machine learningnon-parametric algorithmsparameter estimationrecovery test>In this study we propose a new method called the cessation time approach (CTA) for interpreting recovery tests in confined aquifers, wh
非参数模型并不是说模型中没有参数。这里的non-parametric类似单词priceless,也就是参数是非常非常非常多的!(注意:所谓“多”的标准,就是参数数目大体和样本规模差不多)
We present a general class of machine learning algorithms called parametric matrix models. In contrast with most existing machine learning models that imitate the biology of neurons, parametric matrix models use matrix equations that emulate physical systems. Similar to how physics problems are usually ...
The first goal of this study was to estimate the total hydrogen inventory in ITER divertor. To this end, FESTIM simulations of ITER-like monoblocks were performed. Instead of simulating each monoblock of the divertor individually (which would be computatively expensive), a parametric study was m...
Estimating Liquefaction Susceptibility Using Machine Learning Algorithms with a Case of Metro Manila, Philippines. Applied Sciences (Switzerland), 2023, 13(11): 6549. 29. Gaur, L., Garg, P.K. Emerging trends, techniques, and applications in geospatial data science. Emerging Trends, Techniques...
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Through an intelligent redesigning of the Support vector machine optimisation, not only do we bring noise resilience into the model, but also retain its sparsity. Our model exhibits properties similar to Support vector machines, hence many SVM related learning algorithms can be extended to make it ...
Indeed, applying the underlying algorithms to modeling motor vehicles has motivated many studies in this regard (Hu, 2018). The degree of safety can be deduced from the models used for crash tests or simulations, thus, necessitating to represent the entire whole population of occupants. According...
Machine learning algorithms Monte Carlo method 1. Introduction Modern societies require efficient means of transport for passengers and goods. Speed, comfort, safety and environmental friendliness are unavoidable demands nowadays. There are several reasons that have made the railway one of the most used...
& Yan, W. A prediction of precipitation data based on support vector machine and particle swarm optimization (PSO-SVM) algorithms. Algorithms 10(2), 57 (2017). MathSciNet MATH Google Scholar Hong, W. C. Rainfall forecasting by technological machine learning models. Applied Mathematics and ...