參考文獻
1.白子易，「下水道系統生化動力模式建立之研究」，博士論文，國立中央大學環境工程研究所，中壢（2001）。
2.何欣憲，「柔性計算用應用於都市及工業廢污水廠出流水水質預測之研究」，碩士論文，朝陽科技大學環境工程與管理系研究所，台中(2005)。3.阮成隆，「以倒傳遞類神經網路及多元線性迴歸模擬建築工地對台中縣粒狀污染物之影響」，碩士論文，朝陽科技大學，台中（2010）。4.林逸塵，「類神經網路應用於空氣品質預測之研究」，碩士論文，國立中山大學環境工程研究所，高雄市（2002）。
5.莊源鍵，「類神經網路應用於一般廢棄物焚化廠煙道氣品質預測之研究」，碩士論文，國立雲林科技大學，雲林縣（1998）。6.陳建谷，「應用倒傳遞類神經及適應性模糊類神經網路模式預測垃圾焚化廠煙道氣之比較研究」，碩士論文，國立雲林科技大學環境與安全衛生工程研究所，雲林縣（2003）。7.溫坤禮、黃宜豊、陳繁雄、李元秉、連志峰、賴家瑞，灰預測原理與應用，全華科技出版社，台北 (2002)。
8.煒盛廢水處理股份有限公司，「98年中部科學工業園區台中園區污水下水道系統操作維護工作，台中（2009）。
9.萬騰州，范惠婷，許家宴，方景萱，「應用類神經網路於雲林地區空氣品質(PM10)預測之研究」，實務專題，國立雲林科技大學環境與安全工程系，雲林縣（2001）。
10.葉怡成，「應用類神經網路」，儒林出版社，台北 (1997)。
11.蔡勇斌，1993，「活性污泥系統自動化與最佳化動態操作控制之研究」，博士論文，中央大學土木工程研究所。12.羅華強，2001，「類神經網路-MATLAB 的應用」，清蔚科技出版。
13.蘇志朋，「以倒傳遞類神經網路及多元線性回規模擬建築工地對台中市粒狀污染物之影響」，碩士論文，朝陽科技大學，台中（2010）。14.蘇漢昌，「應用適應性模糊推論系統改善類神經網路預測工業廢水廠出流水水質之研究」，碩士論文，朝陽科技大學，台中（2008）。15.Pai T.Y., Y.P. Tsai, H.M. Lo, C.H. Tsai and C.Y. Lin. ”Grey and neural network prediction of suspended solids and chemical oxygen demand in hospital wastewater treatment plant Effluent”, Computers & Chemical Engineering. (2007a).
16.Pai T.Y., T.J. Wan, S.T. Hsu, T.C. Chang, Y.P. Tsai, C.Y. Lin, H.C. Su and L.F. Yu, “Using fuzzy inference system to improve neural network for predicting hospital wastewater treatment plant effluent,” Computers & Chemical Engineering. (2009a).
17.Pai T.Y., S.C. Wang, C.F. Chiang, H.C. Su, L.F. Yu, P.J. Sung, C.Y. Lin and H.C. Hu , “Improving neural network prediction of effluent from biological wastewater treatment plant of industrial park using fuzzy learning approach,” Bioprocess and Biosystems Engineering. (2009b).
18.Pai T.Y., S.H. Chuang, T.J. Wan, H.M. Lo, i Y.P. Tsa, H.C. Su, L.F. Yu, H.C. Hu and P.J. Sung, “Comparisons of grey and neural network prediction of industrial park wastewater effluent using influent quality and online monitoring parameters,” Environmental Monitoring and Assessment, 146(1-3), 51-66 (2008a).
19.Pai T.Y. “Gray and neural network prediction of effluent from the wastewater treatment plant of industrial park using influent quality,” Environmental Engineering Science, 25(5), 757-766. (2008b).
20.Acuna G., H. Jorquera, R. Perez, ”Neural network model for maximum ozone concentration prediction., ”Lecture Notes in Computer Science, No.1112, pp.263-268, (1996).
21.Henze M., Gujer W., Mino T. and van Loosdrecht M.C.M.. Activated sludge models: ASM1, ASM2, ASM2d and ASM3, IWA, London(2000).
22.Olsson G. and Newell B., Wastewater Treatment Systems, Modelling, Diagnosis and Control, IWA, London, (2000).
