enso.rar_ANFIS_ANFIS matlab_anfis matlab_weather_weather matlab

figure load ESTSP2007_competition_data.dat; a=ESTSP2007_competition_data; plot(a,'r:*') xlabel('week','fontsize',12);ylabel('temperature'... ,'fontsize',14); trn_data = zeros(475, 5); chk_data = zeros(400, 5); % prepare training data trn_data(:, 1) = a(1:475); trn_data(:, 2) = a(7:481); trn_data(:, 3) = a(13:487); trn_data(:, 4) = a(19:493); trn_data(:, 5) = a(25:499); % prepare checking data= chk_data(:, 1) = a(449:848); chk_data(:, 2) = a(455:854); chk_data(:, 3) = a(461:860); chk_data(:, 4) = a(467:866); chk_data(:, 5) = a(473:872); % The initial MFs for training are shown in the plots. fismat=genfis1(trn_data,[2,2,2,2],char('gbellmf','trimf','trimf','pimf'),'constant'); % for index=1:4, % subplot(2,2,index) % [x,y]=plotmf(fismat,'input',index); % plot(x,y) % axis([-inf inf 0 1.2]); % xlabel(['Input ' int2str(index)],'fontsize',10); % end figure [trn_fismat,trn_error,step,chkfis,chk_error] = ... anfis(trn_data, fismat,[15 NaN 0.01 1],[1 1 1 1],chk_data,1) % plot final MF's on x, y, z, u for input_index=1:4, subplot(2,2,input_index) [x,y]=plotmf(trn_fismat,'input',input_index); plot(x,y) axis([-inf inf 0 1.2]); xlabel(['Input ' int2str(input_index)],'fontsize',10); end % error curves plot epoch_n = 10; plot([trn_error chk_error,]); hold on; plot([trn_error chk_error], 'or'); hold off; xlabel('Epochs','fontsize',10); legend('trn_error','chk_error',0); ylabel('RMSE (Root Mean Squared Error)','fontsize',10); title('Error Curves','fontsize',10); %comparision input = [trn_data(:, 1:4); chk_data(:, 1:4)]; anfis_output = evalfis(input, trn_fismat); index = 1:875; figure plot(index,[a(index) anfis_output]); title('comparision'); xlabel('week','fontsize',10); ylabel('temp','fontsize',20); legend('original','predicted'); % % Prediction errors of ANFIS % % figure % diff=a(index)-anfis_output; % % plot(index,diff); % xlabel('week'); % title('ANFIS prediction errors','fontsize',15);