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復(fù)雜網(wǎng)絡(luò)傳播動(dòng)力學(xué):模型、方法與穩(wěn)定性分析(英文版)

復(fù)雜網(wǎng)絡(luò)傳播動(dòng)力學(xué):模型、方法與穩(wěn)定性分析(英文版)

定 價(jià):¥79.00

作 者: 傅新楚,[澳] 斯摩爾(Michael Small),陳關(guān)榮 著
出版社: 高等教育出版社
叢編項(xiàng): 網(wǎng)絡(luò)科學(xué)與工程叢書
標(biāo) 簽: 計(jì)算機(jī)/網(wǎng)絡(luò) 網(wǎng)絡(luò)配置與管理 網(wǎng)絡(luò)與數(shù)據(jù)通信

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ISBN: 9787040307177 出版時(shí)間: 2014-02-01 包裝: 精裝
開本: 16開 頁(yè)數(shù): 314 字?jǐn)?shù):  

內(nèi)容簡(jiǎn)介

《網(wǎng)絡(luò)科學(xué)與工程叢書·復(fù)雜網(wǎng)絡(luò)傳播動(dòng)力學(xué):模型、方法與穩(wěn)定性分析(英文版)》較全面介紹了復(fù)雜網(wǎng)絡(luò)傳播動(dòng)力學(xué)的研究結(jié)果與最新進(jìn)展,包括三位作者的近期研究成果。主要內(nèi)容包括各種“倉(cāng)室”模型及有關(guān)的主要結(jié)果;復(fù)雜網(wǎng)絡(luò)上流行病的網(wǎng)絡(luò)建模、數(shù)值模擬、疾病控制與風(fēng)險(xiǎn)評(píng)估;流行病閾值的幾種主要求法;疾病的控制與免疫方法,各種免疫策略的比較;人類意識(shí)在疾病傳播與控制中的獨(dú)特作用;在傳播媒介作用下非齊次網(wǎng)絡(luò)上流行病動(dòng)力學(xué)的性質(zhì);幾種典型網(wǎng)絡(luò)傳播模型的全局穩(wěn)定性;網(wǎng)絡(luò)同步動(dòng)力學(xué)與流行病傳播動(dòng)力學(xué)之間的自適應(yīng)演化關(guān)系;信息、輿情、謠言等在因特網(wǎng)及社會(huì)網(wǎng)絡(luò)中的傳播特性;信啟、傳播與流行病傳播之間的異同等。
  《網(wǎng)絡(luò)科學(xué)與工程叢書·復(fù)雜網(wǎng)絡(luò)傳播動(dòng)力學(xué):模型、方法與穩(wěn)定性分析(英文版)》可作為高等院校應(yīng)用數(shù)學(xué)、生物數(shù)學(xué)、計(jì)算機(jī)科學(xué)與技術(shù)等專業(yè)相關(guān)課程的教學(xué)參考書,也可供從事動(dòng)力系統(tǒng)、網(wǎng)絡(luò)科學(xué)和復(fù)雜性科學(xué)等領(lǐng)域研究工作的教學(xué)科研人員參考使用。

作者簡(jiǎn)介

傅新楚,2001年獲英國(guó)Exeter大學(xué)應(yīng)用數(shù)學(xué)博士學(xué)位。1997年至2002年在英國(guó)劍橋大學(xué)、Warwick大學(xué)作高級(jí)訪問(wèn)學(xué)者,隨后在英國(guó)Surrey大學(xué)、Exeter大學(xué)任ResearchFellow,由英國(guó)國(guó)家基金EPSRC資助研究一類不連續(xù)系統(tǒng)的動(dòng)力學(xué)問(wèn)題。2002年5月回國(guó),在上海大學(xué)數(shù)學(xué)系工作,任教授、博士生導(dǎo)師。先后主持國(guó)家自然科學(xué)基金項(xiàng)目5項(xiàng),曾參加國(guó)家“攀登計(jì)劃”重大項(xiàng)目。
  
  斯摩爾(Michael Small),西澳大利亞大學(xué)應(yīng)用數(shù)學(xué)Winthrop教授,澳大利亞研究理事會(huì)未來(lái)研究員,IEEE高級(jí)會(huì)員,澳大利亞數(shù)學(xué)會(huì)會(huì)員,多家國(guó)際期刊的編委。曾在香港理T.大學(xué)電子及信息工程系做博士后并任教。在混沌、非線性時(shí)間序列建模、復(fù)雜系統(tǒng)等領(lǐng)域的基礎(chǔ)理論及應(yīng)用方面,發(fā)表約150篇期刊論文和書籍章節(jié),約150篇會(huì)議論文,3部著作。
  
