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Статті в журналах з теми "Small world scale-free transportation network"
Shang, Jun, Hao Qiang Liu, Qiang Liu, and Zi Qi Liu. "Design of the Small World Model by NS2." Applied Mechanics and Materials 496-500 (January 2014): 2338–41. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2338.
Повний текст джерелаTarapata, Zbigniew. "Modelling and analysis of transportation networks using complex networks: Poland case study." Archives of Transport 36, no. 4 (December 31, 2015): 55–65. http://dx.doi.org/10.5604/08669546.1185207.
Повний текст джерелаWang, Yong, and Ta Zhou. "Complexity Analysis of Public Transportation Network in Zhangjiagang City Using Complex Network Theory." Advanced Materials Research 546-547 (July 2012): 1211–16. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.1211.
Повний текст джерелаTrobajo, M. T., and M. V. Carriegos. "Spanish Airport Network Structure: Topological Characterization." Computational and Mathematical Methods 2022 (April 9, 2022): 1–9. http://dx.doi.org/10.1155/2022/4952613.
Повний текст джерелаZHAO, HUI, and ZIYOU GAO. "GENERALIZED SHORTEST PATH AND TRAFFIC EQUILIBRIUM IN COMPLEX TRANSPORTATION NETWORKS." Modern Physics Letters B 21, no. 20 (August 30, 2007): 1343–49. http://dx.doi.org/10.1142/s021798490701350x.
Повний текст джерелаChong, Pengyun, Bin Shuai, Shaowei Deng, Jianting Yang, and Hui Yin. "Analysis on Topological Properties of Dalian Hazardous Materials Road Transportation Network." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/340780.
Повний текст джерелаDe Bona, A. A., K. V. O. Fonseca, M. O. Rosa, R. Lüders, and M. R. B. S. Delgado. "Analysis of Public Bus Transportation of a Brazilian City Based on the Theory of Complex Networks Using the P-Space." Mathematical Problems in Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/3898762.
Повний текст джерелаZhang, Ling, Jingjing Hao, Xiaofeng Ji, and Lan Liu. "Research on the Complex Characteristics of Freight Transportation from a Multiscale Perspective Using Freight Vehicle Trip Data." Sustainability 11, no. 7 (March 29, 2019): 1897. http://dx.doi.org/10.3390/su11071897.
Повний текст джерелаRen, Cuiping, Bianbian Chen, Fengjie Xie, Xuan Zhao, Jiaqian Zhang, and Xueyan Zhou. "Understanding Hazardous Materials Transportation Accidents Based on Higher-Order Network Theory." International Journal of Environmental Research and Public Health 19, no. 20 (October 16, 2022): 13337. http://dx.doi.org/10.3390/ijerph192013337.
Повний текст джерелаCao, Weiwei, Xiangnan Feng, Jianmin Jia, and Hong Zhang. "Characterizing the Structure of the Railway Network in China: A Complex Weighted Network Approach." Journal of Advanced Transportation 2019 (February 3, 2019): 1–10. http://dx.doi.org/10.1155/2019/3928260.
Повний текст джерелаДисертації з теми "Small world scale-free transportation network"
Lamanna, Fabio. "Time-related analysis of small world and scale-free transportation networks." Doctoral thesis, Università degli studi di Trieste, 2008. http://hdl.handle.net/10077/2747.
Повний текст джерелаCoupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web are only a few examples of Small World and Scale-free complex networks, i.e. systems composed by a large number of highly interconnected dynamical units. During the last ten years these kinds of systems have been the subject of many studies related to comprehend their common structural properties and their dynamics. Small World and Scale-free networks are supposed to be very stable and robust structures in case of failures or deliberate attacks on the system. Moreover, due to their well-known properties, they allow to model several real networks in order to find the key elements for a complete and efficient communication activity between nodes. This thesis introduced a new mathematical tool developed by the author called Time=net.work. The latter has got the purpose to extend the above mentioned complex networks theories to transportation systems under a new time-related point of view. Analysis have been taken firstly on Berlin Transportation Network and then to several other test cases. The relative results help in finding statistical properties about the connectivity and the structure of such system both topologically and considering the travel time and the frequency of the scheduled services. This is a new approach on robustness of transportation networks which allows to find which and how many nodes have to assurance their functionality in order to provide a desired Level of Service in case of failures or deliberate attacks.
