Academic literature on the topic 'Urban network modelling'
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Journal articles on the topic "Urban network modelling"
Ji, Q., S. Barr, P. James, and D. Fairbairn. "A GEOSPATIAL ANALYSIS FRAMEWORK FOR FINE SCALE URBAN INFRASTRUCTURE NETWORKS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4 (September 19, 2018): 291–96. http://dx.doi.org/10.5194/isprs-archives-xlii-4-291-2018.
Full textPrice, R. K., and G. J. Catterson. "Monitoring and modelling in urban drainage." Water Science and Technology 36, no. 8-9 (October 1, 1997): 283–87. http://dx.doi.org/10.2166/wst.1997.0680.
Full textHuide, Zhou, Rachid Bouyekhf, and Adbellah EL Moudni. "Modelling and H∞ Control of Urban Transportation Network." IFAC Proceedings Volumes 45, no. 24 (September 2012): 72–77. http://dx.doi.org/10.3182/20120912-3-bg-2031.00014.
Full textKunapo, Joshphar, Shobhit Chandra, and Jim Peterson. "Drainage Network Modelling for Water-Sensitive Urban Design." Transactions in GIS 13, no. 2 (April 2009): 167–78. http://dx.doi.org/10.1111/j.1467-9671.2009.01146.x.
Full textNagendra, S. M. Shiva, and Mukesh Khare. "Modelling urban air quality using artificial neural network." Clean Technologies and Environmental Policy 7, no. 2 (February 19, 2005): 116–26. http://dx.doi.org/10.1007/s10098-004-0267-6.
Full textKutzner, Tatjana, Ihab Hijazi, and Thomas H. Kolbe. "Semantic Modelling of 3D Multi-Utility Networks for Urban Analyses and Simulations." International Journal of 3-D Information Modeling 7, no. 2 (April 2018): 1–34. http://dx.doi.org/10.4018/ij3dim.2018040101.
Full textZheng, Fangfang, Xiaobo Liu, Henk van Zuylen, Jie Li, and Chao Lu. "Travel Time Reliability for Urban Networks: Modelling and Empirics." Journal of Advanced Transportation 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/9147356.
Full textZeng, Lu, Jun Liu, Yong Qin, Li Wang, and Jie Yang. "A Passenger Flow Control Method for Subway Network Based on Network Controllability." Discrete Dynamics in Nature and Society 2018 (September 4, 2018): 1–12. http://dx.doi.org/10.1155/2018/5961090.
Full textden Duijn, X., G. Agugiaro, and S. Zlatanova. "MODELLING BELOW- AND ABOVE-GROUND UTILITY NETWORK FEATURES WITH THE CITYGML UTILITY NETWORK ADE: EXPERIENCES FROM ROTTERDAM." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W7 (September 20, 2018): 43–50. http://dx.doi.org/10.5194/isprs-annals-iv-4-w7-43-2018.
Full textYan, J., S. W. Jaw, R. V. Son, K. H. Soon, and G. Schrotter. "THREE-DIMENSIONAL DATA MODELLING FOR UNDERGROUND UTILITY NETWORK MAPPING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4 (September 19, 2018): 711–15. http://dx.doi.org/10.5194/isprs-archives-xlii-4-711-2018.
Full textDissertations / Theses on the topic "Urban network modelling"
Vythoulkas, Petros C. "Modelling dynamic stochastic user equilibrium for urban road networks." Thesis, Cranfield University, 1991. http://hdl.handle.net/1826/3937.
Full textHo, Siu-kui. "Sensitivity of parameters in transportation modelling on the implication of network requirement : a case study of Hong Kong /." [Hong Kong] : University of Hong Kong, 1986. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1233361X.
Full textSmit, Robin, and n/a. "An Examination of Congestion in Road Traffic Emission Models and Their Application to Urban Road Networks." Griffith University. School of Environmental Science, 2007. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20070724.155421.
