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翁正剛
以機器學習預測地下水位的變化
以機器學習預測地下水位的變化
以機器學習預測地下水位的變化
By
翁正剛
・
Taoyuan City, Taiwan
Connect
特徵資料: 約16萬個電錶用電資料 (分布於濁水溪沖積扇區域), 預測目標: 39個觀測井未來的地下水位 (濁水溪沖積扇區域之第一和第二含水層)。 使用技術: 1. Linear Regression、2. Random Forest、3. Support Vector Machine、4. Artificial Neural Network。 結果評估: 未來30天每一天平均地下水位之預測, 第一含水層: MSE為0.998、R^2為0.995, 第二含水層: MSE為1.508、R^2為0.996。 附圖為其中一個的觀測井的預測結果圖。
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Post
翁正剛
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Published: Apr 14th 2019
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Tools
TensorFlow
Python
Machine Learning
Artificial Neural Network
Support Vector Machine
Random Forest
Linear Regression
python
Deep Learning
機器學習
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