Machine learning in natural and engineered water systems
R Huang, C Ma, J Ma, X Huangfu, Q He - Water Research, 2021 - Elsevier
Water resources of desired quality and quantity are the foundation for human survival and
sustainable development. To better protect the water environment and conserve water …
sustainable development. To better protect the water environment and conserve water …
A survey on river water quality modelling using artificial intelligence models: 2000–2020
There has been an unsettling rise in the river contamination due to the climate change and
anthropogenic activities. Last decades' research has immensely focussed on river basin …
anthropogenic activities. Last decades' research has immensely focussed on river basin …
[HTML][HTML] The future of sensitivity analysis: an essential discipline for systems modeling and policy support
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling.
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …
[HTML][HTML] Designing diversified renewable energy systems to balance multisector performance
JM Gonzalez, JE Tomlinson, EA Martínez Ceseña… - Nature …, 2023 - nature.com
Renewable energy system development and improved operation can mitigate climate
change. In many regions, hydropower is called to counterbalance the temporal variability of …
change. In many regions, hydropower is called to counterbalance the temporal variability of …
An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …
applications, there remains a need to develop more reliable and intelligent expert systems …
Introductory overview: Optimization using evolutionary algorithms and other metaheuristics
Environmental models are used extensively to evaluate the effectiveness of a range of
design, planning, operational, management and policy options. However, the number of …
design, planning, operational, management and policy options. However, the number of …
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …
sustainability of water resources. The literature has shown great potential for nature-inspired …
[HTML][HTML] Exploring trade-offs among the multiple benefits of green-blue-grey infrastructure for urban flood mitigation
Climate change is presenting one of the main challenges to our planet. In parallel, all
regions of the world are projected to urbanise further. Consequently, sustainable …
regions of the world are projected to urbanise further. Consequently, sustainable …
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 …
Climate adaptation as a control problem: Review and perspectives on dynamic water resources planning under uncertainty
Climate change introduces substantial uncertainty to water resources planning and raises
the key question: when, or under what conditions, should adaptation occur? A number of …
the key question: when, or under what conditions, should adaptation occur? A number of …