Results 41 to 50 of about 30,221 (232)

Geospatial XAI: A Review

ISPRS International Journal of Geo-Information, 2023
Explainable Artificial Intelligence (XAI) has the potential to open up black-box machine learning models. XAI can be used to optimize machine learning models, to search for scientific findings, or to improve the understandability of the AI system for the
Cédric Roussel, Klaus Böhm
doaj   +1 more source

Artificial Intelligence–Driven and Digital Practices for Circular Business and Finance: Insights for Advancing Hubs for Circularity

Business Strategy and the Environment, EarlyView.
ABSTRACT The emerging concept of Hubs for Circularity (H4Cs) presents an opportunity to create collaborative, self‐sustaining regional industrial ecosystems that drive circular economy transitions at scale. However, the operationalisation of H4Cs faces financial, organisational and data‐driven challenges.
Aditya Tripathi, Marcos R. Machado, Laura Spierdijk, Devrim Murat Yazan   +3 more
wiley   +1 more source

Applying spatial reasoning to topographical data with a grounded geographical ontology [PDF]

, 2007
Grounding an ontology upon geographical data has been pro- posed as a method of handling the vagueness in the domain more effectively. In order to do this, we require methods of reasoning about the spatial relations between the regions within the data ...
A.C. Varzi, A.C. Varzi, B. Bennett, B. Bennett, D. Dubois, D.A. Randell, F. Fonseca, H. Blum, J. Almendros-Jimenez, J. Jaffar, J. Wielemaker, J.F. Allen, J.L. Bentley, L. Laera, M. Giritli, M. Held, M. Mantyla, M. Taddeo, M.J. Egenhofer, M.J. Egenhofer, M.P. Taylor, N. Guarino, S. Harnad, X. Bai, X. Bai, Y.R. Ge   +25 more
core   +1 more source

Strengthening urban resilience in China through underground infrastructures management: Addressing global climate challenges with technological solutions

Deep Underground Science and Engineering, EarlyView.
This paper explores how climate‐resilient technologies, such as smart grids, digital twins, and self‐healing materials, can enhance urban resilience. It highlights the urgent need for proactive planning, public‐private collaboration, and data‐driven innovation to future‐proof underground infrastructure amid accelerating climate and urban pressures ...
Kai Chen Goh, Tonni Agustiono Kurniawan, Christia Meidiana, Abdelkader Anouzla, Faissal Aziz, Imran Ali, Joan Cecilia C. Casila, M. Imran Khan, Dongdong Zhang, Meihui Jiang, Mohd Hafiz Dzarfan Othman, Md Munir Hayet Khan, Kasun Kumara Dissanayake   +12 more
wiley   +1 more source

Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow

Journal of Big Data
The increasing demand for electricity presents substantial challenges in power system planning, particularly optimizing the Optimal Power Flow (OPF) problem.
Huangying Wu, Yi Chen, Zhennao Cai, Ali Asghar Heidari, Huiling Chen, Guoxi Liang   +5 more
doaj   +1 more source

An evolutionary Nelder–Mead slime mould algorithm with random learning for efficient design of photovoltaic models

Energy Reports, 2021
The efficiency of solar cells in converting solar energy into electrical energy can be improved by efficient and accurate solar photovoltaic cell modelling.
Xuemeng Weng, Ali Asghar Heidari, Guoxi Liang, Huiling Chen, Xinsheng Ma   +4 more
doaj   +1 more source

What Happens When a Black Swan Meets a Gray Rhino? Reflections on the Evaluation Market in Transformative Times

New Directions for Evaluation, EarlyView.
ABSTRACT This chapter examines recent disruptions in the U.S. evaluation market through the combined lens of the Evaluation Marketplace Framework and the Black Swan/Gray Rhino typology. We argue that the Trump Administration's abrupt reduction in federal evaluation commissioning constitutes a Black Swan shock, whereas the long‐anticipated technological
Steffen Bohni Nielsen, Sebastian Lemire
wiley   +1 more source

A Wavelet PM2.5 Prediction System Using Optimized Kernel Extreme Learning with Boruta-XGBoost Feature Selection

Mathematics, 2022
The fine particulate matter (PM2.5) concentration has been a vital source of info and an essential indicator for measuring and studying the concentration of other air pollutants. It is crucial to realize more accurate predictions of PM2.5 and establish a
Ali Asghar Heidari, Mehdi Akhoondzadeh, Huiling Chen   +2 more
doaj   +1 more source

Workforce Representation and Service in Shortage Areas: Outcomes of a HBCU College of Dentistry, Class 2004–2023

Journal of Dental Education, EarlyView.
ABSTRACT Purpose This study examines Howard University College of Dentistry's (HUCD) contributions to dental education, focusing on its role in strengthening workforce representation, expanding access to care in dental health professional shortage areas (DHPSAs) and medically underserved areas (MUAs), and addressing persistent oral health disparities ...
Marzia Mustamand, Minxuan Lan, Esther Childers, Cheryl Fryer, Kingsley Kanjin, Emma Ta‐Zhou, Najah Abduh, Whittley Deleveaux, Raheem Pierre, Gail Cherry‐Peppers, Reginald Salter, Deborah Nixon‐Willis, Tanya Greenfield, Dexter Woods, Andrea Jackson, Xinbin Gu   +15 more
wiley   +1 more source

Q-learning enhanced differential evolution for feature selection in high-dimensional medical data analysis

Journal of King Saud University: Computer and Information Sciences
Feature selection (FS) plays a crucial role in improving predictive performance and computational efficiency in high-dimensional medical data analysis.
Chenliang Huang, Mingjing Wang, Heidari Ali Asghar, Zhilin Wang, Huiling Chen   +4 more
doaj   +1 more source