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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃心豪 | zh_TW |
| dc.contributor.advisor | Hsin-Haou Huang | en |
| dc.contributor.author | 馮冠倫 | zh_TW |
| dc.contributor.author | Kuan-Lun Feng | en |
| dc.date.accessioned | 2023-10-03T17:08:53Z | - |
| dc.date.available | 2023-11-09 | - |
| dc.date.copyright | 2023-10-03 | - |
| dc.date.issued | 2023 | - |
| dc.date.submitted | 2023-08-10 | - |
| dc.identifier.citation | 第七章 參考文獻
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90678 | - |
| dc.description.abstract | 本研究使用前人歸納出的多種吸音機制，提取複數機制結合後的模型特徵，並進行基因演算法優化，使用目標函數對初始結果進行轉換之後帶入進化/變異算法，找出優化的特徵組合為何，但由於基因驗算法優化後的結果為一個數值，無法得知真實的吸音表現，所以建立由機器學習所建構而成的替代模型，以便快速了解優化後的特徵組合具有何種吸音表現，最後藉由此套方法開發出在2 kHz ~ 20 kHz 範圍中，皆具有高達0.9以上吸音係數的高性能水下吸音超材料，同時解決了在吸音超材料中無法兼顧高低頻吸音的問題，達到寬帶吸音。 | zh_TW |
| dc.description.abstract | This study utilizes various absorption mechanisms identified by previous research to extract combined features of multiple mechanisms. The extracted features are then optimized using a genetic algorithm, where an objective function is applied to transform the initial results and input them into an evolutionary/mutation algorithm. The goal is to identify the optimized combination of features. However, since the results of the genetic algorithm optimization are numerical values, the actual absorption performance cannot be determined. Therefore, an alternative model constructed by machine learning is established to quickly understand the absorption performance of the optimized feature combination. Finally, using this approach, a high-performance underwater absorption metamaterial is developed with absorption coefficients exceeding 0.9 across the range of 2 kHz to 20 kHz. This solution simultaneously addresses the challenge of achieving broadband absorption in metamaterials, which typically struggle with absorbing both high and low frequencies. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-10-03T17:08:53Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2023-10-03T17:08:53Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 目錄
誌謝 i 中文摘要 ii 英文摘要 iii 目錄 iv 圖目錄 vii 表目錄 x 第一章 簡介 1 1.1 動機 1 1.2 研究背景 1 1.3 研究目的 2 1.4 重要性與貢獻 3 1.5 名詞對照與符號說明 5 1.5.1 英文專有名詞與中文翻譯對照 5 1.5.2 符號說明表 8 第二章 文獻探討 9 2.1 水下吸音機制 9 2.2 數據均勻化 14 2.3 優化方法 20 2.4 替代模型-快速預測方法 23 第三章 吸音機制篩選與超穎材料模型建立 27 3.1 有限元素法模擬 27 3.2 吸音機制組合 29 3.2.1 吸音機制篩選與組合 29 3.2.2 初始模型之性能分析 33 3.3 均勻化實驗設計 35 3.3.1 拉丁超立方取樣 35 3.3.2 模型幾何特徵萃取 (Feature extraction) 36 第四章 基因優化演算法 38 4.1 目標函數轉換 38 4.2 基因優化演算法框架 41 4.3 種群的交叉與變異 44 4.3.1 交叉與變異算法 45 4.3.2 算法性能比較 48 4.4 估計器精確度與最終優化結果 52 第五章 機器學習預測 63 5.1 替代模型精度指標 63 5.2 替代模型預測與比較 67 5.2.1 特徵工程 (Feature engineering) 69 5.2.2 XGBoost回歸器 72 5.2.3 RandomForest回歸器 81 5.2.4 CatBoost回歸器 86 5.2.5 替代模型性能比較 91 第六章 結論與未來展望 94 6.1 結論 94 6.2 未來展望 95 第七章 參考文獻 96 附錄 101 附錄 A : 近正交拉丁超立方規劃均勻實驗設計組合 101 附錄 B : 估計器精度測試結果 & 測試誤差 104 附錄 C : 優化後的幾何參數組合 (GAO算法、ACO算法) 105 | - |
| dc.language.iso | zh_TW | - |
| dc.subject | 高性能水下吸音超材料 | zh_TW |
| dc.subject | 基因演算法優化 | zh_TW |
| dc.subject | 目標函數 | zh_TW |
| dc.subject | 機器學習 | zh_TW |
| dc.subject | 寬帶吸音 | zh_TW |
| dc.subject | high-performance underwater absorption metamaterial | en |
| dc.subject | Genetic algorithm optimization | en |
| dc.subject | broadband absorption | en |
| dc.subject | machine learning | en |
| dc.subject | objective function | en |
| dc.title | 基於機器學習模型與基因演算法優化對高性能水下寬帶吸音超材料的設計與優化 | zh_TW |
| dc.title | Design and optimization of high-performance underwater broadband sound-absorbing metamaterials based on machine learning models and genetic algorithm | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 111-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 黃勝翊;張恆華;黃乾綱 | zh_TW |
| dc.contributor.oralexamcommittee | Hseng-Ji Huang;Heng-Hua Chang;Chien-Kang Huang | en |
| dc.subject.keyword | 基因演算法優化,目標函數,機器學習,高性能水下吸音超材料,寬帶吸音, | zh_TW |
| dc.subject.keyword | Genetic algorithm optimization,objective function,machine learning,high-performance underwater absorption metamaterial,broadband absorption, | en |
| dc.relation.page | 106 | - |
| dc.identifier.doi | 10.6342/NTU202303266 | - |
| dc.rights.note | 同意授權(限校園內公開) | - |
| dc.date.accepted | 2023-08-10 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 工程科學及海洋工程學系 | - |
| dc.date.embargo-lift | 2028-08-07 | - |
| 顯示於系所單位： | 工程科學及海洋工程學系 | |
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