Full textSmit, Robin. "An Examination of Congestion in Road Traffic Emission Models and Their Application to Urban Road Networks." Thesis, Griffith University, 2007. http://hdl.handle.net/10072/365194.
Full textThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Environmental Planning
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Parsafard, Mohsen. "Space-Time Transportation System Modelling: from Traveler’s Characteristics to the Network Design Problem." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/6924.
Full textLee, Ka-Man. "Impact of Urbanisation on Estuarine Sandflats: Use of Ecological Indicators, Stable Isotope Enrichment and Network Modelling." Thesis, Griffith University, 2011. http://hdl.handle.net/10072/366733.
Full textThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Giffith School of Environment
Science, Environment, Engineering and Technology
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Matheussen, Bernt Viggo. "Effects of anthropogenic activities on snow distribution, and melt in an urban environment." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Engineering Science and Technology, 2004. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-243.
Full textIn many parts of the world snow melt runoff influence discharge from combined sewer overflows (CSO) and flooding in urban drainage systems. Despite this, urban snow hydrology is a field that has received little attention from the urban drainage community. The objectives of this research were to better understand urban snow hydrology and through field work and hydrological modelling quantify effects of anthropogenic activities (AA) on snow distribution, and melt in an urban environment. This means in principle how the presence (design geometry) and operation of roads and buildings influence the snow distribution and melt in urban areas. The Risvollan urban catchment (20 ha) located in Trondheim, Norway, was used as a study area. A literature review of urban snow hydrology was also carried out.
A gridded urban hydrology model (GUHM) was developed as part of the study. The principal idea of the GUHM is to subdivide an urban catchment into orthogonal equal area grid cells. The snow routine in the GUHM is based on an energy balance approach, which together with a soil-runoff routine is used to calculate a time series of rain, snow water equivalent (SWE), snow melt, and runoff, for each grid cell. In GUHM, processes such as snow clearing of roads, locally low albedos, heat/shadowing from buildings, and effects of slope and aspect are included in the model structure.
A technique for observing time series of snow covered area (SCA) for an urban catchment is presented. The method is based on image processing and neural network technology to calculate SCA from a time series of images taken from a tall building in the Risvollan catchment. It was shown that SCA on roads and roofs in general becomes more rapidly snow free during melt periods compared to the park areas of the Risvollan catchment. This can be explained by snow clearing of roads, snowdrift from roofs and high snow melt rates on roofs and roads. The high melt rates was attributed to locally low albedos in vicinity to roads, rooftop snow packs exposure to wind and solar radiation, in addition to anthropogenic heat release from the roofs themselves.
Field observations of SWE were carried out in the Risvollan catchment and it was shown that areal mean SWE located on/or nearby roads and buildings were significantly lower during mid and end of the winter, than in park areas. This can be attributed to higher melt rates caused by AA. A time series of SCA and SWE was obtained through field work for the period from 2000 to 2003 in the Risvollan catchment.
The GUHM was applied and calibrated for the Risvollan catchment for a three year period. Two seasons were used as validation period. Comparison between the simulated and observed SWE, SCA and runoff data showed that the GUHM was able to simulate snow accumulation and melt for whole seasons with short time resolution (1 hour) satisfactory.
The GUHM was used to quantify effects of AA on snow distribution and melt for six different land use scenarios in the Risvollan catchment for the period June 1998 to June 2003. The modelling results showed that when the area coverage of buildings and roads increased, the SCA and SWE more rapidly decreased during melt periods. Because of this more runoff will be produced in the early winter season (Jan-March) compared to if the catchment had been covered with only sparsely vegetated areas.
The simulation results showed that when the impervious surface covers of a catchment increase, the peak and volume runoff will also increase, as expected.
Both the field observations and the hydrological model study carried out in this work showed that AA lowers SCA and SWE more rapidly in an urban environment compared to more untouched terrain. The reasons for this are redistribution of snow, and strong snow melt rates on roads, roofs, and in snow deposit areas. Low albedos and anthropogenic heat release are the main reasons for the enhanced snow melt rates.
