136 skills found · Page 5 of 5
BluffeyTest / Ransaca ransac algorithm for fitting 2d geometry，just like line, circle, and ellipse.用ransac算法拟合2d几何图形，如圆，直线，椭圆等
stevemacn / GeneticClojure curve fitting using genetic algorithms
benediktfesl / GMM CplxPython implementation of a complex-valued version of the expectation-maximization (EM) algorithm for fitting Gaussian Mixture Models (GMMs).
hrishi84 / Nesting SoftwareA classical shape fitting problem solution using a naive algorithm which gives more efficient solution than normal/random fitting
KhaledAshrafH / Curve FittingThis program implements a genetic algorithm for curve fitting using a polynomial equation. The goal is to find the best coefficients for the polynomial equation that minimize the distance between the curve and a given set of data points. The genetic algorithm is used to search for the optimal solution by evolving a population of candidate solutions
tildekara / Raman Spectroscopy Data Analysis In Python And Autonatic Export To Txt FilesPython script to perform data analysis of Raman spectrum with fitting Lorentz curve with genetic algorithm of initial parameters to chosen mode and automatic export to txt file. This example was made in order to annalyse carbon nanotubes single point, multiple acquisitions measurement data.
BiplabBag / Early Stage Fault Detection Of Stator Winding In 3 Phase Induction Motor Using Machine LearningFirst of all we have collected data and exported in data sheet.we have collected the data for healthy, unbalance, Faulty(stator winding) motor by doing an experiment and all of the data has been collected by YOKOGOWA power analyser. The collected data is stator current of three phases.For making the anaysis simplier we have converted the all 3 phase data into a single one by doing park's vector method. For ML Algorithms we need to select some of the feature We have done Feature extraction(33 feature) from PVM and PVAC . We have trained and tasted the model choosen classifier by giving 75% data for traning and we have used 25% data for testing out of180 sample. Then choose the best classifier and the best classifier that we get is K-Nearest Neighbour. After selecting the best model we have to tune the parameter of KNN model so that we get best accuracy. After fitting test data into the model we get accuracy of 91.1% and we can see the confusion matrix that shows how well the model classified the different fault (Healthy(0), Unbalance(1), Stator fault(2)) of motor . Out of 15 healthy test data all 15 are predicted in heathy class, out of 15 unbalance data 13 samples are classified in unbalance class and other 2 are misclassified in faulty case, out of 15 stator fault data 13 samples are classified in fault class and other 2 are misclassified in unbalance case.
SeamusClarke / BTSBehind The Spectrum (BTS) fitter
hightower70 / MagCalMagnetic sensor calibration in c# using Q. Li ellipsoid fitting
zhengzheng / FitCurvesC++ and Python implementation of Philip J. Schneider's "An Algorithm for Automatically Fitting Digitized Curves"
wahyudin-syam / Circle Sphere Cylinder Non Linear Geometric FittingNon-linear fittng for circle, sphere and cylinder geometry - based on NIST and Levenberg-Marquardt algorithm
tudarsm / MarsftMARSFT, an efficient genetic algorithm for fitting coherent anti-Stokes Raman spectra
gginolhac / InSAR COFI PLCode of paper "Covariance Fitting Interferometric Phase Linking: Modular Framework and Optimization Algorithms"
fengshun124 / PyAFSpyAFS is a Python package replicating the Alpha-shape Fitting to Spectrum (AFS) algorithm from R, providing data-driven continuum fitting and spectrum normalisation.
micmog / Strain Rate Constitutive Model Fitting With Genetic AlgorithmsUsing GALGO to fit Johnson Cook Parameters using Genetic Algorithms. Work In Progress
ipazc / DeepevolutionDeepevolution is a PIP package for evolving tensorflow keras models with a genetic algorithm towards fitting a fitness function.
Anselmoo / RBF NetworkFittingRadial-Basis-Function-Network for solving the 1D- and 2D-minimization problem
dzungdoan6 / HQC Robust FittingImplementation of Hybrid Quantum-Classical Algorithm for Robust Fitting
HagesLab / MetroTRPLEfficient parameter fitting of TRPL curves using a Metropolis-Hastings Monte Carlo sampling algorithm
zunzun / ZunzunsiteA Django site in Python 2 for curve fitting 2D and 3D data that can output source code in several computing languages and run a genetic algorithm for initial parameter estimation. Includes orthogonal distance and relative error regressions. Generates PDF files and surface animations. Based on code from zunzun.com.
