Consequently, the machine learning-based computational model designed in this investigation is a helpful tool for estimating the PCC's engineering properties when laboratory tests are not attainable. Thus, the main novelty of this study is creating a robust model to determine ...
Combining machine learning (ML) with computational fluid dynamics (CFD) opens many possibilities for improving simulations of technical and natural systems
rubynlplistmachine-learningnatural-language-processingawesomesentiment-analysisawesome-listcomputational-linguisticspos-tagrubynlprubyml UpdatedJun 27, 2023 Ruby eselkin/awesome-computational-neuroscience Star718 A list of schools and researchers in computational neuroscience ...
Artificial neural networks (NNs) have been widely used in creation of various machine learning (ML) models. Training an NN for a given dataset is essential... GR Liu - 《International Journal of Computational Methods》 被引量: 0发表: 2022年 Solution Existence Theory for Artificial Neural Networ...
Using machine learning to reveal seasonal nutrient dynamics and their impact on chlorophyll-a levels in lake ecosystems: A focus on nitrogen and phosphorus Revealed seasonal TP and TN impacts on phytoplankton via macroscale ML analysis.ADASYN for data synthesis could optimize ML model performance.Weight...
摘要: In this work, we present a machine learning (ML)-enhanced computational reverse-engineering analysis of scattering experiments (CREASE) approach to analyze the small-angle scattering profiles from ...收藏 引用 批量引用 报错 分享 全部来源 求助全文 ACS 相似文献Machine Learning-Enhanced ...
learning (ML) has demonstrated its transformative potential in concrete research. Given the rapid adoption of ML for concrete mixture design, there is a need to understand methodological limitations and formulate best practices in this emerging computational field. Here, we review the areas in which ...
learning (ML) has demonstrated its transformative potential in concrete research. Given the rapid adoption of ML for concrete mixture design, there is a need to understand methodological limitations and formulate best practices in this emerging computational field. Here, we review the areas in which ...
Concept Maps Combined with Case-Based Reasoning in Order to Elaborate Intelligent Teaching/Learning Systems The use of pedagogical methods with the technologies of the information and communications produce a new quality that favors the task of generating, transm... ML Espinosa,NM Sanchez,ZG Valdivia...
Machine learning (ML) has become critical for post-acquisition data analysis in (scanning) transmission electron microscopy, (S)TEM, imaging and spectroscopy. An emerging trend is the transition to real-time analysis and closed-loop microscope operation. The effective use of ML in electron microscop...