| DC 欄位 |
值 |
語言 |
| DC.contributor | 土木工程學系 | zh_TW |
| DC.creator | 張修榕 | zh_TW |
| DC.creator | Shiou-Rong Chang | en_US |
| dc.date.accessioned | 2001-7-9T07:39:07Z | |
| dc.date.available | 2001-7-9T07:39:07Z | |
| dc.date.issued | 2001 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN= 88322033 | |
| dc.contributor.department | 土木工程學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 本研究分為兩階段進行，第一階段利用模擬的方式，產生交通資料，作為資料之產生器，並且作為研究最後之旅行時間之驗證部分，第二階段則是採用三層、完全連結及前向式的網路架構，配合倒傳遞演算法來建立不同交通車流型態下之旅行時間預測模式，期望能透過偵測器所偵測之交通資料，提供精準之旅行時間預測，以作為用路人路徑選擇或是出發時間決策判斷之依據。
經由反覆的校估與測試，由研究結果得知，本研究所構建旅行時間預測模式，預測效果良好，於高速公路旅行時間預測方面，可提供交通相關單位預測旅行時間參考之雛形。 | zh_TW |
| dc.description.abstract | There are two phases in this research. First, we use simulation to produce traffic information in first phase. Second, we use artificial neural network with three layers, fully connected and feed-forward, and backpropagation algorithm to build forecasting highway travel time models. Using simulation to produce the relative data of traffic character detected by vehicle detector sequentially for the base of artificial neural network training and testing.
After repeatedly correcting and testing, the effect of forecasting model constructed in the research is very well .As to the result, this research can be provided to forecast travel time in real-time highway travel time estimation. | en_US |
| DC.subject | 模擬 | zh_TW |
| DC.subject | 類神經網路 | zh_TW |
| DC.subject | 倒傳遞演算法 | zh_TW |
| DC.subject | 車輛偵測器 | zh_TW |
| DC.subject | 旅行時間預測 | zh_TW |
| DC.subject | Simulation | en_US |
| DC.subject | Artificial neural network | en_US |
| DC.title | 高速公路旅行時間預測之研究 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |