AIMC Topic: Models, Theoretical

Clear Filters Showing 11 to 20 of 1953 articles

Using a neural network approach and starspots dependent models to predict effective temperatures and ages of young stars.

PloS one
This study presents a statistical approach to accurately predict the effective temperatures of pre-main sequence stars, which are necessary for determining stellar ages using the isochrone methodology and cutting-age starspots-dependent models. By tr...

A novel algorithm for model uncertainty reduction in trapezoidal fuzzy fault tree risk assessment.

PloS one
Intelligent risk assessment in complex systems increasingly relies on methods like trapezoidal fuzzy fault trees. However, conventional techniques often struggle with accurately calculating top-event probabilities and handling model uncertainty, whic...

Precise energy modeling and green retrofitting optimization of existing buildings based on BIM and deep learning approaches.

PloS one
The construction industry has emerged as a major contributor to global energy consumption and greenhouse gas emissions amidst continuously rising worldwide energy demands. Enhancing building energy efficiency represents a critical intervention for ac...

Applications of newly defined diamond Pythagorean fuzzy CODAS method via multi-criteria decision-making problems.

PloS one
The diverse decision values may fail to capture an accurate perspective when multiple decision-makers are part of the process. To address this challenge, this work introduces the diamond Pythagorean fuzzy set (Dia‑PyFS), an advancement over both the ...

Improved predictive formulae for wave overtopping at sloped breakwaters using interpretable machine learning models.

PloS one
Accurate prediction of mean wave overtopping discharge is essential for the safe and cost-effective design of coastal defence structures. While traditional empirical, physical, and numerical models remain important, Machine Learning (ML) has recently...

Forecasting China's shipping indices based on modal decomposition and optimized deep learning integrated model.

PloS one
This study proposes an innovative hybrid forecasting model, VMD-CPSO-BiLSTM, which significantly enhances the prediction accuracy of shipping indices in China's maritime sector. The model employs a sophisticated three-phase methodology: (1) decomposi...

Hybrid backdoor attacks for deep code models.

PloS one
Deep code models face security vulnerabilities through backdoor attacks. Previous approaches have primarily relied on single-trigger mechanisms, resulting in limited stealth and vulnerability to defense strategies. This paper proposes a novel hybrid ...

Mechanistic, data-driven, and hybrid models: A critical comparison in surrogate drug dissolution modeling.

International journal of pharmaceutics
Mathematical modeling is becoming increasingly important in the pharmaceutical industry. It supports the Quality by Design framework by aiding process understanding and examining the impact of critical material and process parameters on the critical ...

Capsule-based federated reinforcement learning adaptive sliding mode for anomaly detection and control of floating wind turbines.

PloS one
Floating wind turbines (FWTs) are now recognized as one of the most effective and affordable renewable energy sources. However, their performance is strongly influenced by dynamic environmental conditions, particularly sea waves under significant osc...

Advancing training effectiveness prediction in mass sport through longitudinal data: A mathematical model approach based on the Fitness-Fatigue Model.

PloS one
Despite the critical need for scientific training load assessment in mass sports, the Fitness-Fatigue Model (FFM) requires further mathematical optimization and practical output indicators. The aim of this study was to optimize the mathematical relat...