I sistemi biologici e chimici, le interazioni ed i rapporti sociali, Internet e il World Wide Web sono soltanto alcuni esempi dei cosiddetti sistemi complessi Small World e Scale-free; essi sono particolari strutture di rete composte da un gran numero di unità interconnesse tra loro che scambiano informazioni dinamicamente ed evolvendosi nel tempo. Negli ultimi dieci anni questi particolari sistemi fisici sono stati oggetto di numerosi studi tesi a determinare le proprietà comuni a diversi tipi di rete e le loro dinamiche. Le reti Small World e Scale-free ad esempio, sono state analizzate per la loro stabilità e resistenza in caso di avarie o di attacchi mirati verso particolari elementi del sistema. Grazie alle loro proprietà tali sistemi consentono di modellizzare diversi tipi di reti reali al fine di determinare gli elementi chiave necessari a garantire la più completa efficienza nelle comunicazioni tra i nodi. Questa tesi presenta un nuovo strumento matematico sviluppato dall'autore denominato Time=net.work. Quest'ultimo ha l'obiettivo di estendere le teorie che contraddistinguono i sistemi complessi a reti di trasporto in funzione di caratteristiche temporali. Le analisi hanno riguardato la rete di trasporto pubblico di Berlino ed altri casi di studio. I relativi risultati consentono di ricavare numerose proprietà statistiche riguardo la connettività e le proprietà strutturali di tali sistemi, sia da un punto di vista topologico che da quello legato ai tempi di percorrenza ed alla frequenza dei servizi. Si tratta di un nuovo approccio alla resistenza delle reti di trasporto che permette di ricavare quali e quanti elementi della rete devono garantire il loro completo funzionamento al fine di provvedere un desiderato Livello di Servizio in caso di avarie o di attacchi deliberati al sistema.
XX Ciclo
1977
Westlund, Johannes, and Jakob Svenningsson. "Examining network properties using breadth-first sampling : A case study of the network spanned by the kth.se domain." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208346.
Повний текст джерелаKomplexa nätverk i vår omvärld består av ett stort antal hörn och kanter vilket gör dem svå- ra att extrahera och analysera. Denna rapport undersöker vilka nätverksegenskaper som kan härledas vid undersökningen av små stickprov av ett nätverk och hur bra dessa representerar egenskaperna hos det fullständiga nätverket. Detta är av betydelse eftersom användandet av små stickprov kommer troligtvis att vara standarden vid undersökningar av nätverk i framtiden. Denna studie undersökte scale-free egenskapen, small-world egenskapen och community strukturen för nätverket som omfattas av KTH domaänen. Metoden innefattade att samla in data om nätverket genom stickprov baserat på en bredden-först sökning. Detta realiserades genom att använda en sökrobot. Sedan jämfördes de olika stickproven med avseende på de olika nätverksegenskaperna. Resultetat visade att nätverkets scale-free egenskap kunde approximaeras med små stickprov. Däremot var det inte möjligt att approximera nätverkets small-world egenskap genom användet av den givna stickprovsmetoden. Goda approximationer observerades för att avgöra ett hörns community tillhörighet men den allmäna community strukturen kunde inte approximeras. Sammanfattningsvis visade resultatet att stickprov kan användas för att approximera vissa egenskaper hos det fullständiga KTH nätverket men att mer forskning krävs för att avgöra om resultaten kan generaliseras.
Sun, Xiaowei. "Comparative Analysis of Urban Morphology: Evaluating Space Syntax and Traditional Morphological Methods." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-15492.
Повний текст джерелаAbdesselam, Kahina. "Network Distribution and Respondent-Driven Sampling (RDS) Inference About People Who Inject Drugs in Ottawa, Ontario." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/38744.
Повний текст джерелаLuo, Hongwei, and Hongwei luo@rmit edu au. "Modelling and simulation of large-scale complex networks." RMIT University. Mathematical and Geospatial Sciences, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080506.142224.
Повний текст джерелаZhuang, Yuwen. "Metric Based Automatic Event Segmentation and Network Properties Of Experience Graphs." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1337372416.
Повний текст джерелаJiang, Jian. "Modeling of complex network, application to road and cultural networks." Phd thesis, Université du Maine, 2011. http://tel.archives-ouvertes.fr/tel-00691129.
Повний текст джерелаDuarte, Gerdivane Ferreira. "F?sica estat?stica aplicada a sistemas sociais atrav?s do estudo de redes complexas." Universidade Federal do Rio Grande do Norte, 2014. http://repositorio.ufrn.br:8080/jspui/handle/123456789/18609.
Повний текст джерелаCoordena??o de Aperfei?oamento de Pessoal de N?vel Superior
In this work a study of social networks based on analysis of family names is presented. A basic approach to the mathematical formalism of graphs is developed and then main theoretical models for complex networks are presented aiming to support the analysis of surnames networks models. These, in turn, are worked so as to be drawn leading quantities, such as aggregation coefficient, minimum average path length and connectivity distribution. Based on these quantities, it can be stated that surnames networks are an example of complex network, showing important features such as preferential attachment and small-world character
Neste trabalho ? apresentado um estudo das redes sociais baseado na an?lise dos nomes de fam?lias. Faz-se uma abordagem b?sica do formalismo matem?tico dos grafos e em seguida apresenta-se os principais modelos te?ricos para as Redes Complexas com o objetivo de fundamentar a an?lise das redes dos sobrenomes. Estas, por sua vez, s?o trabalhadas de modo a serem extra?das as principais grandezas, tais como coe ciente de agrega??o, menor caminho m?dio e distribui??o de conectividades. Com base nestas grandezas, pode-se a rmar que as redes de sobrenomes s?o um exemplo de rede complexa, exibindo caracter?sticas importantes como liga??o preferencial e o car?ter de mundo pequeno.
Hsiao, Ping-Nan, and 蕭炳南. "A Small World with Scale Free Model for Network Communication." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/67517557425671723948.
Повний текст джерела淡江大學
資訊工程學系
91
The small world network model has been popular to describe human social relations and network formed by biological entities such as neurons. The network model achieves small diameter with relatively few links as measured by the ratio of clustering coefficient and the number of links. It is quite natural to consider email communication as similar to social network pattern. Quite surprisingly we find from our empirical study that email network follows a different type of network model that falls into the category of scale-free network. We propose a new network model to describe such communication topology from linked edge, degree and messages size aspect.
Piersa, Jarosław. "Scale-freeness and small-world phenomenon in information-flow graphs of geometrical neural networks." Doctoral thesis, 2013. http://depotuw.ceon.pl/handle/item/215.
Повний текст джерелаCelem niniejszej rozprawy jest analiza uproszczonego modelu przepływu aktywności w sztucznych sieciach neuronowych zanurzonych w przestrzeni geometrycznej. Przedstawiony model dostarcza matematycznego opisu transferu aktywności w terminach zbliżonych do wielowartościowych maszyn Boltzmanna. Wymóg zachowania stałej sumarycznej aktywności odzwierciedla krytyczność dynamiki i wraz z uwzględnieniem wpływu lokalizacji geometrycznej neuronów sprawia, że system jest bardziej adekwatny do modelowania rzeczywistych sieci. Badania koncentrują się na bezskalowości oraz fenomenie małego świata w wyżej wymienionych sieciach. Uzyskane rezultaty potwierdzają obecność obu własności w omawianych grafach. Pokażemy, że rozkład stopni wejściowych wierzchołków zachowuje się jak funkcja potęgowa z wykładnikiem równym -2. Ponadto prezentujemy wyniki dotyczące charakterystycznej długości ścieżki, który rośnie logarytmicznie wraz z wielkością systemu, podczas gdy współczynnik klasteryzacji okazuje się dość duży. W konsekwencji stosunek klasteryzacji do długości ścieżek jest zaskakująco wysoki, co jest dystynktywną własnością sieci małego świata. Wreszcie, dokonujemy porównania cech omawianego modelu przepływu aktywności z neuro-biologicznymi rezultatami, przedstawionymi w badaniach grafów mózgowych z danych uzyskanych z funkcjonalnego obrazowania z wykorzystaniem rezonansu magnetycznego (fMRI). Wskazujemy silną odpowiedniość pomiędzy kształtem i wartością wykładnika rozkładu stopni, zaś klasteryzacja i charakterystyczna długość ścieżki są porównywalne w modelu i danych medycznych.
Книги з теми "Small world scale-free transportation network"
Vernizzi, Graziano, and Henri Orland. Complex networks. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.43.
