Implementation of machine learning techniques into the Subset Simulation methodStructural system reliabilitySubset SimulationKriging modelClustering algorithmMultiple failure modesA hybrid reliability analysis
Advanced machine learning techniques for building performance simulation: a comparative analysismachine learningenergy modellingXGBoostartificial neural networksfeature engineeringfeature selectionEnergy consumption predictions for buildings play an important role in energy efficiency and sustainability research. Accurate...
An explosion in high-resolution ion channel structures paved way for structure-based rational drug design and the state-of-the-art simulation and machine learning techniques dramatically improved the efficiency and effectiveness of computer-aided drug design. Here we present an overview of how ...
We developed a simulation methodology on the basis of machine learning techniques for simulation of pharmaceutical solubility in a supercritical solvent, i.e., CO2 with the perspective of nanodrug production. The X variables considered in this simulation work included pressure and temperature of the ...
For instance, machine learning techniques have been used to predict association rate constants based on the chemical or structural properties of proteins37,38. Physics-based methods, such as Brownian dynamic (BD) simulation, are widely used to reproduce the association of two proteins39–60. These...
Heterogeneous catalysis is at the heart of chemistry. New theoretical methods based on machine learning (ML) techniques that emerged in recent years provide a new avenue to disclose the structures and reaction in complex catalytic systems. Here we review
Among such techniques, the most common geostatistical tools include simple Kriging, ordinary Kriging (OK), and universal Kriging. Ordinary Kriging is, indeed, considered as the best linear unbiased estimator (Isaaks and Srivastava, 1989). However, like other weighted average-based estimators and as ...
Application of Machine Learning Techniques for Simplifying the Association Problem in a Video Surveillance System This paper presents the application of machine learning techniques for acquiring new knowledge in the image tracking process, specifically, in the blobs de... B Rodríguez,Óscar Pérez,J ...
This study not only enhances our understanding of the performance of dimensionality reduction on the microstructure evolution, but it also provides insights on strategies for accelerating phase-field modeling via machine learning techniques. 04 文章标题:模拟熔融盐热物理特性的计算方法 期刊名称:Communications...
The ANN methodology outperforms other machine learning techniques in predicting the objective function, which contains the amount of solar radiation absorption, volume, and surface area, according to the results of this research. Also, this research demonstrates how a simulation technique based on NSGA...