# A Convex Combination Approach for Artificial Neural Network of Interval Data
## 3 The Proposed Method Artificial Neural Network with Convex Combination (ANN-CC)
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**One Hidden Node** & **Weight Parameter** & **MAE** & & **MSE** & & **RMSE** \\ \hline PTT & w1 & w2 & out & in & out & in & out & in \\ \hline tanh & 0.500000 & 0.500000 & 0.019527 & 0.019337 & 0.000626 & 0.000593 & 0.025023 & 0.024332 \\ sigmoid & 0.500000 & 0.500000 & 0.019831 & 0.019362 & 0.000639 & 0.000596 & 0.025286 & 0.024424 \\ linear & 0.500000 & 0.500000 & 0.019064 & 0.019355 & 0.000597 & 0.000583 & 0.024441 & 0.02415 \\ exp & 0.500000 & 0.500000 & **0.012656** & **0.011672** & **0.000261** & **0.000225** & **0.016154** & **0.015011** \\ \hline SCC & w1 & w2 & out & in & out & in & out & in \\ \hline tanh & 0.500000 & 0.500000 & 0.017691 & 0.017901 & 0.000479 & 0.000496 & 0.021866 & 0.022275 \\ sigmoid & 0.500000 & 0.500000 & 0.017738 & 0.017932 & 0.000506 & 0.000499 & 0.022495 & 0.022342 \\ linear & 0.500000 & 0.500000 & 0.017561 & 0.017892 & 0.000465 & 0.000486 & 0.021569 & 0.022032 \\ exp & 0.500000 & 0.500000 & **0.017469** & **0.017703** & **0.000455** & **0.000472** & **0.021335** & **0.021737** \\ \hline CPALL & w1 & w2 & out & in & out & in & out & in \\ \hline tanh & 0.500000 & 0.500000 & 0.021078 & 0.020439 & 0.000801 & 0.000631 & 0.028314 & 0.025126 \\ sigmoid & 0.500000 & 0.500000 & **0.021049** & **0.020295** & **0.000797** & **0.000626** & **0.028236** & **0.025027** \\ linear & 0.500000 & 0.500000 & 0.021850 & 0.020635 & 0.000857 & 0.000658 & 0.029283 & 0.025666 \\ exp & 0.500000 & 0.500000 & 0.022129 & 0.020771 & 0.000891 & 0.000733 & 0.029861 & 0.027078 \\ \hline
**Two Hidden Nodes** & **Weight Parameter** & **MAE** & & **MSE** & & **RMSE** \\ \hline PTT & w1 & w2 & out & in & out & in & out & in \\ \hline tanh & 0.500000 & 0.500000 & 0.018938 & 0.019209 & 0.000558 & 0.000556 & 0.023622 & 0.023830 \\ sigmoid & 0.500000 & 0.500000 & 0.019426 & 0.019363 & 0.000608 & 0.000611 & 0.024658 & 0.024490 \\ linear & 0.500000 & 0.500000 & **0.018735** & **0.018200** & **0.000548** & **0.000541** & **0.023434** & **0.023269** \\ exp & 0.500000 & 0.500000 & 0.019611 & 0.019322 & 0.000629 & 0.000595 & 0.025092 & 0.024391 \\ \hline SCC & w1 & w2 & out & in & out & in & out & in \\ \hline tanh & 0.500000 & 0.500000 & 0.017883 & 0.017851 & 0.000472 & 0.000487 & 0.021731 & 0.022073 \\ sigmoid & 0.500000 & 0.500000 & 0.018067 & 0.017798 & 0.000517 & 0.000476 & 0.022742 & 0.021825 \\ linear & 0.500000 & 0.500000 & 0.018658 & 0.017653 & 0.000546 & 0.000461 & 0.023375 & 0.021481 \\ exp & 0.500000 & 0.500000 & **0.013203** & **0.012860** & **0.000291** & **0.000281** & **0.017057** & **0.016770** \\ \hline CPALL & w1 & w2 & out & in & out & in & out & in \\ \hline tanh & 0.500000 & 0.500000 & 0.020415 & 0.020792 & 0.000690 & 0.000681 & 0.026271 & 0.026090 \\ sigmoid & 0.500000 & 0.500000 & 0.021457 & 0.020544 & 0.000752 & 0.000665 & 0.027426 & 0.025781 \\ linear & 0.500000 & 0.500000 & 0.020851 & 0.020698 & 0.000644 & 0.000692 & 0.025382 & 0.026314 \\ exp & 0.500000 & 0.500000 & **0.015538** & **0.014341** & **0.000472** & **0.000386** & **0.021739** & **0.019653** \\ \hline
**Three Hidden Nodes** & **Weight Parameter** & **MAE** & & **MSE** & & **RMSE** \\ \hline PTT & w1 & w2 & out & in & out & in & out & in \\ \hline tanh & 0.5000000 & 0.5000000 & 0.019384 & 0.019376 & 0.000581 & 0.000607 & 0.024115 & 0.024637 \\ sigmoid & 0.500000 & 0.500000 & 0.019355 & 0.019373 & 0.000608 & 0.000600 & 0.024667 & 0.024495 \\ linear & 0.500000 & 0.500000 & 0.019215 & 0.019423 & 0.000603 & 0.000602 & 0.024549 & 0.024536 \\ exp & 0.5000000 & 0.500000 & **0.009504** & **0.009139** & **0.000178** & **0.000165** & **0.013344** & **0.012845** \\ \hline SCC & w1 & w2 & out & in & out & in & out & in \\ \hline tanh & 0.5000000 & 0.5000000 & 0.017898 & 0.017843 & 0.000493 & 0.000482 & 0.02213 & 0.021961 \\ sigmoid & 0.5000000 & 0.500000 & 0.017337 & 0.017988 & 0.000458 & 0.000491 & 0.021412 & 0.022166 \\ linear & 0.500000 & 0.500000 & 0.017841 & 0.017864 & 0.000489 & 0.000483 & 0.022121 & 0.021968 \\ exp & 0.5000000 & 0.500000 & **0.012653** & **0.012585** & **0.000273** & **0.000267** & **0.016530** & **0.016