Results 51 to 60 of about 394,931 (262)
Improving the performance of Bayesian networks in non-ignorable missing data imputation
Kuwait Journal of Science, 2013 The issue of missing data may arise for researchers who deal with data gathering problems. Bayesian networks are one of the proposed methods that have been recently used in missing data imputation.
P. NILOOFAR +2 more
doaj
Artificial Intelligence as the Next Visionary in Liquid Crystal Research
Advanced Functional Materials, EarlyView.The functions of AI in the research laboratory are becoming increasingly sophisticated, allowing the entire process of hypothesis formulation, material design, synthesis, experimental design, and reiterative testing to be automated. In our work, we conceive how the incorporation of AI in the laboratory environment will transform the role and ...
Mert O. Astam +2 more
wiley +1 more source
Analyzing Uncertainty in Complex Socio-Ecological Networks
Entropy, 2020 Socio-ecological systems are recognized as complex adaptive systems whose multiple interactions might change as a response to external or internal changes. Due to its complexity, the behavior of the system is often uncertain.
Ana D. Maldonado +3 more
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Engineering Management in Production and Services, 2021 This paper proposes a novel approach that integrates the capability of empirical validation of structural equation modelling (SEM) and the prediction ability of Bayesian networks (BN).
Wipulanusat Warit +4 more
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Journal of Transportation and Logistics, 2023 The traffic problem in Intelligent Transportation Systems has recently become a very important issue. Thanks to Intelligent Transportation Systems, the formation of large amounts of traffic data has led to the formation of data-oriented models.
Cihan Çiftçi, Halim Kazan
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Advanced Healthcare Materials, EarlyView.We developed a micro‐sized, biocompatible implant for postoperative sustained delivery of anti‐fibrotic antibodies in glaucoma surgery. Machine learning‐guided optimization of polymer composition, implant geometry, and porosity enabled precise control of drug release.
Mengqi Qin +5 more
wiley +1 more source
The variance of causal effect estimators for binary v-structures
Journal of Causal Inference, 2022 Adjusting for covariates is a well-established method to estimate the total causal effect of an exposure variable on an outcome of interest. Depending on the causal structure of the mechanism under study, there may be different adjustment sets, equally ...
Kuipers Jack, Moffa Giusi
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Intelligent Tutoring Systems by Bayesian Nets with Noisy Gates
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Directed graphical models such as Bayesian nets are often used to implement intelligent tutoring systems able to interact in real-time with learners in a purely automatic way.
Alessandro Antonucci +3 more
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Advanced Materials, EarlyView.Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Uniqueness of the Level Two Bayesian Network Representing a Probability Distribution
International Journal of Mathematics and Mathematical Sciences, 2011 Bayesian Networks are graphic probabilistic models through which we can acquire, capitalize on, and exploit knowledge. they are becoming an important tool for research and applications in artificial intelligence and many other fields in the last decade ...
Linda Smail
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