Ho, Siu-kui, and 何兆鉅. "Sensitivity of parameters in transportation modelling on the implication of network requirement: a casestudy of Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1986. http://hub.hku.hk/bib/B31975070.
Full textIshtiaq, Muhammad Saeed. "Journey time forecasting in urban networks." Thesis, University of Southampton, 1995. https://eprints.soton.ac.uk/421965/.
Full textMongeot, Helene. "Traffic incident modelling in mixed urban networks." Thesis, University of Southampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286751.
Full textBooks on the topic "Urban network modelling"
White, Roger. The artificial intelligence of urban dynamics: Neural network modelling of urban structure. [Toronto]: Centre for Urban and Community Studies, University of Toronto, 1989.
Find full textLundqvist, Lars. Network Infrastructure and the Urban Environment: Advances in Spatial Systems Modelling. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998.
Find full textNetwork Infrastructure and the Urban Environment: Advances in Spatial Systems Modelling. Springer, 2011.
Find full textL, Lundqvist, Mattsson L. G. 1947-, and Kim Tschangho John, eds. Network infrastructure and the urban environment: Advances in spatial systems modelling. Berlin: Springer, 1998.
Find full text(Editor), L. Lundqvist, L. G. Mattsson (Editor), and Tschangho John Kim (Editor), eds. Network Infrastructure and the Urban Environment: Advances in Spatial Systems Modelling : With 53 Figures and 52 Tables (Advances in Spatial Science). Springer-Verlag Telos, 1998.
Find full textBook chapters on the topic "Urban network modelling"
Ionescu, A., and Y. Candau. "Optimization of an Urban Air Monitoring Network." In Air Pollution Modelling and Simulation, 586–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04956-3_63.
Full textBrepols, Christoph, Heinrich Dahmen, Maja Lange, Annelie Sohr, Reinhold Kiesewski, and Richard Rohlfing. "Model-Based Sewer Network Control - Practical Experiences." In New Trends in Urban Drainage Modelling, 20–24. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99867-1_3.
Full textPeña-Guzmán, Carlos, Paula Balaguera, Nathalia Hernandez, and Ronal Sierra. "Redesign of Water Quality Network for the Urban Rivers in Salitre in Bogotá, Colombia, Using an Artificial Neural Network." In New Trends in Urban Drainage Modelling, 915–19. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99867-1_157.
Full textAyazpour, Zolal, Amin E. Bakhshipour, and Ulrich Dittmer. "Combined Sewer Flow Prediction Using Hybrid Wavelet Artificial Neural Network Model." In New Trends in Urban Drainage Modelling, 693–98. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99867-1_120.
Full textCaprario, Jakcemara, Aline Schuck Rech, Fabiane Andressa Tasca, and Alexandra Rodrigues Finotti. "Influence of Drainage Network and Compensatory Techniques on Urban Flooding Susceptibility." In New Trends in Urban Drainage Modelling, 717–22. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99867-1_124.
Full textKolehmainen, Mikko, Hannu Martikainen, Teri Hiltunen, and Juhani Ruuskanen. "Forecasting Air Quality Parameters Using Hybrid Neural Network Modelling." In Urban Air Quality: Measurement, Modelling and Management, 277–86. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-010-0932-4_30.
Full textCorti, A., and A. Senatore. "Project of an Air Quality Monitoring Network for Industrial Site in Italy." In Urban Air Quality: Measurement, Modelling and Management, 109–17. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-010-0932-4_12.
Full textPasini, Antonello, and Sergio Potestà. "Neural Network Modelling: Perspectives of Application for Monitoring and Forecasting Physical-Chemical Variables in the Boundary Layer." In Urban Air Pollution, 329–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-61120-9_26.
