ANN.rar_ANN_LOAD ANN_forecast_forecasting_load forecasting

P=[0.82183908 0.913793103 0.890804598 0.804597701 0.908045977 0.873563218 0.82183908 0.902298851 0.890804598 0.862068966 0.862068966 0.804597701 0.1004; 0.787356322 0.862068966 0.833333333 0.706896552 0.735632184 0.66091954 0.545977011 0.747126437 0.793103448 0.82183908 0.862068966 0.752873563 0.1009; 0.91954023 0.959770115 0.925287356 0.833333333 0.833333333 0.735632184 0.787356322 0.850574713 0.908045977 0.798850575 0.856321839 0.850574713 0.0983; 0.804597701 0.879310345 0.856321839 0.718390805 0.787356322 0.747126437 0.718390805 0.879310345 0.879310345 0.965517241 0.913793103 0.890804598 0.0968]'; T=[0.787356322 0.862068966 0.833333333 0.706896552 0.735632184 0.66091954 0.545977011 0.747126437 0.793103448 0.82183908 0.862068966 0.752873563; 0.91954023 0.959770115 0.925287356 0.833333333 0.833333333 0.735632184 0.787356322 0.850574713 0.908045977 0.798850575 0.856321839 0.850574713; 0.804597701 0.879310345 0.856321839 0.718390805 0.787356322 0.747126437 0.718390805 0.879310345 0.879310345 0.965517241 0.913793103 0.890804598; 0.83908046 0.936781609 0.850574713 0.862068966 0.890804598 0.718390805 0.67816092 0.83908046 0.879310345 0.867816092 0.879310345 0.873563218]'; threshold=[0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1;0 1]; net=newff(threshold,[27,12],{'tansig','logsig'},'trainlm'); net.trainParam.epochs=1000; net.trainParam.goal=0.01; LP.lr=0.1; net=train(net,P,T); P_test=[0.83908046 0.936781609 0.850574713 0.862068966 0.890804598 0.718390805 0.67816092 0.83908046 0.879310345 0.867816092 0.879310345 0.873563218 0.0996]; Out=sim(net,P_test);