會議論文
| 學年 | 94 |
|---|---|
| 學期 | 1 |
| 發表日期 | 2005-10-13 |
| 作品名稱 | 結合人工智慧與專家知識之智慧型水庫操作系統 |
| 作品名稱（其他語言） | Integrating AI with Expert Knowledge to Build Intelligent Reservoir |
| 著者 | 張斐章; 張雅婷; 張麗秋 |
| 作品所屬單位 | 淡江大學水資源及環境工程學系 |
| 出版者 | 臺北市：中國農業工程學會 |
| 會議名稱 | 九十四年度農業工程研討會 |
| 會議地點 | 苗栗市, 臺灣 |
| 摘要 | Resulting from the continuous increase in water demand and uneven water distribution both on time and space, the efforts of pursuing integrated optimal water resource management become critical. In this study, we propose a novel intelligent control methodology that includes the genetic algorithm (GA), fuzzy rule base (FRB), and the adaptive network-based fuzzy inference system (ANFIS) to enhance the efficiency of reservoir operation. The Shihmen reservoir in north Taiwan is used as a case study, and its last thirty-six years hydrological data are used to train and/or verify the models' performance. GA and FRB are used to extract the knowledge based on the historical inflow data with a design objective function and the traditional rule curve operating strategy, respectively. The ANFIS is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. The practicability and effectiveness of the proposed approach is tested on the operation of the Shihmen reservoir. The results show that the ANFIS models built on different types of knowledge have better performance than the traditional M-5 rule curves in reservoir operation. Moreover, we demonstrate that the ANFIS model can be more intelligent for reservoir operation if more information (or knowledge) is involved. |
| 關鍵字 | 水庫操作;人工智慧;遺傳演算法;調適性網路模糊推論系統;模糊規則庫;Reservoir operation;Artificial intelligence;Genetic algorithm;Adaptive network-based fuzzy inference system;Fuzzy rule base |
| 語言 | zh_TW |
| 收錄於 | |
| 會議性質 | 國內 |
| 校內研討會地點 | |
| 研討會時間 | 20051013~20051013 |
| 通訊作者 | |
| 國別 | TWN |
| 公開徵稿 | Y |
| 出版型式 | 紙本 |
| 出處 | 九十四年度農業工程研討會論文集，14頁 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/68061 ) |