Повний текст джерелаЧастини книг з теми "Small world scale-free transportation network"
"Small World and Scale-Free Network Topologies in an Artificial Regulatory Network Model." In Artificial Life IX. The MIT Press, 2004. http://dx.doi.org/10.7551/mitpress/1429.003.0068.
Повний текст джерелаStein, Michael D., and Sandro Galea. "Creating Health Is Like Winning at Soccer." In Pained, 3–4. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780197510384.003.0001.
Повний текст джерелаNolte, David D. "Network Dynamics." In Introduction to Modern Dynamics, 207–42. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198844624.003.0007.
Повний текст джерелаYoussef, Bassant, Scott F. Midkiff, and Mohamed R. M. Rizk. "SNAM." In Advanced Methods for Complex Network Analysis, 215–36. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9964-9.ch009.
Повний текст джерела"Accelerated Network Traversal Using Multi/Many-Cores." In Advances in Computer and Electrical Engineering, 59–86. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3799-1.ch003.
Повний текст джерелаQiu, Yuhu, Tianyang Lyu, Xizhe Zhang, and Ruozhou Wang. "Studies on the Decrease Mechanisms of Typical Complex Networks." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210293.
Повний текст джерелаBansal, Ankush, and Pulkit Anupam Srivastava. "Transcriptomics to Metabolomics." In Advances in Bioinformatics and Biomedical Engineering, 188–206. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2607-0.ch008.
Повний текст джерелаBansal, Ankush, and Pulkit Anupam Srivastava. "Transcriptomics to Metabolomics." In Biotechnology, 361–79. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8903-7.ch014.
Повний текст джерелаVrana, Vasiliki G., Dimitrios A. Kydros, Evangelos C. Kehris, Anastasios-Ioannis T. Theocharidis, and George I. Kavavasilis. "Top Museums on Instagram." In Research Anthology on Strategies for Using Social Media as a Service and Tool in Business, 1029–55. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-9020-1.ch052.
Повний текст джерелаPatterson, Megan S., Michael K. Lemke, and Jordan Nelon. "Complex Systems in a Nutshell." In Complex Systems and Population Health, 19–32. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190880743.003.0002.
Повний текст джерелаТези доповідей конференцій з теми "Small world scale-free transportation network"
Nabati, Rouhollah, Ali Ghaffari Nejad, and Ali Yousefi. "EDSS: An extended deterministic scale-free small world network." In 2016 Eighth International Conference on Information and Knowledge Technology (IKT). IEEE, 2016. http://dx.doi.org/10.1109/ikt.2016.7777790.
Повний текст джерелаSun, Yuan-yuan, Kai-ning Hou, and Xing-yuan Wang. "A Scale-Free Small-World Network from Durer Pentagons." In 2011 Fourth International Workshop on Chaos-Fractals Theories and Applications (IWCFTA). IEEE, 2011. http://dx.doi.org/10.1109/iwcfta.2011.14.
Повний текст джерелаChen, Guangping, Jiabo Hao, Zhiyuan Zhang, and Yu Tang. "Getting scale-free network from a small world network without growth." In 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI). IEEE, 2012. http://dx.doi.org/10.1109/icaci.2012.6463112.
Повний текст джерелаMa, Fei, Jing Su, and Bing Yao. "One small-world scale-free network model having tuned parameters." In 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE, 2017. http://dx.doi.org/10.1109/iaeac.2017.8053985.
Повний текст джерелаSihua, Yang, Yao Bing, Yao Ming, Chen Xiang-En, Zhang Xiaomin, Wang Hongyu, and Yang Chao. "Labelling Sun-Like Graphs from Scale-Free Small-World Network Models." In 2014 Sixth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA). IEEE, 2014. http://dx.doi.org/10.1109/icmtma.2014.93.
Повний текст джерелаLiu, Dongzhao, Lei Guo, Youxi Wu, and Guizhi Xu. "Robustness of the Scale-free Spiking Neural Network with Small-world Property." In 2020 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2020. http://dx.doi.org/10.1109/ssci47803.2020.9308435.
Повний текст джерелаBERKOWITZ, KATHERINE, RISHABH D. GUHA, OLUWATIMILEHIN OLUWAJIRE, and LANDON GRACE. "A MACHINE LEARNING APPROACH FOR IMPACT DAMAGE QUANTIFICATION IN POLYMER MATRIX COMPOSITES." In Proceedings for the American Society for Composites-Thirty Seventh Technical Conference. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/asc37/36412.
Повний текст джерела