Abstract: This paper proposes a predictive techno-economic analysis in terms of voltage stability and cost using regression-based machine learning (ML) models and effectiveness of the analysis is ...
Abstract: The diesel generators sets (DGs) and battery storage systems (BSS) are the essential energy sources in a modern high-rise buildings. In this paper DG, BSS and Photovoltaic system (PV) has ...
mSINDy - modular Sparse Identification of Nonlinear Dynamics is a modular MATLAB framework for data-driven discovery of governing equations in nonlinear dynamical systems based on sparse regression ...
David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...
Aims To develop prediction models for identifying cases with poor visual outcomes after surgery for primary rhegmatogenous ...
Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem, including: Benchmarks of equation solver implementations ...
Is it possible to predict the composition of a microgram-sized salt deposit solely from its macroscopic appearance? While the task seems intractable, we show that for pure aqueous salt solutions dried ...
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