Predicting Photochemical Pollutants in Taoyuan Area Using Adaptive Network Based Fuzzy Inference System and Backpropagation Neural Network
| Autor: | Wei-Jia Lai, 賴偉嘉 |
|---|---|
| Rok vydání: | 2012 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 100 This study employed adaptive network based fuzzy inference system (ANFIS) and Back-Propagation Neural Network (BNN) method to establish an air quality prediction model of Taoyuan area .Variable factors used Ozone, Temp, Wind direc, Wind speed, Nitrogen oxides, Nitric oxide, Nitrogen dioxide, Sulfur dioxide. We input data between January and November, 2011 as parameters to establish an optimizing network to predict the air quality of O3 and NOx on December, 2011. BNN research shows that the best mean absolute percentage error (MAPE) 14.92% by using three input parameters to compare one output parameter in O3. In predict part, the best result will be MAPE 27.91% by using four input parameters to compare one output parameter in NOx.ANFIS research shows that the best mean absolute percentage error (MAPE) 17.55% by using gbellmf three input parameters to compare one output parameter in O3. In predict part, the best result will be MAPE 23.32% by using four input parameters to compare one output parameter in NOx.According to training and prediction of O3 and NOx figure, the simulation result is better. O3 and NOX could be achieved using different types of ANFIS.And utilize four kinds trimf, trapmf, gbellmf and gaussmf in ANFIS to four the Membership function and predict,O3 of prediction result had better regard trimf as all, gaussmf take second, under the Membership function for gbellmf and trapmf respectively finally.NOX of prediction result had better regard gaussmf as all, gbellmf take second, under the Membership function for trimf and trapmf respectively finally.Therefore, ANFIS and BNN mode makes a conclusion that predicts effect perfects. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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