23.Martin T. Hagan, Howard B. Demuth, and Mark Beale, Neural Network Design, PWS Publishing Company, Boston(1996).
24.Pai T.Y., Tsai Y.P., Chen S.W., Chiou R.J. and Tsai C.H. “Prediction of effluent quality from an industrial wastewater treatment plant of deep oxidation ditch process using grey model, ” 1st IWA-ASPIRE Regional Conference and Exhibition, Singapore(2005).
25.Chang S.C., Pai T.Y., Ho H.H., Leu H.G. and Shieh Y.R. Evaluating Taiwan’s air quality variation trends using grey system theory. Journal of the Chinese Institute of Engineers, 30(2), 361-367 (2007).
26.Pai T.Y., Ouyang C.F., Su J.L. and Leu H.G. Modelling the steady-state effluent characteristics of the TNCU process with ASM2d under varied SRT conditions. Journal of the Chinese Institute of Environmental Engineering, 10(1), 35-42 (2000a).
27.Pai T.Y., Ouyang C.F., Liao Y.C. and Leu H.G. Oxygen transfer in gravity flow sewer. Water Science and Technology, 42(3-4), 417-422 (2000b).
28.Pai T.Y., Ouyang C.F., Su J.L. and Leu H.G. Modeling the stable effluent qualities of the A2O process with Activated Sludge Model 2d under different return supernatant. Journal of the Chinese Institute of Engineers, 24(1), 75-84 (2001a).
29.Pai T.Y., Ouyang C.F., Su J.L. and Leu H.G. Modelling the steady-state effluent characteristics of the TNCU process under different return mixed liquid. Applied Mathematical Modelling, 25(12), 1025-1038 (2001b).
30.Pai T.Y., Chuang S.H., Tsai Y.P. and Leu H.G. Development of two-stage nitrification/denitrification model (TaiWan Extension Activated sludge model NO.1) for BNR process. Journal of the Chinese Institute of Environmental Engineering, 14(1), 51-60 (2004a).
31.Pai T.Y., Tsai Y.P., Chou Y.J., Chang H.Y., Leu H.G. and Ouyang C.F. Microbial kinetic analysis of three different types of EBNR process. Chemosphere, 55(1), 109-118 (2004b).
32.Pai T.Y., Chuang S.H., Tsai Y.P. and Ouyang C.F. Modelling a combined anaerobic/anoxic oxide and rotating biological contactors process under dissolved oxygen variation by using an activated sludge - biofilm hybrid model. Journal of Environmental Engineering-ASCE, 130(12), 1433-1441 (2004c).
33.Pai T.Y. Modeling nitrite and nitrate variations in A2O process under different return oxic mixed liquid using an extended model. Process Biochemistry, 42(6), 978-987 (2007).
34.Pai T.Y., Hanaki K., Ho H.H. and Hsieh C.M. Using grey system theory to evaluate transportation on air quality trends in Japan, Transportation Research Part D: Transport and Environment, 12 (3), 158-166 (2007a).
35.Pai T.Y., Tsai Y.P., Lo H.M., Tsai C.H. and Lin C.Y. Grey and neural network prediction of suspended solids and chemical oxygen demand in hospital wastewater treatment plant effluent, Computers & Chemical Engineering, 31(10), 1272-1281 (2007b).
36.Pai T.Y. Gray and neural network prediction of effluent from the wastewater treatment plant of industrial park using influent quality. Environmental Engineering Science, 25(5), 757-766 (2008).
37.Pai T.Y., Chuang S.H., Ho H.H., Yu L.F., Su H.C. and Hu H.C. Predicting performance of grey and neural network in industrial effluent using online monitoring parameters. Process Biochemistry, 43(2), 199-205 (2008a).
38.Pai T.Y., Chuang S.H., Wan T.J., Lo H.M., Tsai Y.P., Su H.C., Yu L.F., Hu H.C. and Sung P.J. Comparisons of grey and neural network prediction of industrial park wastewater effluent using influent quality and online monitoring parameters. Environmental Monitoring and Assessment, 146(1-3), 51-66 (2008b).
39.Pai T.Y., Chiou R.J. and Wen H.H. Evaluating impact level of different factors in environmental impact assessment for incinerator plants using GM (1, N) model. Waste Management, 28(10), 1915-1922 (2008c).
