Results 21 to 30 of about 1,555,240 (261)
Data-Driven Method to Quantify Correlated Uncertainties
Polynomial chaos (PC) has been proven to be an efficient method for uncertainty quantification, but its applicability is limited by two strong assumptions: the mutual independence of random variables and the requirement of exact knowledge about the distribution of the random variables.
Jeahan Jung, Minseok Choi
openaire +2 more sources
Predicting personal thermal preferences based on data-driven methods [PDF]
One of the prevalent models to account for thermal comfort in HVAC design is the Predicted Mean Vote (PMV). However, the model is based on parameters difficult to estimate in real applications and it focuses on mean votes of large groups of people ...
Aguilera José Joaquín +2 more
doaj +1 more source
Mitigation of model error effects in neural network-based structural damage detection
This paper proposes a damage detection procedure based on neural networks that is able to account for the model error in the network training. Vibration-based damage detection procedures relied on machine learning techniques hold great promises for the ...
Federico Ponsi +2 more
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Data-driven extract method recommendations: a study at ING [PDF]
The sound identification of refactoring opportunities is still an open problem in software engineering. Recent studies have shown the effectiveness of machine learning models in recommending methods that should undergo different refactoring operations.
David van der Leij +5 more
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Modeling Water Quality Parameters Using Data-driven Methods
Introduction: Surface water bodies are the most easily available water resources. Increase use and waste water withdrawal of surface water causes drastic changes in surface water quality.
Shima Soleimani +2 more
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Data‐driven Methods for Modeling Social Perception [PDF]
Abstract How do we model the complexity of social perception? A major methodological problem is that the space of possible variables driving social perceptions is infinitely large, thus posing an insurmountable hurdle for conventional approaches.
Todorov, A.T. +3 more
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An Approach To Mode and Anomaly Detection with Spacecraft Telemetry Data
This paper discusses a mixed method that combines unsupervised learning methods and human expert input for analyzing telemetry data from long-duration robotic space missions.
Gautam Biswas +5 more
doaj +1 more source
Knowledge-driven building extraction method exhibits a restricted adaptability scope and is vulnerable to external factors that affect its extraction accuracy.
Ming Hao +5 more
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Small-Scale Zero-Shot Collision Localization for Robots Using RL-CNN
For safety reasons, in order to ensure that a robot can make a reasonable response after a collision, it is often necessary to localize the collision. The traditional model-based collision localization methods, which are highly dependent on the designed ...
Haoyu Lin +5 more
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Background Anaemia significantly affects health outcomes and quality of life. While blood transfusion remains a common intervention, alternative treatments, such as iron supplementation and erythropoiesis‐stimulating agents (ESAs), offer potential to ...
Hiro Farabi +9 more
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