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游筑鈞
2020 第六屆高速公路ETC資料在交通管理之應用競賽(國道交通與事件資 ...
2020 第六屆高速公路ETC資料在交通管理之應用競賽(國道交通與事件資 料分析)-第三名
2020 第六屆高速公路ETC資料在交通管理之應用競賽(國道交通與事件資 料分析)-第三名
By
游筑鈞
專任研究助理 @ 中央研究院統計科學研究所
・
Taipei, Taiwan
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以人數最少、年紀最小的隊伍與來自各業界的團隊一起比賽,最後得到季軍的肯定。並受邀位參加 2020 年中華民國運輸學會年會暨學術論文國際研討會發表作品。 競賽主題:針對一○八年國道交通資料進行數據探勘,透過大數據分析,將分析結果應用於交通管理上,作為未來交通安全或交通管理業務改善之參據。 提案名稱 -- 再給我幾分鐘,保你一路暢通( 由事故排除時間預測系統 ,即時發出警示 ) 提案內容 --本次研究使用主辦單位提供的 108 年國道交通資料,高速公路電子收費交通資料蒐集支援系統(TDCS —M05A)、國道實施開放路肩措施路段及時段一覽表,清理合併後以交通事故資料集和散落物資料集進行後續分析。首先,針對這兩筆資料集以視覺化探索性分析進行現況探討與問題盤點。接著,以正規化迴歸模型 Elastic Net、樹型演算法 Random Forest、XGBoost、神經網路多重感知器四種模型,選擇影響排除時間長短的重要變數,以平均均方誤差、平均絕對誤差作為模型評估的指標,並用交叉驗證進行模型參數選擇,分別針對交通事故資料集及散落物資料集以最適合的參數組合進行模型配適,以預測排除時間。再者,規劃將「事故排除時間預測系統」導入 1968 App 的三個應用推廣層面,並提出相關配套措施。最後針對該提案進行優勢與效益分析,以期將事故排除時間這項重要資訊向外傳遞,提供用路人更加即時完整的路況訊息,以降低國道事故所造成的負面衝擊。 Link:https://drive.google.com/drive/folders/1DB5BCaHONnDnpUX1ExN6AZy1G3W-R1rS
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游筑鈞
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Published: Apr 18th 2021
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regularized regression
elastic net
Multilayer Perceptron
Open Data
XGBoost
RandomForest
prediction model
Data Science
Data Mining
Data Visualization
Python
Machine Learning
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游筑鈞
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