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2 690
Engineering with Agentic AI: Using Skills to Improve Your Agent
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via MATLAB@YouTube (author: MATLAB)
2 690
The All-Electric Flying Machine Reinventing Sea Travel
#YouTube
via MATLAB@YouTube (author: MATLAB)
2 690
📡 MATLAB Central - File Exchange - rating:5.0 | truncAxis (break X/Y axis | 截断坐标轴)
Basic usagetruncAxis(gca, 'X', [x1, x2])truncAxis(gca, 'Y', [y1, y2])truncAxis(gca, 'X', [x1, x2], 'Y', [y1, y2]) Where:x1, x2: break points on X-axis, satisfying XLim(1) < x1 < x2 < XLim(2)y1, y2: break points on Y-axis, satisfying YLim(1) < y1 < y2 < YLim(2)Demo 1X = linspace(0, 2*pi, 100);Y = exp(.3*X).*sin(3*X);scatter(X, Y, 'LineWidth',1);set(gca, 'Box','on', 'NextPlot','add', 'LineWidth',1.5, ... 'FontName','Times New Roman', 'FontSize',15, ... 'XLim',[0, 6], 'YLim',[-6, 6], 'XColor','r','YColor','b', ... 'XMinorTick','on', 'YMinorTick','on', 'TickDir','out', 'TickLength',[.005,.001]);truncAxis('X',[4, 4.5], 'Y',[2, 3], 'XResize','on', 'YResize','on')legendDemo 2% Generate sample dataData = [randi([20, 35], [5, 1]), randi([160, 190], [5, 1])];err = rand([5, 2]) .* 5;hold onbarHdl = bar(Data, 'BarWidth', 1, 'LineWidth',1);% Customize bar colors and transparencybarHdl(1).FaceColor = [153, 153, 253] ./ 255;barHdl(2).FaceColor = [255, 153, 154] ./ 255;barHdl(1).FaceAlpha = 0.9;barHdl(2).FaceAlpha = 0.9;% Render and customize error barserrorbar(barHdl(1).XEndPoints, Data(:, 1), err(:, 1), ... 'LineStyle', 'none', 'Color', 'k', 'LineWidth', 1);errorbar(barHdl(2).XEndPoints, Data(:, 2), err(:, 2), ... 'LineStyle', 'none', 'Color', 'k', 'LineWidth', 1);% Axes styling and label customizationax = gca;ax.YLim = [0, 200];ax.LineWidth = 1;ax.TickLength = [0.005, 0.001];ax.Box = 'on';ax.FontSize = 13;ax.XTick = 1:5;ax.XTickLabel = {'A', 'B', 'C', 'D', 'E'};axMat = truncAxis('Y', [50, 155]);axMat(1).Children(end).BaseLine.Color = 'none';% Add legendlegend({'AAAAA', 'BBBBB'}, 'FontSize', 13);
2 690
Electrolyzer modelling toolbox
MATLAB Central - File Exchange - rating:5.0 (RSS)
[](https://se.mathworks.com/matlabcentral/fileexchange/117175-electrolyzer-modelling-toolbox)### GENERAL DESCRIPTIONThis toolbox is a Matlab tool for electrolysis modelling, for both PEM and alkaline systems. Main functionality is in parametrization of the UI curvebased on measured data. This toolbox aims to simplify the process and provide easy-to-use commands for quickly determining the UI curve parameter values and their margins of uncertainty.Since version 2.0.0, dynamic modeling functionality has been added, being capable of fitting model parameters from time-dependent data sets and using the fit parameters to simulate dynamic voltage response to arbitrarycurrent waveforms.---### INSTALLATIONMATLAB needs to be installed on the computer for the user to be able toinstall the electrolyzer modelling toolbox. Following steps install thetoolbox for that matlab installation:1. Download the provided electrolyzerModellingToolbox.mltbx file from the releases page. - Double click on the .mltbx file to initiate installation.2. Once the installation completes the toolbox functions are usable in all matlab projects---### AUTHORS AND CONTACTSPietari PuranenJunior researcher at the Lappeenranta-Lahti University of Technology LUTEmail: Pietari.Puranen@lut.fiLauri JärvinenJunior researcher at the Lappeenranta-Lahti University of Technology LUTEmail: Lauri.Jarvinen@lut.fi---### AKNOWLEDGEMENTSMarchov Chain Monte Carlo (MCMC) tools provided by Marko Laine have been used for the determination of uncertainty in curve fitting when using the particleswarm optimization method. The licensing for the tools can be foundunder ./Utils/mcmcstat/LICENSE.txtThe Academy of Finland is acknowledged for the main financial support ofthe Research of Power Quality Effect on Water Electrolyzer Operation (POQELYZER) project.
2 690
How to Forecast Data Using the Econometric Modeler App in MATLAB
#YouTube
via MATLAB@YouTube (author: MATLAB)
2 690
MRES 6th Edition and PRES 2nd Edition – Errata / Corrections
via MATLAB and Python Recipes for Earth Sciences (author: Martin H. Trauth)
2 690
Embedded Intelligence: The Future of Engineering Design
#YouTube
via MATLAB@YouTube (author: MATLAB)
2 690
Spline Fitting Explained: How to Smooth Noisy Data in MATLAB
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via MATLAB@YouTube (author: MATLAB)
