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題名 大台北都會區空氣污染指標之時空數列分析 作者 廖敏治
LIAO, MIN-ZHI貢獻者 吳柏林
廖敏治
LIAO, MIN-ZHI關鍵詞 時空數列
STARMA模式
空氣污染指標值(PSI)日期 1992
1991上傳時間 2-May-2016 17:07:15 (UTC+8) 摘要 摘要 參考文獻 中文部份 蔣本基。(1987) 。高雄市空氣污染受體接式之研究。國立台灣大學環境工程研究所研究報告。 行政院環境保護署。(1987-1991) 。中華民國環境保護統計月報。台北:行政院環境保護署。 呂世宗。(1988) 。大都會星空氣品質污染潛勢預測之研究。第一階段:台北地區，國立中央大學大氣物理系研究報告。 行政院環境保護署。(1989) 。中華民國臺灣地區環境資訊。台北:行政院環境保護署。 行政院環境保護署。(1990) 。臺灣地區空氣品質監測現況報告。台北:行政院環境保護署。 李清勝、陳泰然和俞家忠。( 1990) 。即時氣象資料應用在空氣污染分析之研究與實驗。期中報告，台北:行政院環境保護署。 蔡俊鴻。(1990) 。空氣品質監測與微尺度氣象觀測之區成代表性檢討。期中報告，台北:行政院環境保護署。 鄒惠斌、羅夢娜和黃妙冠。(1990) 。雨量及風迷對空氣品質影響之非線性模式的探討。中國統計月報，第28卷，第一期。 陳得均、季延安和林肇信。(1991) 。大氣污染化學，五版。科技圖書及份限公司。 英文部份 Aroian. L.A.(1985). `Time series in M dimensions: past present, and fuure`,in O. D. Anderson, J. K. Ord and E. A. Robinson(eds), Time Series Analysis: Theory and Practice, 6, Amsterdam: North-Holland. Bennet, RJ. (1975). `The representation and identification of spatiotemporal systems: an example of popukation diffusion in North-West England`, Trans. In st. British Geographer, 66,73-94. Bennet, R. J. (1979). Spatial Time Series. Pion Limited, London.Besag,J.S. (1974). Spatial Interaction and the Statistical Analysis of Lattice Systems. Journal of the Royal Statistical Society, Ser. B, 36, 197-242. BoxG. E. P. and Jinkins,G. M. (1976). Time series Analysis Forecasting and Control, 2nd ed., Hoiden-Day, San Francisco. Cliff,A. D. and Ord,J. K.(1973). Spatial Autocorrelation. London Pioneer. Cliff,A. D., Haggett, P. Ord,J.K., Bassett, K. A. andDaries, R.B. (1975) Elements of Spatial Structure: A Quantitative Approach. New York :Combride University press. Cliff,A. D. and Ord,J. K.(1975). Space-Time Modeling with an Application to Regional Forecasting. Trans.Inst. British Geographer, 66,119-128. Cliff, A. D., and Ord, J. K.(1981). Spatial Processes and Models and Applications. Pions Limited, London. Deutsch, SJ.and Ramos, J.A.(1987). Space-Time Modeling of Vector Hydrologic Sequences. Water Resources Bulletin, 22, 967-981. Kosko,B. (1992). NeuralNetworks for Signal Processing. Prentice Hall,Englewood Cliffs, NJ. Lee, K. Y. , Cha, Y. T. and Part ,J.H. (1991). Short-tenn LoadForecasting Using an Artificial Neural Network; , IEEE Winter Power Meeting. Marquardt,D. W. (1963). Algorithm for Least Squares Estimation of Non-linear Parameters. 1. Soc. and APPUED Math.,11, 431-41. Martin, R. E. and Oeppen,J.E. (1975). The Identification of Regional Forecasting Models Using Space-Time Correlation Function. Trans. Inst.British Geographers,66, 95-118. Park, D. C. El-sharkawi, M. A., Marks, R. J. , Atlas, L. E. and Damborg, m. j. (1991). Electric Load Forecasting Using an Artificial Neural Network.IEEE Winter Power Meeting. Perry, R. and Aroian, L.A. (1979). Of Time and the River: Time Series in M Dimension, the One-Dimension Autoregressive Model. Proceedings of the American Statistical Association, Statistical Computing Section. Phillip E. Pfeifer. (1979). Spatial-DyamicModeling. Georgia Institute of Technology. Phillip E. Pfeifer and Stuart Jay Deudsch. (1980a). A Three-Stage Iterative Process for Space-Time Modeling. Technometrics, 22, 35-47. Phillip E. Pfeifer and Stuart Jay Deudsch. (1980b). Identification and Interpretation of First Order