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Gerardo Colín-García, Enrique Palacios-Vélez, Adolfo López-Pérez, Martín Alejandro Bolaños-González, Héctor Flores-Magdaleno, Roberto Ascencio-Hernández and Enrique Inoscencio Canales-Islas
Assessing the impact of climate change is essential for developing water resource management plans, especially in areas facing severe issues regarding ecosystem service degradation. This study assessed the effects of climate change on the hydrological ba...
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Laurent Risser, Agustin Martin Picard, Lucas Hervier and Jean-Michel Loubes
The problem of algorithmic bias in machine learning has recently gained a lot of attention due to its potentially strong impact on our societies. In much the same manner, algorithmic biases can alter industrial and safety-critical machine learning applic...
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Tiago P. Pagano, Rafael B. Loureiro, Fernanda V. N. Lisboa, Rodrigo M. Peixoto, Guilherme A. S. Guimarães, Gustavo O. R. Cruz, Maira M. Araujo, Lucas L. Santos, Marco A. S. Cruz, Ewerton L. S. Oliveira, Ingrid Winkler and Erick G. S. Nascimento
One of the difficulties of artificial intelligence is to ensure that model decisions are fair and free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and mitigate algorithmic unfairness and bias. This study examines ...
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Youssef Brouziyne, Ali El Bilali, Terence Epule Epule, Victor Ongoma, Ahmed Elbeltagi, Jamal Hallam, Fouad Moudden, Maha Al-Zubi, Vincent Vadez and Rachael McDonnell
North Africa (NA) is supposed to lower emissions in its agriculture to honor climate action commitments and to impulse sustainable development across Africa. Agriculture in North Africa has many assets and challenges that make it fit to use the tools of ...
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Yiwen Li, Juan Liu, Pengfei Lin, Hailong Liu, Zipeng Yu, Weipeng Zheng and Jinlei Chen
Marine heatwaves (MHWs) are becoming increasingly frequent and intense around China, impacting marine ecosystems and coastal communities. Accurate forecasting of MHWs is crucial for their management and mitigation. In this study, we assess the forecastin...
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Usman Mohseni, Prasit G. Agnihotri, Chaitanya B. Pande and Bojan Durin
Understanding the likely impacts of climate change (CC) and Land Use Land Cover (LULC) on water resources (WR) is critical for a water basin?s mitigation. The present study intends to quantify the impact of (CC) and (LULC) on the streamflow (SF) of the P...
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Cheng Zhu, Shaoqi Wang, Na He, Hui Sun, Linjuan Xu and Filip Gurkalo
To improve the accuracy of debris flow forecasts and serve as disaster prevention and mitigation, an accurate and intelligent early warning method of debris flow initiation based on the IGWO-LSTM algorithm is proposed. First, the entropy method is employ...
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André M. Claro, André Fonseca, Helder Fraga and João A. Santos
The susceptibility to precipitation extreme events (PEEs) and aridity in the Iberian Peninsula (IP) were assessed over a long historical period (1950?2022). Eight extreme precipitation and two aridity indices were calculated. Furthermore, two newly devel...
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Tiago P. Pagano, Rafael B. Loureiro, Fernanda V. N. Lisboa, Gustavo O. R. Cruz, Rodrigo M. Peixoto, Guilherme A. de Sousa Guimarães, Ewerton L. S. Oliveira, Ingrid Winkler and Erick G. Sperandio Nascimento
The majority of current approaches for bias and fairness identification or mitigation in machine learning models are applications for a particular issue that fails to account for the connection between the application context and its associated sensitive...
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Nikzad Chizari, Keywan Tajfar and María N. Moreno-García
In today?s technology-driven society, many decisions are made based on the results provided by machine learning algorithms. It is widely known that the models generated by such algorithms may present biases that lead to unfair decisions for some segments...
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