Tackling climate change with machine learning

D Rolnick, PL Donti, LH Kaack, K Kochanski… - ACM Computing …, 2022 - dl.acm.org
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

Machine learning for sustainable energy systems

PL Donti, JZ Kolter - Annual Review of Environment and …, 2021 - annualreviews.org
In recent years, machine learning has proven to be a powerful tool for deriving insights from
data. In this review, we describe ways in which machine learning has been leveraged to …

Computational sustainability: Computing for a better world and a sustainable future

C Gomes, T Dietterich, C Barrett, J Conrad… - Communications of the …, 2019 - dl.acm.org
Computational sustainability: computing for a better world and a sustainable future Page 1 56
COMMUNICATIONS OF THE ACM | SEPTEMBER 2019 | VOL. 62 | NO. 9 Computational …

Reducing adverse impacts of Amazon hydropower expansion

AS Flecker, Q Shi, RM Almeida, H Angarita… - Science, 2022 - science.org
Proposed hydropower dams at more than 350 sites throughout the Amazon require strategic
evaluation of trade-offs between the numerous ecosystem services provided by Earth's …

Artificial intelligence for social good: A survey

ZR Shi, C Wang, F Fang - arXiv preprint arXiv:2001.01818, 2020 - arxiv.org
Artificial intelligence for social good (AI4SG) is a research theme that aims to use and
advance artificial intelligence to address societal issues and improve the well-being of the …

Strategic planning of hydropower development: balancing benefits and socioenvironmental costs

RM Almeida, RJP Schmitt, A Castelletti… - Current Opinion in …, 2022 - Elsevier
Hydropower continues to expand globally as the power sector transitions away from carbon-
intensive fossil fuels. New dam sites vary widely in the magnitude of their adverse effects on …

Deep probabilistic accelerated evaluation: A robust certifiable rare-event simulation methodology for black-box safety-critical systems

M Arief, Z Huang, GKS Kumar, Y Bai… - International …, 2021 - proceedings.mlr.press
Evaluating the reliability of intelligent physical systems against rare safety-critical events
poses a huge testing burden for real-world applications. Simulation provides a useful …

Energy development reveals blind spots for ecosystem conservation in the Amazon Basin

EP Anderson, T Osborne… - Frontiers in Ecology …, 2019 - Wiley Online Library
Energy development–as manifested by the proliferation of hydroelectric dams and increased
oil and gas exploration–is a driver of change in Amazonian ecosystems. However …

Scaling up pareto optimization for tree structures with affine transformations: Evaluating hybrid floating solar-hydropower systems in the amazon

M Grimson, R Almeida, Q Shi, Y Bai… - Proceedings of the …, 2024 - ojs.aaai.org
Sustainability challenges inherently involve the consideration of multiple competing
objectives. The Pareto frontier–the set of all optimal solutions that cannot be improved with …

Multi-objective evolutionary algorithm in tables for placement of SCADA and PMU considering the concept of Pareto Frontier

MP Vigliassi, JAD Massignan, ACB Delbem… - International Journal of …, 2019 - Elsevier
The main concern of Metering Systems Planning (MSP) for state estimation is the
determination of the number, type and location to install metering devices to attend …