本論文主要探討原水濁度、原水pH值以及聚氯化鋁加藥量對淨化水質濁度之最佳化問題。
利用二階段迴歸方法，首次迴歸分析尋找最佳加藥量與原水濁度之迴歸關係，以此模型進一步
配適三個解釋變數下對淨化水質濁度之迴歸模型。依據第二階段迴歸分析結果，來探討在設定
淨化後之濁度期望值條件下，推估出最佳加藥量，以作為未來淨化水質之最佳加藥處理方式之
參考。

The main purpose of this study is to investigate the relationship between the water turbidity
purification result with raw water turbidity, raw water pH value and PAC dosage,
and find the optimal treatment dosage level. A regression model between the response
and treatment variables has been built with a two-stage procedure. In the first stage,
the regression model treats a given raw water turbidity as the explanatory variable and
the best treatment effect dosage level, among the six experimental dosage levels as the
response. Later the model is used to find the second stage regression model where the
water turbidity purification result is treated as the response, and the other three variables
mentioned above as explanatory variables. According to the results of the second stage
regression model about the best dosage level with a given raw water turbidity, the optimal
PAC dosage is estimated for the optimization in water turbidity purification, which may
be used as a way for future purification of water turbidity.

1 序論1
2 統計方法與介紹3
2.1 迴歸分析簡介. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 基礎統計圖形. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
3 最佳加藥量模型6
3.1 加藥量與原水濁度迴歸模型. . . . . . . . . . . . . . . . . . . . . . . . . 6
3.2 淨水最佳加藥量之二次迴歸. . . . . . . . . . . . . . . . . . . . . . . . . 8
3.3 淨水最佳加藥量之對數迴歸. . . . . . . . . . . . . . . . . . . . . . . . . 14
3.4 自來水淨化處理成效標準. . . . . . . . . . . . . . . . . . . . . . . . . . 17
4 結論與建議18
5 參考文獻19
6 附錄20
6.1 加藥量之變異數推導. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
6.2 加藥後濁度之二次迴歸. . . . . . . . . . . . . . . . . . . . . . . . . . . 21

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Activated Carbon for MIB and Geosmin Removal: Predicting PAC Doses in Four
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Treatment Processes-Experiences at the Wahnbach Reservoir”, Water Science technology,
37, 43-48 .
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