40.Pai T.Y., Wang S.C., Lo H.M., Chiang C.F., Liu M.H., Chiou R.J., Chen W.Y., Hung P. S., Liao W.C., Leu H.G. Novel modeling concept for evaluating the effects of cadmium and copper on heterotrophic growth and lysis rates in activated sludge process. Journal of Hazardous Materials, 166(1), 200-206 (2009a).
41.Pai T.Y., Wan T.J., Hsu S.T., Chang T.C., Tsai Y.P., Lin C.Y., Su H.C. and Yu L.F. Using fuzzy inference system to improve neural network for predicting hospital wastewater treatment plant effluent. Computers & Chemical Engineering, 33(7), 1272-1278 (2009b).
42.Pai T.Y., Wang S.C., Chiang C.F., Su H.C., Yu L.F., Sung P.J., Lin C.Y. and Hu H.C. Improving neural network prediction of effluent from biological wastewater treatment plant of industrial park using fuzzy learning approach. Bioprocess and Biosystems Engineering, 32(6), 781-790 (2009c).
43.Pai T.Y., Chang H.Y., Wan T.J., Chuang S.H. and Tsai Y.P. Using an extended activated sludge model to simulate nitrite and nitrate variations in TNCU2 process. Applied Mathematical Modelling, 33(11), 4259-4268 (2009d).
44.Pai T.Y., Wang S.C., Lin C.Y., Liao W.C., Chu H.H., Lin T.S., Liu C.C. and Lin S.W. Two types of organophosphate pesticides and their combined effects on heterotrophic growth rates in activated sludge process. Journal of Chemical Technology and Biotechnology, 84(12), 1773-1779 (2009e).
45.Pai T.Y., Wan T.J., Tsai Y.P., Tzeng C.J., Chu H.H., Tsai Y.S. and Lin C.Y. Effect of sludge retention time on biomass and kinetic parameter of two nitrifying species in anaerobic/oxic process. CLEAN-Soil Air Water, 38(2), 167-172 (2010a).
46.Pai T.Y., Chiou R.J., Tzeng C.J., Lin T.S., Yeh S.C., Sung P.J., Tseng C.H., Tsai C.H., Tsai Y.S., Hsu W.J. and Wei Y.L. Variation of biomass and kinetic parameter for nitrifying species in TNCU3 process at different aerobic hydraulic retention time. World Journal of Microbiology & Biotechnology, 26(4), 589-597 (2010b).
47.Pai T.Y., Huang J.D., Wang S.C., Chang D.H., Huang K.J., Lee C.C., Lin S.R., Tseng C.H., Sung P.J. and Leu H.G. Evaluate the establishment site of ecological water purification processes in Dali River using QUAL2K. Suatainable Environment Research, 20(4), 239-243 (2010c).
48.Pai T.Y., Chen C.L., Chung H., Ho H.H. and Shiu T.W. Monitoring and assessing variation of sewage quality and microbial functional groups in a trunk sewer line. Environmental Monitoring and Assessment, 171(1-4), 551-560 (2010d).
49.Pai T.Y., Lin K.L., Shie J.L., Chang T.C. and Chen B.Y. Predicting the co-melting temperatures of municipal solid waste incinerator fly ash and sewage sludge ash using grey model and neural network. Waste Management & Research (2011a). (In press)
50.Pai T.Y., Ho C.L., Chen S.W., Lo H.M., Sung P.J., Lin S.W., Lai W.J., Tseng S.C., Ciou S.P., Kuo J.L. and Kao J.T. Using seven types of GM (1, 1) model to forecast hourly particulate matter concentration in Banciao City of Taiwan. Water, Air, and Soil Pollution (2011b). (In press)
51.Pai T.Y., Hanaki K., Su H.C. and Yu L.F. A 24-h forecast of oxidant concentration in Tokyo using neural network and fuzzy learning approach. CLEAN-Soil Air Water (2011c). (In press)
52.Pai T.Y., Yang P.Y., Wang S.C., Lo H.M., Chiang C.F., Kuo J.L., Chu H.H., Su H.C., Yu L.F., Hu H.C. and Chang Y.H. Predicting effluent from the wastewater treatment plant of industrial park based on fuzzy network and influent quality. Applied Mathematical Modelling (2011d). (In press)