  陳關(guān)榮,1981年獲中山大學(xué)計(jì)算數(shù)學(xué)碩士學(xué)位,1987年獲美國(guó)德克薩斯A&M大學(xué)應(yīng)用數(shù)學(xué)博士學(xué)位。于休斯頓大學(xué)任教至2000年,現(xiàn)任香港城市大學(xué)電子工程系講座教授。1996年當(dāng)選為IEEE Fellow。獲2012年及2008年國(guó)家自然科學(xué)二等獎(jiǎng)、2010年何梁何利獎(jiǎng)、2011年俄羅斯歐拉獎(jiǎng)并獲俄羅斯圣彼得堡國(guó)立大學(xué)榮譽(yù)博士學(xué)位,獲5項(xiàng)IEEE等最佳學(xué)術(shù)雜志論文獎(jiǎng),是國(guó)內(nèi)外30多所大學(xué)的榮譽(yù)或客座教授,現(xiàn)任International Journal of Bifurcation and Chaos主編。SCI他引兩萬(wàn)多次,h指數(shù)78,被ISI評(píng)定為工程學(xué)高引用率研究人員。

圖書目錄

1 Introduction
1.1 Motivation and background
1.2 A brief history of mathematical epidemiology
1.2.1 Compartmental modeling
1.2.2 Epidemic modeling on complex networks
1.3 Organization of the book
References

2 Various epidemic models on complex networks
2.1 Multiple stage models
2.1.1 Multiple susceptible individuals
2.1.2 Multiple infected individuals
2.1.3 Multiple-staged infected individuals
2.2 Staged progression models2.1 Multiple stage models
2.1:1 Multiple susceptible individuals
2.1.2 Multiple infected individuals
2.1.3 Multiple-staged infected individuals
2.2 Staged progression models
2.2.1 Simple-staged progression model
2.2.2 Staged progression model on homogenous networks
2.2.3 Staged progression model on heterogenous networks
2.2.4 Staged progression model with birth and death
2.2.5 Staged progression model with birth and death on homogenous networks
2.2.6 Staged progression model with birth and death on heterogenous networks
2.3 Stochastic SIS model
2.3.1 A general concept: Epidemic spreading efficiency
2.4 Models with population mobility
2.4.1 Epidemic spreading without mobility of individuals
2.4.2 Spreading of epidemic diseases among different cities
2.4.3 Epidemic spreading within and between cities
2.5 Models in meta-populations
2.5.1 Model formulation
2.6 Models with effective contacts
2.6.1 Epidemics with effectively uniform contact
2.6.2 Epidemics with effective contact in homogenous and heterogenous networks
2.7 Models with two distinct routes
2.8 Models with competing strains
2.8.1 SIS model with competing strains
2.8.2 Remarks and discussions
2.9 Models with competing strains and saturated infectivity
2.9.1 SIS model with mutation mechanism
2.9.2 SIS model with super-infection mechanism
2.10 Models with birth and death of nodes and links
2.11 Models on weighted networks
2.11.1 Model with birth and death and adaptive weights
2.12 Models on directed networks
2.13 Models on colored networks
2.13.1 SIS epidemic models on colored networks
2.13.2 Microscopic Markov-chain analysis
2.14 Discrete epidemic models
2.14.1 Discrete SIS model with nonlinear contagion scheme
2.14.2 Discrete-time epidemic model in heterogenous networks
2.14.3 A generalized model References

3 Epidemic threshold analysis
3.1 Threshold analysis by the direct method
3.1.1 The epidemic rate is βln inside the same cities
3.1.1 Epidemics on homogenous networks
3.1.1 Epidemics on heterogenous networks
3.2 Epidemic spreading efficiency threshold and epidemic threshold
3.2.1 The case of λ1 ≠λ2
3.2.2 The case of λ1≠λ2
3.2.3 Epidemic threshold in finite populations
3.2.4 Epidemic threshold in infinite populations
3.3 Epidemic thresholds and basic reproduction numbers
3.3.1 Threshold from a self-consistency equation
3.3.2 Threshold unobtainable from a self-consistency equation
3.3.3 Threshold analysis for SIS model with mutation
3.3.4 Threshold analysis for SIS model with super-infection
3.3.5 Epidemic thresholds for models on directed networks
3.3.6 Epidemic thresholds on technological and social networks
3.3.7 Epidemic thresholds on directed networks with immunization
3.3.8 Comparisons of epidemic thresholds for directed networks with immunizationdel
……
4 Networked models for SARS and avian influenza
5 Infectivity functions
6 SIS models with an infective medium
7 Epidemic control and awareness
8 Adaptive mechanism between dynamics and epidemics
9 Epidemic control and immunization
10 Global stability analysis
11 Information diffusion and pathogen propagation
Appendix A Proofs of theorems
Appendix B Further proofs of results
Index

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