A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects
I Palomares, E Martínez-Cámara, R Montes… - Applied …, 2021 - Springer
Abstract The17 Sustainable Development Goals (SDGs) established by the United Nations
Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity …
Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity …
A transdisciplinary review of deep learning research and its relevance for water resources scientists
C Shen - Water Resources Research, 2018 - Wiley Online Library
Deep learning (DL), a new generation of artificial neural network research, has transformed
industries, daily lives, and various scientific disciplines in recent years. DL represents …
industries, daily lives, and various scientific disciplines in recent years. DL represents …
Machine learning for risk and resilience assessment in structural engineering: Progress and future trends
Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …
to increased exposure and vulnerability of structural and infrastructure systems to hazards …
Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm
Monthly streamflow forecasting is required for short-and long-term water resources
management especially in extreme events such as flood and drought. Therefore, there is …
management especially in extreme events such as flood and drought. Therefore, there is …
Artificial intelligence based models for stream-flow forecasting: 2000–2015
Summary The use of Artificial Intelligence (AI) has increased since the middle of the 20th
century as seen in its application in a wide range of engineering and science problems. The …
century as seen in its application in a wide range of engineering and science problems. The …
Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
Monthly stream-flow forecasting can yield important information for hydrological applications
including sustainable design of rural and urban water management systems, optimization of …
including sustainable design of rural and urban water management systems, optimization of …
Genetic programming in water resources engineering: A state-of-the-art review
The state-of-the-art genetic programming (GP) method is an evolutionary algorithm for
automatic generation of computer programs. In recent decades, GP has been frequently …
automatic generation of computer programs. In recent decades, GP has been frequently …
Daily streamflow forecasting by machine learning methods with weather and climate inputs
Weather forecast data generated by the NOAA Global Forecasting System (GFS) model,
climate indices, and local meteo-hydrologic observations were used to forecast daily …
climate indices, and local meteo-hydrologic observations were used to forecast daily …
Short-term streamflow forecasting using hybrid deep learning model based on grey wolf algorithm for hydrological time series
HC Kilinc, A Yurtsever - Sustainability, 2022 - mdpi.com
The effects of developing technology and rapid population growth on the environment have
been expanding gradually. Particularly, the growth in water consumption has revealed the …
been expanding gradually. Particularly, the growth in water consumption has revealed the …
Multi-objective management of saltwater intrusion in coastal aquifers using genetic programming and modular neural network based surrogate models
J Sreekanth, B Datta - Journal of hydrology, 2010 - Elsevier
Surrogate model based methodologies are developed for evolving multi-objective
management strategies for saltwater intrusion in coastal aquifers. Two different surrogate …
management strategies for saltwater intrusion in coastal aquifers. Two different surrogate …