Implementation of Polynomial Regression on Coconut Charcoal Making System Integrated with IoT and Cloud in Real Timedoi:10.31763/iota.v4i3.797Ardhiah, AuliaChairunisa, DifaPrasetyo, MuhammadSantoso, Iman HediBudiman, GelarInternet of Things & Artificial Intelligence Journal (IOTA)...
js-regression Package provides javascript implementation of linear regression and logistic regression Install npm install js-regression Usage Linear Regression The sample code below illustrates how to run the multiple linear regression (polynomial in this case): ...
These are Linear Regression, Polynomial Regression, Exponential Fit, Logarithmic Fit, Asymptotic fit, Exponential Asymptotic Fit, Single Exponential Smoothing, Double Exponential Smoothing, and Holt-Winters. As an alternative to selecting a specific method, you can allow the system to automatically ...
Research suggests that institutions affect the levels of corruption in a country. We take these arguments a step further and examine whether it is the pres
DifferentialRegression.ipynbapplies differential learning in the context of classic regression models. In the article, we applied differential learning to deep neural networks only. This notebook applies it to polynomial regression to the basket option in a correlated Bachelier model of section 3,1. ...
A total of 130 effective survey responses were obtained. The researchers used polynomial regression combined with response surface analysis based on the two-wave data. The results supported the hypotheses.The findings offered several contributions to literature. First, different combination modes of ...
With an appropriate ansatz (e.g., physics-informed) on the structure of the right hand side in (1), the identification process is computationally executed as sparse regression, see e.g., [2,5,6]. An alternative approach is machine learning techniques such as physics-informed neural networks...
Bakdi et al. [5] proposed an offline path-planning strategy using a genetic algorithm, piecewise cubic Hermite interpolating polynomial, and an adaptive fuzzy-logic controller for keeping track of the robot on the desired path. This implementation proved to be efficient in a static environment, ...
12.1 Linear Regression Can Model Nonlinear Relationships 12.1.1 When Must Curves Be Fitted? 12.1.2 The Graphical Display of Curvilinearity 12.2 Polynomial Regression 12.2.1 Basic Principles 12.2.2 An Example 12.2.3 The Meaning of the Regression Coefficients for Lower-Order Regressors 12.2.4 Centering...
(Ghafari et al.2015). Moreover, artificial neural network (ANN) models were developed for predicting the performance of UHPC under different curing conditions (Ghafari et al.2012,2015). It was found that the polynomial regression model was suitable for predicting the desired properties of UHPC ...