Results 91 to 100 of about 15,829,318 (284)

Probabilistic Fuzzy Goal Programming Problems Involving Pareto Distribution: Some Additive Approaches

Fuzzy Information and Engineering, 2015
In many real-life decision making problems, probabilistic fuzzy goal programming problems are used where some of the input parameters of the problem are considered as random variables with fuzzy aspiration levels.
S.K. Barik
doaj   +1 more source

Consensus Formation and Change are Enhanced by Neutrality

Advanced Science, EarlyView.
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag, Janina A. Hoffmann, Tim Rogers, Christian A. Yates   +3 more
wiley   +1 more source

From Pores to Pavement: Advanced Modeling of Aluminosilicates for Scalable Carbon Capture in Concrete

Advanced Science, EarlyView.
This study presents a transferable modeling framework for carbon capture using aluminosilicates, integrating Universal Isotherm Modeling with experimental data. It reveals how ultramicropores, alumina content, and amine functionalization influence CO2 adsorption energetics.
Pooja Anil Kumar Nair, Jéssica de O. N. Ribeiro, Murilo Daniel de Mello Innocentini, Kevin Paine, Juliana Calabria‐Holley   +4 more
wiley   +1 more source

A Mathematical Framework for Probabilistic Effects: The Model

This study introduces a mathematical framework that combines deterministic effects and probabilistic distributions to model complex systems. Using the expression P(y/x) = Δ(x) · f(x), the framework connects event magnitude with probability behavior and can be applied to biological, physical, and environmental systems. The model also supports extensions
openaire   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Synergistic Spin‐Polarization and Single‐Atom Engineering in Magnetic Heterojunctions for Efficient Solar Water Splitting

Advanced Science, EarlyView.
High‐throughput screening led to the identification of 67 Z‐scheme heterojunctions (comprising 2D magnetic transition metal halides and non‐magnetic transition metal chalcogenides). For CrI3/MoTe2 and CrI3/WTe2, electronic structure analysis demonstrated that synergistic crystallographic point group and built‐in electric field effects generate a ...
Hongyang Ren, Zhenzhou Guo, Huirong Wu, Peilin Huang, Jie Yang, Jie Zhang, Guangqian Ding, Hongkuan Yuan, Biao Wang   +8 more
wiley   +1 more source

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

Advanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li, Kelly Yichen Li, Chiara Nicoletti, Stephen Kwok‐Wing Tsui, Pier Lorenzo Puri, Qin Cao, Kevin Y. Yip   +6 more
wiley   +1 more source

A Hybrid Probabilistic-Neutrosophic Adaptive Convergence Model for Analyzing Innovative Performance of Agricultural Technology Enterprises in the Digital Economy [PDF]

Neutrosophic Sets and Systems
This paper introduces a novel mathematical framework that integrates hybrid probabilistic-neutrosophic logic with adaptive rough ideal statistical convergence (AR-I st) to model and analyze the dynamic performance of innovative agricultural technology ...
Hongyan Xie
doaj   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Knightian Forecasting: Mathematical Models of Ambiguity and the Limits of Probabilistic Prediction

FUTURES & FORESIGHT SCIENCE
ABSTRACT This paper develops a theoretical framework for forecasting under Knightian uncertainty, where probabilities are not uniquely defined, and ambiguity fundamentally constrains predictive inference. Traditional forecasting relies on single‐model probabilistic structures, yet such approaches are often fragile in environments ...
openaire   +1 more source