A novel approach based on machine learning and public engagement to predict water-scarcity risk in urban areas
Climate change, population growth and urban sprawl have put a strain on water supplies across the world, making it difficult to meet water demand, especially in city regions where more than half of the world’s population now reside. Due to the complex urban fabric, conventional techniques should be...
Main Authors: | Hanoon, Sadeq Khaleefah, Abdullah, Ahmad Fikri, M. Shafri, Helmi Z., Wayayok, Aimrun |
---|---|
Format: | Article |
Published: |
Multidisciplinary Digital Publishing Institute
2022
|
Similar Items
-
A Novel Approach Based on Machine Learning and Public Engagement to Predict Water-Scarcity Risk in Urban Areas
by: Sadeq Khaleefah Hanoon, et al.
Published: (2022-12-01) -
Using scenario modelling for adapting to urbanization and water
scarcity: towards a sustainable city in semi-arid areas
by: Hanoon, Sadeq Khaleefah, et al.
Published: (2022) -
Urban Growth Forecast Using Machine Learning Algorithms and GIS-Based Novel Techniques: A Case Study Focusing on Nasiriyah City, Southern Iraq
by: Sadeq Khaleefah Hanoon, et al.
Published: (2023-02-01) -
Comprehensive Vulnerability Assessment of Urban Areas Using an Integration of Fuzzy Logic Functions: Case Study of Nasiriyah City in South Iraq
by: Sadeq Khaleefah Hanoon, et al.
Published: (2022-06-01) -
Content validity-based evaluation criteria system for siting wind-solar plants
by: Sachit, Mourtadha Sarhan, et al.
Published: (2024)