Full textKrajny, Ewa, Leszek Osródka, and Marek Wojtylak. "Application of Artificial Neural Network in Forecasting of Air Pollution in Large Industrial Urban Area." In Air Pollution Modelling and Simulation, 574–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04956-3_59.
Full textEl-Fadel, M., H. Sbayti, and I. Kaysi. "Modeling of Traffic-Induced Emission Inventories in Urban Areas. Effect of Roadway Network Aggregation Levels Traffic Management and Technology." In Air Pollution Modelling and Simulation, 187–202. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-04956-3_20.
Full textConference papers on the topic "Urban network modelling"
Castangia, M., and L. Guala. "Modelling and simulation of a PRT network." In URBAN TRANSPORT 2011. Southampton, UK: WIT Press, 2011. http://dx.doi.org/10.2495/ut110391.
Full text"Artificial Neural Network-Based Modelling for Daylight Evaluations." In 2018 Symposium on Simulation for Architecture and Urban Design. Society for Modeling and Simulation International (SCS), 2018. http://dx.doi.org/10.22360/simaud.2018.simaud.002.
Full textEe Chuo, Helen Sin, Yuan Han Swa, Min Keng Tan, Kit Guan Lim, Liawas Barukang, and Kenneth Tze Kin Teo. "Modelling Discrete Urban Traffic Network System with Cellular Automata." In 2021 IEEE 19th Student Conference on Research and Development (SCOReD). IEEE, 2021. http://dx.doi.org/10.1109/scored53546.2021.9652709.
Full textNovák, D., D. Lehký, L. Pan, and M. Cao. "Sensitivity analysis strategies for the artificial neural network modelling of engineering problems." In International Conference on Civil, Urban and Environmental Engineering. Southampton, UK: WIT Press, 2015. http://dx.doi.org/10.2495/cuee140191.
Full textSondi, Patrick, Dhavy Gantsou, and Sylvain Lecomte. "Mobile Ad Hoc Network-based Monitoring of Battlefields or Rescue Operations in Urban Scenarios." In 2010 European Modelling Symposium (EMS). IEEE, 2010. http://dx.doi.org/10.1109/ems.2010.74.
Full textZang, Lilin, Lei Jia, and Xiangxu Meng. "Modelling and Simulation of Traffic Signal Control for Urban Network." In 2009 Third International Symposium on Intelligent Information Technology Application. IEEE, 2009. http://dx.doi.org/10.1109/iita.2009.467.
Full textBai, Yun, Jian-feng Liu, Zhuang-zhi Sun, and Bao-hua Mao. "Analysis on Route Choice Behavior in Seamless Transfer Urban Rail Transit Network." In 2008 International Workshop on Modelling, Simulation and Optimization (WMSO). IEEE, 2008. http://dx.doi.org/10.1109/wmso.2008.24.
Full textMajor, Mark David, Heba O. Tannous, Sarah Al-Thani, Mahnoor Hasan, Adiba Khan, and Adele Salaheldin. "Macro and micro scale modelling of multi-modal transportation spatial networks in the city-state of Doha, Qatar." In Post-Oil City Planning for Urban Green Deals Virtual Congress. ISOCARP, 2020. http://dx.doi.org/10.47472/piqu7255.
Full textLi, Hanyu, Zhaobin Du, Lidan Chen, and Baorong Zhou. "A Spatial-temporal Charging Load Forecasting Modelling of Electric Vehicles Considering Urban Traffic Network." In 2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). IEEE, 2018. http://dx.doi.org/10.1109/isgt-asia.2018.8467975.
Full textLauster, Moritz, Peter Remmen, Marcus Fuchs, Jens Teichmann, Rita Streblow, and Dirk Müller. "Modelling long-wave radiation heat exchange for thermal network building simulations at urban scale using Modelica." In the 10th International Modelica Conference, March 10-12, 2014, Lund, Sweden. Linköping University Electronic Press, 2014. http://dx.doi.org/10.3384/ecp14096125.
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