How to create a time series dataset for prediction of load demand using matlab

I want to create a time series dataset to tain my ML model which should has resistance load, inductive load, capasitive load and power factor.

Answer 1

[Manas]

Hi Aakanksh,

you can use the following code for reference to build you dataset

% Define time interval and duration
timeInterval = seconds(1); % Time resolution of 1 second
duration = hours(1); % Duration of 1 hour

% Generate time stamps
timeStamps = (datetime('now'):timeInterval:(datetime('now')+duration))';

% Preallocate arrays for data
numSamples = numel(timeStamps);
loadResistance = zeros(numSamples, 1);
inductiveResistance = zeros(numSamples, 1);
capacitiveResistance = zeros(numSamples, 1);
powerFactor = zeros(numSamples, 1);

% Generate random or simulated values for each time stamp
for i = 1:numSamples
    % Generate random values for load resistance, inductive resistance, capacitive resistance, and power factor
    loadResistance(i) = rand(); % Modify with appropriate range or distribution
    inductiveResistance(i) = rand(); % Modify with appropriate range or distribution
    capacitiveResistance(i) = rand(); % Modify with appropriate range or distribution
    powerFactor(i) = rand(); % Modify with appropriate range or distribution
end

% Create a table to store the data
data = table(timeStamps, loadResistance, inductiveResistance, capacitiveResistance, powerFactor);

% Save the data to a CSV file
writetable(data, 'time_series_dataset.csv');

You can refer to the following documentation for more info:

Time Series Objects

[Aakanksh Gowda]

I have tried this before but it will generate random data. What i wanted is more complicated. I wanted the dataset to maintain its relation for resistive, inductive and capacitive load