Results 191 to 200 of about 29,055 (302)
Deep Underground Science and Engineering, EarlyView.Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley +1 more source
Deep Underground Science and Engineering, EarlyView.Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley +1 more source
In 2007, Liao finished his Ph.d. dissertation[18](Liao 2007) entitled “The Solutions on Multi-choice Games”. Chapter 1 of the dissertation mainly worked on two special cases of the H&R multi-choice Shapley value. One assumes that the weight function w(j)
Hsiao, Chih-Ru
core
Deep Underground Science and Engineering, EarlyView.This research proposes an interpretable hybrid stacking ensemble framework, optimized by the Sparrow Search Algorithm, to enhance hard rock pillar stability prediction. By integrating six machine learning models—k‐nearest neighbors, support vector machines, random forests, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and Light Gradient ...
Ning Wang +3 more
wiley +1 more source
Weighted Average Lexicographic Values for Share Sets and Balanced Cooperative Games
Inspired by Kalai-Samet [4] and Tijs [11], weighted average lexicographic values are introduced for share sets and for cores of cooperative games using induction arguments. Continuity properties and monotonicity properties of these weighted lexicographic
Tijs, S.H., Torre, A., Caprari, E.
core
Machine‐Learning‐Enabled Wood with Nanopump Functionalization for Solar Interfacial Evaporation
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.This study employed machine learning to design an iron‐cobalt‐carbon‐wood photothermal material, achieving high‐efficiency evaporation at 2.807 kg m−2 h−1 and excellent salt resistance. The integrated system increased the daily water production efficiency of solar distillation by 1.5 times, providing an innovative solution for sustainable seawater ...
Chaohai Wang +10 more
wiley +1 more source
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.This work systematically reviews the key factors influencing the performance of low‐temperature NH3‐SCR. The mechanism and challenges of defect engineering strategies, such as oxygen vacancies, heteroatom doping, crystal facet exposure, and surface reconstruction, in controlling both activity and selectivity were analyzed.
Rongrong Kan +3 more
wiley +1 more source
The use of the Shapley value in planning innovative projects
Nowoczesne Systemy Zarządzania, 2013 Tomasz JANICKI
doaj +1 more source
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.First‐principles DFT calculations and machine learning analysis show that heteroatom doping of graphene (G) significantly enhances the stabilization of transition‐metal single atoms by strengthening metal–support interactions and increasing charge transfer. N‐doped G exhibits higher adsorption energies, lower d‐band centers, and shorter TM–G bonds than
Sajjad Ali +3 more
wiley +1 more source
ESC Heart Failure, Volume 12, Issue 2, Page 859-868, April 2025.Abstract Aims Natriuretic peptide‐based pre‐heart failure screening has been proposed in recent guidelines. However, an effective strategy to identify screening targets from the general population, more than half of which are at risk for heart failure or pre‐heart failure, has not been well established.
Yuichiro Mori +5 more
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