Space-Time ARMA Modeling. Technometrics,22, 397-408. PhillipE. Pfeifer and Stuart Jay Deudsch. (!981). Seasonal Space-Time Modeling. Geographical Analysis, 13, 117-133. Phillip E. Pfeiffer and Samuel E. Bodily. (1990). A Test of Space-Time ARMA Modeling and Forecasting of Hotel Data. Journal of Forecasting,9, 225-272. Rame, J. (1989). Neural Computing. l. Neural Ware, Inc. Pittsburgh. Reylonds, K. M. and Madden, L. V. (1988). Analysis of Epidemics Using Spatio-Temporal autocorrelation. Phytopathology, 78,240-245. Stoffer, D. S. (1986). Estimation and Identification of Space -Time ARMAX Models in the Presence of Missing Data. Journal of the American Statistical Association, 81, 246-52. Stuart Jay Deutsch and Phillip E. Pfiffer. (1981). Space-time ARMA Modeling with Cotemporaneously Correlated Innovaaations. Technometrics,23, 401-409 Tinline, R. (1971). Linear Operators in Diffusion Research. in M. D. I. Chisolm, et al. (eds), Regional Forecasting, London: Butterworths. Tobler, W. R. (1969). Geographical Filters and Their Inverses. Geo graphical Analysis, 1, 234-53. Tobler, W. R. (1970). A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography, 46, 234-40. 描述 碩士
國立政治大學
應用數學系資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002004733 資料類型 thesis dc.contributor.advisor 吳柏林 zh_TW dc.contributor.author (Authors) 廖敏治 zh_TW dc.contributor.author (Authors) LIAO, MIN-ZHI en_US dc.creator (作者) 廖敏治 zh_TW dc.creator (作者) LIAO, MIN-ZHI en_US dc.date (日期) 1992 en_US dc.date (日期) 1991 en_US dc.date.accessioned 2-May-2016 17:07:15 (UTC+8) - dc.date.available 2-May-2016 17:07:15 (UTC+8) - dc.date.issued (上傳時間) 2-May-2016 17:07:15 (UTC+8) - dc.identifier (Other Identifiers) B2002004733 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/89757 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 應用數學系 zh_TW dc.description.abstract (摘要) 摘要 zh_TW dc.description.tableofcontents 目錄 摘要 壹 前言 1 貳 理論方法 4 (一)時空數列模式的定義…………………..4 (二)三階段模式的建立…………………..7 參 資料分析 17 肆 模式的建立與選擇 23 伍 預測結果 31 陸 結論與建議 35 參考文獻 36 zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002004733 en_US dc.subject (關鍵詞) 時空數列 zh_TW dc.subject (關鍵詞) STARMA模式 zh_TW dc.subject (關鍵詞) 空氣污染指標值(PSI) zh_TW dc.title (題名) 大台北都會區空氣污染指標之時空數列分析 zh_TW dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 中文部份 蔣本基。(1987) 。高雄市空氣污染受體接式之研究。國立台灣大學環境工程研究所研究報告。 行政院環境保護署。(1987-1991) 。中華民國環境保護統計月報。台北:行政院環境保護署。 呂世宗。(1988) 。大都會星空氣品質污染潛勢預測之研究。第一階段:台北地區，國立中央大學大氣物理系研究報告。 行政院環境保護署。(1989) 。中華民國臺灣地區環境資訊。台北:行政院環境保護署。 行政院環境保護署。(1990) 。臺灣地區空氣品質監測現況報告。台北:行政院環境保護署。 李清勝、陳泰然和俞家忠。( 1990) 。即時氣象資料應用在空氣污染分析之研究與實驗。期中報告，台北:行政院環境保護署。 蔡俊鴻。(1990) 。空氣品質監測與微尺度氣象觀測之區成代表性檢討。期中報告，台北:行政院環境保護署。 鄒惠斌、羅夢娜和黃妙冠。(1990) 。雨量及風迷對空氣品質影響之非線性模式的探討。中國統計月報，第28卷，第一期。 陳得均、季延安和林肇信。(1991) 。大氣污染化學，五版。科技圖書及份限公司。 英文部份 Aroian. L.A.(1985). `Time series in M dimensions: past present, and fuure`,in O. D. Anderson, J. K. Ord and E. A. Robinson(eds), Time Series Analysis: Theory and Practice, 6, Amsterdam: North-Holland. Bennet, RJ. (1975). `The representation and identification of spatiotemporal systems: an example of popukation diffusion in North-West England`, Trans. In st. British Geographer, 66,73-94. Bennet, R. J. (1979). Spatial Time Series. Pion Limited, London.Besag,J.S. (1974). Spatial Interaction and the Statistical Analysis of Lattice Systems. Journal of the Royal Statistical Society, Ser. B, 36, 197-242. BoxG. E. P. and Jinkins,G. M. (1976). Time series Analysis Forecasting and Control, 2nd ed., Hoiden-Day, San Francisco. Cliff,A. D. and Ord,J. K.