• HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
Wednesday, November 5, 2025
BIOENGINEER.ORG
No Result
View All Result
  • Login
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
No Result
View All Result
Bioengineer.org
No Result
View All Result
Home NEWS Science News Biology

A genetic algorithm predicts the vertical growth of cities

Bioengineer by Bioengineer
May 25, 2018
in Biology
Reading Time: 3 mins read
0
Share on FacebookShare on TwitterShare on LinkedinShare on RedditShare on Telegram
IMAGE

Credit: Ivan Pazos et al.

The increase of skyscrapers in a city resembles the development of some living systems. Spanish researchers have created an evolutionary genetic algorithm that, on the basis of the historical and economic data of an urban area, can predict what its skyline could look like in the coming years. The method has been applied successfully to the thriving Minato Ward, in Tokyo.

Scientists have realized that the growth of cities follows patterns similar to those of certain self-organized biological systems. Inspired by nature, they have developed genetic algorithms that predict how the number of skyscrapers and other buildings in an urban area will increase.

"We operate within evolutionary computation, a branch of artificial intelligence and machine learning that uses the basic rules of genetics and Darwin's natural selection logic to make predictions," explains architect Ivan Pazos.

"In this type of computing, a multitude of possible solutions to a problem are randomly combined," adds the expert, who currently works for a Japanese architectural firm, "and a selection system is choosing the best results. This operation is repeated again and again until the algorithms get the most accurate results."

In this way, Pazos and a team of researchers from the University of A Coruña (Spain) have created algorithms -based on other standard genetic algorithms- that learn the growth patterns of urban districts using historical data from the construction sector and different economic parameters.

The study, published in the Journal of Urban Planning and Development, has focused on one of the neighbourhoods with the highest vertical growth in the world in recent years: the Minato Ward, in Tokyo, where the headquarters of multinational companies such as Mitsubishi, Honda, NEC, Toshiba or Sony, are located. "This methodology could have been applied to any other city with a high number of skyscrapers," Pazos points out.

In 2015, once all the information had been gathered, the authors created a series of maps and 3D representations of Minato to be able to predict the number of buildings and their probable locations within this booming ward in the following years during the 2016-2019 period.

"The predictions of the algorithm have been very accurate with respect to the actual evolution of the Minato skyline in 2016 and 2017," says Pazos, who comments: "Now we are evaluating their accuracy for 2018 and 2019 and it seems, according to the observations, that they will be 80% correct."

According to the authors, the algorithm not only estimates the number of future skyscrapers in a neighbourhood of the city, but also the specific areas where they will be most likely be located.

"The final conclusion of the study is that evolutionary computation seems to be able to find growth patterns that are not obvious in complex urban systems, and by means of its subsequent application, it serves the function of predicting possible scenarios for the evolution of cities." concludes Pazos.

###

References:

Rafael Ivan Pazos Perez, AdrianCarballal, Juan R. Rabuñal, Omar A. Mures and María D. García-Vidaurrázaga. "Predicting Vertical Urban Growth Using Genetic Evolutionary Algorithms in Tokyo's Minato Ward". Journal of Urban Planning and Development 144: 1, March 2018.

Media Contact

SINC
[email protected]
34-914-251-820
@FECYT_Ciencia

http://www.fecyt.es/fecyt/home.do

Original Source

http://www.agenciasinc.es/en/News/A-genetic-algorithm-predicts-the-vertical-growth-of-cities

Share12Tweet7Share2ShareShareShare1

Related Posts

blank

Breakthrough in Bone Regeneration: Stem Cells from Fat Tissue Pave the Way

November 5, 2025
blank

Evaluating PR1 Genes in Mung Bean’s Pathogen Response

November 5, 2025

Unveiling Wheat’s Defense Against WSMV: A Transcriptomic Study

November 4, 2025

Unveiling Wheat’s Defense Against WSMV: A Transcriptomic Study

November 4, 2025
Please login to join discussion

POPULAR NEWS

  • Sperm MicroRNAs: Crucial Mediators of Paternal Exercise Capacity Transmission

    1298 shares
    Share 518 Tweet 324
  • Stinkbug Leg Organ Hosts Symbiotic Fungi That Protect Eggs from Parasitic Wasps

    313 shares
    Share 125 Tweet 78
  • ESMO 2025: mRNA COVID Vaccines Enhance Efficacy of Cancer Immunotherapy

    205 shares
    Share 82 Tweet 51
  • New Study Suggests ALS and MS May Stem from Common Environmental Factor

    138 shares
    Share 55 Tweet 35

About

We bring you the latest biotechnology news from best research centers and universities around the world. Check our website.

Follow us

Recent News

Nonuniform Cooling Impacts Polymer Quality in 3D Printing

Breakthrough in Bone Regeneration: Stem Cells from Fat Tissue Pave the Way

Large Language Models Boost Human-Robot Flexible Scheduling

Subscribe to Blog via Email

Enter your email address to subscribe to this blog and receive notifications of new posts by email.

Join 67 other subscribers
  • Contact Us

Bioengineer.org © Copyright 2023 All Rights Reserved.

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In
No Result
View All Result
  • Homepages
    • Home Page 1
    • Home Page 2
  • News
  • National
  • Business
  • Health
  • Lifestyle
  • Science

Bioengineer.org © Copyright 2023 All Rights Reserved.