The Evolution of Automatic Control Field Networks During the Half Century
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- 英文论文题名：The Evolution of Automatic Control Field Networks During the Half Century
- 论文作者：Xueguang Yang ; Zhihai Rong ; Chao Fan
- 英文论文作者：Xueguang Yang ; Zhihai Rong ; Chao Fan ; CompleX Lab ; Web Sciences Center and Big Data Research Center ; University of Electronic Science and Technology of China
- 年：2017
- 作者机构：CompleX Lab,Web Sciences Center and Big Data Research Center,University of Electronic Science and Technology of China;
- 英文论文关键词：Complex Networks ; Field Network ; Evolution
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（A）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（A）
- 语种：英文
- 分类号：O157.5;TP273
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：4
- 文件大小：224k
- 原文格式：D
- 会议级别：全国
摘要
In modern research the innovation is easy to appear in the multidisciplinary investigation. Understanding the interaction among related scientific research fields is an important problem. In this paper, we analyze the paper data published in IEEE Transactions on Automatic Control(T AC) during the past half century, and construct a field network to disclose the evolution of research fields in IEEE Control Systems Society. We find that the distribution of number of papers per field is heterogeneous with a power-law form, and there are some hot fields that can attract more papers in some time period. Hence, the field network owns the scale-free character and these key fields tend to interconnect as a dense core. Moreover, many structural properties in the field network, such as degree distribution, clustering coefficient, average shortest path length, degree mixing pattern, are evolving stably, which may provide some clues to predict the future development in Control Systems Society.
In modern research the innovation is easy to appear in the multidisciplinary investigation. Understanding the interaction among related scientific research fields is an important problem. In this paper, we analyze the paper data published in IEEE Transactions on Automatic Control(T AC) during the past half century, and construct a field network to disclose the evolution of research fields in IEEE Control Systems Society. We find that the distribution of number of papers per field is heterogeneous with a power-law form, and there are some hot fields that can attract more papers in some time period. Hence, the field network owns the scale-free character and these key fields tend to interconnect as a dense core. Moreover, many structural properties in the field network, such as degree distribution, clustering coefficient, average shortest path length, degree mixing pattern, are evolving stably, which may provide some clues to predict the future development in Control Systems Society.
In modern research the innovation is easy to appear in the multidisciplinary investigation. Understanding the interaction among related scientific research fields is an important problem. In this paper, we analyze the paper data published in IEEE Transactions on Automatic Control(T AC) during the past half century, and construct a field network to disclose the evolution of research fields in IEEE Control Systems Society. We find that the distribution of number of papers per field is heterogeneous with a power-law form, and there are some hot fields that can attract more papers in some time period. Hence, the field network owns the scale-free character and these key fields tend to interconnect as a dense core. Moreover, many structural properties in the field network, such as degree distribution, clustering coefficient, average shortest path length, degree mixing pattern, are evolving stably, which may provide some clues to predict the future development in Control Systems Society.
引文
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[2]A.Clauset,D.B.Larremore,and R.Sinatra,“Data-driven predictions in the science of science,”Science,vol.355,pp.477-480,2017.
[3]S.Milojevi,“Principles of scientific research team formation and evolution,”Proc.Natl.Acad.Sci.USA,vol.111,pp.3984-3989,2014.
[4]D.J.de Solla Price,“Networks of scientific papers,”Science,vol.149,pp.510-515,1965.
[5]S.Redner,“Citation statistics from 110 years of physical review,”Phys.Today,vol.58,pp.49-54,2005.
[6]M.E.J.Newman,“The structure of scientific collaboration networks,”Proc.Natl.Acad.Sci.USA,vol.98,pp.404-409,2001.
[7]A.L.Barabási,H.Jeong,Z.Neda,E.Ravasz,A.Schubert,and T.Vicsek,“Evolution of the social network of scientific collaborations,”Physica A,vol.311,pp.590-614,2002.
[8]R.Guimera,B.Uzzi,J.Spiro,and L.A.Amaral,“Team assembly mechanisms determine collaboration network structure and team performance,”Science,vol.308,pp.697-702,2005.
[9]A.Ma,R.J.Mondragn,and V.Latora,“Anatomy of funded research in science,”Proc.Natl.Acad.Sci.USA,vol.112,pp.14760-14765,2015.
[10]M.Szell and R.Sinatra,“Research funding goes to rich clubs,”Proc.Natl.Acad.Sci.USA,vol.112,pp.14749-14750,2015.
[11]A.M.Petersen,S.Fortunato,R.K.Pan,K.Kaski,O.Penner,A.Rungi,M.Riccaboni,H.E.Stanley,and F.Pammolli,“Reputation and impact in academic careers,”Proc.Natl.Acad.Sci.USA,vol.111,pp.15316-15321,2014.
[12]A.Clauset,S.Arbesman,and D.B.Larremore,“Systematic inequality and hierarchy in faculty hiring networks,”Science Advances,vol.1,pp.e1400005,2015.
[13]M.E.J.Newman,“The structure and function of complex networks,”SIAM Rev.,vol.45,pp.167-256,2003.
[14]X.F.Wang and C.Chen,“Complex Networks:Small-World,Scale-Free and Beyond,”IEEE Circuits and Systems Magazine,vol.1,pp.6-20,2003.
[15]S.Boccaletti,V.Latora,Y.Moreno,M.Chavez,and D.U.Hwang DU,“Complex networks:Structure and dynamics,”Phys.Rep.,vol.424,pp.175-308,2006.
[16]L.M.A.Bettencourt,“Impact of Changing Technology on the Evolution of Complex Informational Networks,”Proc.of the IEEE,vol.102,pp.1878-1891,2014.
[17]G.R.Chen,“Pinning Control and Controllability of Complex Dynamical Networks,”International Journal of Automation and Computing,vol.14,pp.19,2017.
[18]http://datamarket.azure.com/dataset/mrc/microsoftacademic
[19]A.Sinha,Z.Shen,Y.Song,H.Ma,D.Eide,B.-J.P.Hsu,and K.Wang,“An Overview of Microsoft Academic Service(MAS)and Applications,”Proceedings of the 24th International Conference on World Wide Web(WWW 15 Companion),New York:ACM,2015,pp.243-246.
[20]R.Olfati-Saber and R.M.Murray,“Consensus problems in networks of agents with switching topology and time-delays,”IEEE Trans.Automat.Contr.,vol.49,pp.1520-1533,2004.
[21]A.L.Barabási and R.Albert,“Emergence of scaling in random networks,”Science,vol.286,pp.509-512,1999.
[22]S.N.Dorogovtsev,A.V.Goltsev,and J.F.F.Mendes,“Kcore organization of complex networks,”Phys.Rev.Lett.,vol.96,pp.040601,2006.
[23]S.Maslov and K.Sneppen,“Specificity and stability in topology of protein networks,”Science,vol.296,pp.910-913,2002.
[24]D.J.Watts and S.H.Strogatz,“Collective dynamics of‘small-world’networks,”Nature,vol.393,pp.440-442,1998.
[25]M.E.J.Newman,“Assortative Mixing in Networks,”Phys.Rev.Lett.,vol.89,pp.208701,2002.