap and separate from each other, for example, not all people in the circle of friends know each other; colleagues may also be classmates. Friends and relatives of the same person may not know each other at all. Both news and infectious diseases can be spread and spread through these intricate networks of relationships. What kind of impact will the information containing infectious diseases have on the transmission of infectious diseases when they are transmitted in the crowd at the same time? There is no doubt that it is necessary to study the process of epidemic transmission with information dissemination. To study the influence of these complicated social relationships and popular news on the transmission of infectious diseases, we should first study the characteristics of information exchange between social relationships. After getting the disease information, the individual in the real network will make the corresponding evasive behavior according to the past infection experience, which is called individual stress-evading behavior in this paper. The spread of social information in the network will inevitably have an impact on the epidemic spread process. Based on this characteristic, this paper uses statistical physics, Operational research and computer simulation methods focus on the impact of individual stress-evading behavior caused by disease messages and the characteristics of individual multi-relationship roles generated by overlapping social networks on epidemic transmission: 1) Group based on individual stress-induced circumvention behavior, The SIS epidemic propagation model is improved on WS small-world and BA scale-free networks, and the theoretical analysis and experimental simulation are carried out. The results show that the individual stress-evading behavior caused by disease information can make the network adapt to the epidemic at the whole level and inhibit the spread of the epidemic. This phenomenon shows that the individual can acquire the ability to prevent infection through self-learning, and the network can also acquire the overall network ability to prevent and control the epidemic through the special ability of the individual. The network as a whole learns how to adapt to disease and gradually modulate its own robust behavior. Have a very positive role in responding quickly to future outbreaks of epidemics and effectively controlling their re-transmission) in order to better address the impact of complex social relationships on the spread of epidemics, In this paper, a superimposed social network, which is different from the traditional multi-community network, is constructed, and a new MR-SIS epidemic transmission model is proposed, and the theoretical analysis and experimental simulation are carried out. The results show that the structure of the network neutron network can affect the epidemic spreading process, especially the nodes in the superimposed sub-network, and the control of these nodes can effectively inhibit the spread of the epidemic. On this basis, an acquaintance immune strategy based on superimposed subnets is proposed, and the experimental results show that the strategy is feasible.
【學(xué)位授予單位】：蘭州理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：G206;O157.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 梁蕾;劉桂榮;;重疊網(wǎng)絡(luò)上信息與疾病傳播模型及其分析[J];山東大學(xué)學(xué)報(bào)(理學(xué)版);2016年11期

2 Chun Yan JI;Da Qing JIANG;Ning Zhong SHI;;Two-group SIR Epidemic Model with Stochastic Perturbation[J];Acta Mathematica Sinica;2012年12期

3 張海峰;Small Michael;傅新楚;汪秉宏;;Dynamical behaviour of an epidemic on complex networks with population mobility[J];Chinese Physics B;2009年09期

4 劉雁;慕德俊;張家忠;;小世界網(wǎng)絡(luò)模型的非線性動(dòng)力學(xué)研究[J];系統(tǒng)仿真學(xué)報(bào);2009年05期

5 周海平;蔡紹洪;;基于群體稀疏分布的SIS疾病傳播模型[J];華中師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2008年03期

6 ;Epidemic spreading behavior in local-world evolving networks[J];Progress in Natural Science;2008年06期

7 劉常昱;胡曉峰;司光亞;羅批;;基于小世界網(wǎng)絡(luò)的輿論傳播模型研究[J];系統(tǒng)仿真學(xué)報(bào);2006年12期

8 李慶華,張陽(yáng),王多強(qiáng);P2P網(wǎng)絡(luò)中基于謠言傳播機(jī)制的資源搜索算法[J];計(jì)算機(jī)應(yīng)用;2005年11期

9 車宏安,顧基發(fā);無(wú)標(biāo)度網(wǎng)絡(luò)及其系統(tǒng)科學(xué)意義[J];系統(tǒng)工程理論與實(shí)踐;2004年04期

10 林國(guó)基,賈s，

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