Azzera filtri
Azzera filtri

if any one have code related to this topic "Modeling of Electricity Consumption Forecasting Using Artificial Neural Network and Support vector Machine" kindly let me know please.

1 visualizzazione (ultimi 30 giorni)
My thesis topic is "Modeling of Electricity Consumption Forecasting Using Artificial Neural Network and Support vector Machine". i used following code to predict the consumption results like R value, MSE , MAPE, MAE etc.
Opts = detectImportOptions('datasetn.txt'); Data = readtable('datasetn.txt', Opts);
input = {'T', 'Wdi', 'S', 'R','W'}; i = Data(:, input); p=table2array(i) %input variables
kWh = Data.kWh; kWh = strrep(kWh, ',', ''); kWh = strjoin(kWh, '\n'); kWh = str2num(kWh); Data.kWh = kWh
respone=Data.kWh % target response
net=feedforwardnet(10); net = configure(net, p', respone') [net, info] = train(net, p',respone'); % p input and respone the target / the info will contain the masks
y1=net(p') %predicted response Rt=corrcoef(y1, respone') %correlation coefficent MSE=mean((respone'-y1).^2); % overall MSE mAE=mean(respone'-y1))/365 %overall MAE
but i dont know what i have to write in experiment chapter because all others papers that i read almost 20 to 30, are much more advanced and they used some ANN methods like "Artificial Neural Network Based Models Generated by Multi Objective Genetic Algorithm" and many more . but i just train using "Levenberg-Marquardt backpropagation". now kindly let me know please what i have to discuss here.
  1 Commento
Stephan
Stephan il 29 Set 2018
This topic should be discussed with your professor, not in a forum for questions related to Matlab.
Find out what you want to do and come back when you get in trouble by doing this in Matlab.

Accedi per commentare.

Risposte (0)

Categorie

Scopri di più su Sequence and Numeric Feature Data Workflows in Help Center e File Exchange

Tag

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by