Advanced Materials Research Vols. 1044-1045

Abstract: In this study, four types of artificial neural network (ANN) were adopted to forecast transportation sector’s energy consumption (TSEC) taking different number of input variables. By taking premium gasoline price (PGP), premium diesel oil price (PDOP), fuel oil price (FOP), raw material natural gas price (RMNGP), and fuel natural gas price (FNGP) as input variables, ANN could successfully forecast TSEC, the best mean absolute percentage error, mean square error, root mean square error, and correlation coefficient for training and testing were 15.03 % versus 24.43 %, 2792036.59 versus 11982081.08, 1670.94 versus 3461.51, and 0.71 versus 0.51, respectively.

Abstract: Through the study on logic and timing about the cognitive process of design, we proposed three situations such as: aesthetic, strategy, image, subdivided the situation in design feature, constructed the structure marked as “Situational types - Characteristics –Characteristic Value” , to explore the interaction between structure, and the computational expression , build the industrial design scenario FBS model, and then to verify with the handheld electronic device.