A machine learning approach for integration of spatial development plans based on natural language processing

Iwona Kaczmarek; Adam Iwaniak; Aleksandra Świetlicka; Mateusz Piwowarczyk; Adam Nadolny

doi:10.1016/j.scs.2021.103479

Scientific Information System of the Poznań University of Technology

PL EN

Main page / Publications / A machine learning approach for integration of spatial development plans based on natural language processing

Submit a comment

Article

Download BibTeX

Title

A machine learning approach for integration of spatial development plans based on natural language processing

Authors

Iwona Kaczmarek
Adam Iwaniak
Aleksandra Świetlicka (WARiE) ^{[ 1 ][ 2.2 ][ P ]}
Mateusz Piwowarczyk
Adam Nadolny

^{[ 1 ]} Instytut Automatyki i Robotyki, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | ^{[ P ]} employee

Scientific discipline (Law 2.0)

[2.2] Automation, electronics, electrical engineering and space technology

Year of publication

2022

Published in

Sustainable Cities and Society

Journal year: 2022 | Journal volume: vol. 76

Article type

scientific article

Publication language

english

Keywords

EN

spatial planning
spatial development plan
unsupervised machine learning
LSTM
GRU
neural networks

Date of online publication

03.11.2021

Pages (from - to)

103479-1 - 103479-44

DOI

10.1016/j.scs.2021.103479

URL

https://www.sciencedirect.com/science/article/pii/S2210670721007460#!

Comments

Article Number: 103479

License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

Open Access Mode

czasopismo hybrydowe

Open Access Text Version

final author's version

Date of Open Access to the publication

in press

Ministry points / journal

100

Impact Factor

11,7

System created by Poznań University of Technology and Poznan Supercomputing and Networking Center

Log in through eKonto to add to SIS