Prediction method of construction land expansion speed of ecological city based on BP neural network. (31st January 2022)
- Record Type:
- Journal Article
- Title:
- Prediction method of construction land expansion speed of ecological city based on BP neural network. (31st January 2022)
- Main Title:
- Prediction method of construction land expansion speed of ecological city based on BP neural network
- Authors:
- Li, Anlin
Niu, Lede
Zhou, Yan - Abstract:
- In order to solve the problems of low accuracy and poor convergence of traditional urban construction land expansion speed prediction, a new method based on BP neural network for ecological city construction land expansion speed prediction is proposed. On the basis of driving forces state responses (DSR) research framework model, this paper analyses the main components of the driving mechanism model of urban construction land expansion, finds out the driving factors, and verifies the unit root of its time series, as well as causality verification and screening, to establish the driving mechanism model of urban construction land expansion. After preprocessing the data in the model, the BP neural network is constructed to predict the expansion speed of urban construction land. The experimental results show that the proposed method has better convergence and higher prediction accuracy, which provides a reference for related research.
- Is Part Of:
- International journal of environmental technology and management. Volume 25:Number 1/2(2022)
- Journal:
- International journal of environmental technology and management
- Issue:
- Volume 25:Number 1/2(2022)
- Issue Display:
- Volume 25, Issue 1/2 (2022)
- Year:
- 2022
- Volume:
- 25
- Issue:
- 1/2
- Issue Sort Value:
- 2022-0025-NaN-0000
- Page Start:
- 108
- Page End:
- 121
- Publication Date:
- 2022-01-31
- Subjects:
- DSR -- BP neural network -- ecological city -- construction land -- expansion speed prediction
Environmental management -- Periodicals
Green technology -- Periodicals
333.705 - Journal URLs:
- http://www.inderscience.com/ ↗
http://www.inderscience.com/jhome.php?jcode=ijetm ↗ - Languages:
- English
- ISSNs:
- 1466-2132
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 18619.xml