(1973). Spatial Autocorrelation. London Pioneer. Cliff,A. D., Haggett, P. Ord,J.K., Bassett, K. A. andDaries, R.B. (1975) Elements of Spatial Structure: A Quantitative Approach. New York :Combride University press. Cliff,A. D. and Ord,J. K.(1975). Space-Time Modeling with an Application to Regional Forecasting. Trans.Inst. British Geographer, 66,119-128. Cliff, A. D., and Ord, J. K.(1981). Spatial Processes and Models and Applications. Pions Limited, London. Deutsch, SJ.and Ramos, J.A.(1987). Space-Time Modeling of Vector Hydrologic Sequences. Water Resources Bulletin, 22, 967-981. Kosko,B. (1992). NeuralNetworks for Signal Processing. Prentice Hall,Englewood Cliffs, NJ. Lee, K. Y. , Cha, Y. T. and Part ,J.H. (1991). Short-tenn LoadForecasting Using an Artificial Neural Network; , IEEE Winter Power Meeting. Marquardt,D. W. (1963). Algorithm for Least Squares Estimation of Non-linear Parameters. 1. Soc. and APPUED Math.,11, 431-41. Martin, R. E. and Oeppen,J.E. (1975). The Identification of Regional Forecasting Models Using Space-Time Correlation Function. Trans. Inst.British Geographers,66, 95-118. Park, D. C. El-sharkawi, M. A., Marks, R. J. , Atlas, L. E. and Damborg, m. j. (1991). Electric Load Forecasting Using an Artificial Neural Network.IEEE Winter Power Meeting. Perry, R. and Aroian, L.A. (1979). Of Time and the River: Time Series in M Dimension, the One-Dimension Autoregressive Model. Proceedings of the American Statistical Association, Statistical Computing Section. Phillip E. Pfeifer. (1979). Spatial-DyamicModeling. Georgia Institute of Technology. Phillip E. Pfeifer and Stuart Jay Deudsch. (1980a). A Three-Stage Iterative Process for Space-Time Modeling. Technometrics, 22, 35-47. Phillip E. Pfeifer and Stuart Jay Deudsch. (1980b). Identification and Interpretation of First Order Space-Time ARMA Modeling. Technometrics,22, 397-408. PhillipE. Pfeifer and Stuart Jay Deudsch. (!981). Seasonal Space-Time Modeling. Geographical Analysis, 13, 117-133. Phillip E. Pfeiffer and Samuel E. Bodily. (1990). A Test of Space-Time ARMA Modeling and Forecasting of Hotel Data. Journal of Forecasting,9, 225-272. Rame, J. (1989). Neural Computing. l. Neural Ware, Inc. Pittsburgh. Reylonds, K. M. and Madden, L. V. (1988). Analysis of Epidemics Using Spatio-Temporal autocorrelation. Phytopathology, 78,240-245. Stoffer, D. S. (1986). Estimation and Identification of Space -Time ARMAX Models in the Presence of Missing Data. Journal of the American Statistical Association, 81, 246-52. Stuart Jay Deutsch and Phillip E. Pfiffer. (1981). Space-time ARMA Modeling with Cotemporaneously Correlated Innovaaations. Technometrics,23, 401-409 Tinline, R. (1971). Linear Operators in Diffusion Research. in M. D. I. Chisolm, et al. (eds), Regional Forecasting, London: Butterworths. Tobler, W. R. (1969). Geographical Filters and Their Inverses. Geo graphical Analysis, 1, 234-53. Tobler, W. R. (1970). A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography, 46, 234-40. zh_TW
