GitHub18d
nonlinear-dynamics
About the https://iris.unipa.it/retrieve/handle/10447/276402/535513/81-Minati_Chaos-2017.pdf I show a set of dynamic non linear equation that represent a good ...
The New York Times22d
Three Giants stats that are due for a negative regression and how they should prepare
Not all regression is bad. Logan Webb allowed more damage in high-leverage situations than low-leverage situations last season. Either he’s uniquely bad when the pressure is on, or it was just a ...
Visual Studio Magazine23d
Random Neighborhoods Regression Using C#
In random neighborhoods regression, you create an ensemble (collection) of several k-nearest neighbor regressor systems, each using a different subset of the source training data, and each with a ...
Frontiers26d
Blending physics with data using an efficient Gaussian process regression with soft inequality and monotonicity constraints
Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, PA, United States In this work, we propose a new Gaussian process (GP) regression framework ... In this work, we use ...
IEEE1mon
Dynamic Non-Gaussian and Nonlinear Industrial Process Monitoring Using Deep Analysis of Hybrid Characteristics
Abstract: Data-driven monitoring using principal component analysis (PCA) and independent component analysis (ICA) has been studied extensively for modern industrial processes. However, due to the ...
Visual Studio Magazine1mon
Random Forest Regression and Bagging Regression Using C#
This article presents a complete demo of random forest regression using the C# language. A good way to see where this article is headed is to take a look at the screenshot in Figure 1. The demo ...
IEEE4mon
Characterizing Device Nonlinearity in Optical Communication Systems Using Frequency-Resolved Nonlinear Noise-to-Signal Ratio Estimation
To address this issue, we propose a method for measuring the nonlinear noise-to-signal ratio (NSR) without altering the input signal. Our approach involves dividing the test input signal into numerous ...
Frontiers5mon
Nonlinear regression modeling of swelling characteristics in cracked expansive soil: integrating crack, moisture, density, and load effect
By comprehensively considering crack rate, dry density, initial moisture content, and overburden load, a nonlinear regression swelling model is proposed ... Early models mainly relied on empirical ...
LinkedIn1y
How do you compare and benchmark different linear programming methods and algorithms in Matlab?
or you can generate your own LP problem using Matlab's random number generators. The choice of the LP problem will affect the size, sparsity, feasibility, and complexity of the LP model ...
LinkedIn1y
How do you use regression analysis for forecasting and prediction?
Polynomial and Non-Linear Regression Models Polynomial Regression: Models relationships that are not linear, using equations like exponential, logarithmic, or power functions. Regularized ...
GitHub2y
Blind Nonlinear Unmixing for Intimate Mixtures Using Hapke Model and Convolutional Neural Network
If you use this code and/or our simulated datasets please do not forget cite the following paper: B. Rasti, B. Koirala, and P. Scheunders, "HapkeCNN: Blind Nonlinear Unmixing for Intimate Mixtures ...