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Pioneering research for sustainable development

CITEEC carries out pioneering research in civil engineering, materials, sustainability and infrastructure. Thanks to multidisciplinary projects and international collaborations, scientific papers are being published that address key challenges facing the sector. This section presents the main papers and results produced by our research groups.

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Pioneering research for sustainable development

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2018

Pazos-Pérez, Rafael Iván; Carballal, Adrián; Rabuñal-Dopico, Juan R.; Mures, Omar A.; García-Vidaurrázaga, María D.

Predicting vertical urban growth using genetic evolutionary algorithms in Tokyo's Minato ward Journal Article

In: Journal of Urban Planning and Development, vol. 144, no. 1, 2018, ISSN: 07339488, (cited By 11).

Abstract | Links | BibTeX | Tags: computer simulation; future prospect; genetic algorithm; location-allocation model; numerical model; prediction; spatial analysis; urban development; urban growth; urban morphology, Evolutionary algorithms; Forecasting; Genetic algorithms; Office buildings; Tall buildings, Evolutionary models; High rise building; High rise development; Minato Ward; Specific areas; Tokyo; Urban morphogenesis; Vertical growth, Honshu; Japan; Kanto; Minato; Tokyo [Kanto]; Tokyo [Tokyo (PRF)], Urban growth

@article{Perez2018,

title = {Predicting vertical urban growth using genetic evolutionary algorithms in Tokyo's Minato ward},

author = {Rafael Iván Pazos-Pérez and Adrián Carballal and Juan R. Rabuñal-Dopico and Omar A. Mures and María D. García-Vidaurrázaga},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85035762081&doi=10.1061%2f%28ASCE%29UP.1943-5444.0000413&partnerID=40&md5=fa6897430d3ff851aff35ea29e9ccbbc},

doi = {10.1061/(ASCE)UP.1943-5444.0000413},

issn = {07339488},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Journal of Urban Planning and Development},

volume = {144},

number = {1},

publisher = {American Society of Civil Engineers (ASCE)},

abstract = {This article explores the use of evolutionary genetic algorithms to predict scenarios of urban vertical growth in large urban centers. Tokyo's Minato Ward is used as a case study because it has been one of the fastest growing skylines over the last 20 years. This study uses a genetic algorithm that simulates the vertical urban growth of MinatoWard to make predictions from pre-established inputted parameters. The algorithm estimates not only the number of future high-rise buildings but also the specific areas in the ward that are more likely to accommodate new high-rise developments in the future. The evolutionary model results are compared with ongoing high-rise developments in order to evaluate the accuracy of the genetic algorithm in simulating future vertical urban growth. The results of this study show that the use of genetic evolutionary computation is a promising way to predict scenarios of vertical urban growth in terms of location as well as the number of future buildings. © 2017 American Society of Civil Engineers.},

note = {cited By 11},

keywords = {computer simulation; future prospect; genetic algorithm; location-allocation model; numerical model; prediction; spatial analysis; urban development; urban growth; urban morphology, Evolutionary algorithms; Forecasting; Genetic algorithms; Office buildings; Tall buildings, Evolutionary models; High rise building; High rise development; Minato Ward; Specific areas; Tokyo; Urban morphogenesis; Vertical growth, Honshu; Japan; Kanto; Minato; Tokyo [Kanto]; Tokyo [Tokyo (PRF)], Urban growth},

pubstate = {published},

tppubtype = {article}

}