Modeling decision-making under uncertainty with qualitative outcomes. by Nachshon Korem, Or Duek, Ruonan Jia, Emily Wertheimer, Sierra Metviner, Michael Grubb, Ifat Levy

“…Modeling decision-making under uncertainty typically relies on quantitative outcomes. …”
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MODEL DECISION MAKING BY INTELLECTUAL SYSTEM ON BASE OF THE ILLDEFINED PROCEDURAL SEMANTIC NETWORK by T. T. Abduragimov, A. I. Halilov

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THE APPLICATION OF MATHEMATICAL METHODS IN THE THEORY OF FUZZY SETS IN MODELING DECISION-MAKING IN THE ECONOMIC AND LEGAL DEVELOPMENTS by Andrey N. Vaschekin

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Enhancing Nowcasting With Multi‐Resolution Inputs Using Deep Learning: Exploring Model Decision Mechanisms by Yuan Cao, Lei Chen, Junjing Wu, Jie Feng

“…To illustrate the model's interpretability, we employ the integrated gradients method, which highlights critical areas in representative cases and provides insights into the model's decision‐making process.…”
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Fast Islanding Detection for Distribution System including PV using Multi-Model Decision Tree Algorithm by Rasool Ebrahimi, Ghazanfar Shahgholian, Bahador Fani

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Implementation of Efficient Artificial Neural Network Data Fusion Classification Technique for Induction Motor Fault Detection by Altaf S., Mehmood M. S., Imran M.

“…Due to these uncertainties and ambiguities in modeling, decision making become difficult and lead to high financial loss. …”
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Emotional intelligence and consumer decision-making styles: the mediating role of brand trust and brand loyalty by George Kankam, Isaac Tetteh Charnor

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Classification of imbalanced travel mode choice dataset with SMOTE and prediction using interpretable machine learning by Mujahid Ali

“…The current study provides both a methodological approach and actionable insights for improving TMC modeling, decision-making, and promoting a sustainable transportation system.…”
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THEORETICAL AND METHODOLOGICAL PRINCIPLES OF APPLICATION OF AGENT-ORIENTED APPROACH TO MODELING PROCESSES OF LOCAL HROMADAS by Yevgen Kotukh, Maryna Riabokin

“…The article also outlines a multi-step algorithm for modeling decision-making and coordination processes within the decentralized budget structure. …”
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The future of pandemic modeling in support of decision making: lessons learned from COVID-19 by Kelly R. Moran, Tammie Lopez, Sara Y. Del Valle

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Leveraging Artificial Intelligence for Smart Healthcare Management: Predicting and Reducing Patient Waiting Times with Machine Learning by Kristijan CINCAR, Todor IVAŞCU

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Mathematical Models for Implementation of the Concept of Hard budget Restrictions in the budgetary system by I. V. Yakovenko

“…In this regard, the focus of economic research is focused on the problems of budgetary decentralization as an engine of economic development, as well as the related topics of the use of mathematical tools for modeling decision support in this area. The created models are subject to the requirements of learnability, adaptability to changing conditions of environmental influences, and the ability to operate not only with quantitative, but also with qualitatively defined characteristics. …”
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METHODOLOGY OF FINANCIAL AND ECONOMIC ANALYSIS OF INNOVATIVE ACTIVITIES OF ENTERPRISES IN THE CONDITIONS OF THE DIGITAL ECONOMY by О. Osadcha, O. Liashenko, O. Pavelko, R. Markov, N. Yurkiv

“…It was found that in the digital economy, classical methods of economic analysis of innovation activity are complemented by innovative ones, such as simulation modeling, decision tree, sensitivity analysis, correlation-regression and variance methods, probability method, analog method, SWOT-analysis, PEST-analysis, SNW-analysis, R-analysis. …”
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Investigation of ML algorithms for prediction of CFD data of fluid flow inside a packed-bed reactor by Yujiang Qiu, Pinxiao Liu

“…For CFD, two-dimensional mathematical modelling and simulation were carried out for the investigation of mass transfer and hydrodynamics of methanol steam reforming in a packed-bed reactor. For ML modeling, Decision Tree (DT), Multi-Layer Perceptron (MLP), and Polynomial Regression (PR) were used in estimating hydrogen concentration using r(m) and z(m) as predictors. …”
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Bayesian inference in racial health inequity analyses for noncommunicable diseases: a systematic review by Oscar Espinosa, Valeria Bejarano, Andrea Mejía, Héctor Castro, Angel Paternina-Caicedo

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Theoretical justification of the model of search for optimal solutions in complex resource management systems by Roman A. Khalturin, Roman O. Sudorgin, Nikita S. Akinshin

“…The study employs a combination of mathematical modeling, decision theory, and optimization techniques to address multicriteria problems in complex systems, particularly in resource allocation systems (RR systems) within transport complexes. …”
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An ontology-based agriculture decision-support system with an evidence-based explanation model by Amani Falah Alharbi, Muhammad Ahtisham Aslam, Khalid Ali Asiry, Naif Radi Aljohani, Yury Glikman

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Multi-Sensor Model for Earth Observation Robust to Missing Data via Sensor Dropout and Mutual Distillation by Francisco Mena, Dino Ienco, Cassio F. Dantas, Roberto Interdonato, Andreas Dengel

“…To address this challenge, we propose a novel method for multi-sensor modeling, Decision-level Sensor Dropout with mutual distillation (DSensD+). …”
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Willingness to Work and the Working Environment of Japanese Dental Hygienists by Yoshiaki Nomura, Ayako Okada, Jun Miyoshi, Masaru Mukaida, Eriko Akasaka, Keietsu Saigo, Hideki Daikoku, Hidenori Maekawa, Tamotsu Sato, Nobuhiro Hanada

“…Structural equation modeling, decision analysis, and correspondence analysis were carried out. …”
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Further N-Frame networking dynamics of conscious observer-self agents via a functional contextual interface: predictive coding, double-slit quantum mechanical experiment, and decis... by Darren J. Edwards

“…It provides a dynamic account of belief evolution through the interplay of internal observer states and external stimuli. By modeling decision-making fallacies such as the conjunction fallacy and conscious intent collapse experiments within this quantum probabilistic framework, the N-Frame model establishes structural and functional equivalence between cognitive processes identified within these experiments and traditional quantum mechanics (QM). …”
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