基于数据仓库的区域环境质量预测分析系统
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摘要
随着经济的多元化迅猛发展,呈现出的环境问题错综复杂,虽然建立了各类环保信息管理系统,但各系统独自完成日常的业务处理工作。由于系统之间的数据不一致,没有形成一个全面、集成的数据环境,各个信息系统之间沟通不畅,信息共享不能实现,无法满足环境管理决策与数据分析的要求。因此,本文利用基于数据仓库的区域环境质量预测技术有效解决现代环境管理的业务要求及环境决策分析管理要求。
本文在研究数据仓库技术、数据挖掘技术、决策支持技术和相关理论基础上,对系统实现的主要关键技术进行了探讨。针对环境管理用户需求进行系统分析,搭建出基于数据仓库的区域环境质量预测系统结构,并对系统中数据仓库、OLAP和数据挖掘部分进行了相应的设计。在系统实施上,将环境管理行业经验与数据挖掘方法密切结合,体现了系统的适用性、先进行与可扩展性。
本研究利用成都市环保局现有的业务管理系统的元数据,建立区域环境质量分析模型。通过对区域环境质量的变化趋势进行预测分析,为全市环境管理、新项目建设提供决策依据和规划方向,并实现对重大环境事件的预测、预警,提高环保局环境管理水平,为领导决策提供准确的数据依据,为城市建设规划及环境管理工作提供数据支撑。
With the burgeoning development of the diversified economy, a great number of complicated environmental problems have emerged. In order to tackle the problems, we have established various environmental information management systems, but each system deals with its daily business processing work separately. Due to the inconsistency of the data in different systems, the lack of a comprehensive and integrated data environment, as well as the difficulty in information exchange among different systems, smooth information sharing cannot be achieved, which causes the failure of fulfilling the requirement of environmental management decision-making and data analysis. Therefore, this thesis availing the regional environmental quality prediction technology based on data warehouse; effectively meet the requirements of modern environmental management business and environmental decision analysis management.
Based on the study of data warehouse technology, decision support technology and related theoretical foundation, key technologies concerning the implementation of the system are discussed in this thesis. System analyses are made according to the requests from the environmental management clients, so as to set up regional environmental quality prediction system structure based on the data warehouse. Meanwhile, the corresponding designs, including data warehouse, OLAP and data mining are also covered. As to system implementation, the combination of industry experience in environmental management and data mining method fully reflects the applicability, superiority and expansibility of the system.
This research, adopting the existing business management system metadata of Chengdu Environmental Protection Bureau, establishes regional environmental quality analysis model. Through the analysis and prediction of the regional environmental quality trend, decision-making basis and planning direction for the environment management and new projects are provided. The realization of forecast and early warning for major environmental events, and the improvement of the environmental protection management level are made possible. It also provides accurate data for the decision-makers for reference, as well as data support for urban construction planning and environmental management work.
本文在研究数据仓库技术、数据挖掘技术、决策支持技术和相关理论基础上,对系统实现的主要关键技术进行了探讨。针对环境管理用户需求进行系统分析,搭建出基于数据仓库的区域环境质量预测系统结构,并对系统中数据仓库、OLAP和数据挖掘部分进行了相应的设计。在系统实施上,将环境管理行业经验与数据挖掘方法密切结合,体现了系统的适用性、先进行与可扩展性。
本研究利用成都市环保局现有的业务管理系统的元数据,建立区域环境质量分析模型。通过对区域环境质量的变化趋势进行预测分析,为全市环境管理、新项目建设提供决策依据和规划方向,并实现对重大环境事件的预测、预警,提高环保局环境管理水平,为领导决策提供准确的数据依据,为城市建设规划及环境管理工作提供数据支撑。
With the burgeoning development of the diversified economy, a great number of complicated environmental problems have emerged. In order to tackle the problems, we have established various environmental information management systems, but each system deals with its daily business processing work separately. Due to the inconsistency of the data in different systems, the lack of a comprehensive and integrated data environment, as well as the difficulty in information exchange among different systems, smooth information sharing cannot be achieved, which causes the failure of fulfilling the requirement of environmental management decision-making and data analysis. Therefore, this thesis availing the regional environmental quality prediction technology based on data warehouse; effectively meet the requirements of modern environmental management business and environmental decision analysis management.
Based on the study of data warehouse technology, decision support technology and related theoretical foundation, key technologies concerning the implementation of the system are discussed in this thesis. System analyses are made according to the requests from the environmental management clients, so as to set up regional environmental quality prediction system structure based on the data warehouse. Meanwhile, the corresponding designs, including data warehouse, OLAP and data mining are also covered. As to system implementation, the combination of industry experience in environmental management and data mining method fully reflects the applicability, superiority and expansibility of the system.
This research, adopting the existing business management system metadata of Chengdu Environmental Protection Bureau, establishes regional environmental quality analysis model. Through the analysis and prediction of the regional environmental quality trend, decision-making basis and planning direction for the environment management and new projects are provided. The realization of forecast and early warning for major environmental events, and the improvement of the environmental protection management level are made possible. It also provides accurate data for the decision-makers for reference, as well as data support for urban construction planning and environmental management work.
引文
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[2] Damien Watkins, Mark Hammond. Programming in the .NET Environment, 2003, 39-40
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[10]荆著,赵宏霞.数据库与数据仓库.现代管理科学,2008, 56(2):19-22
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[14]陈文伟.决策支持系统教程.北京:清华大学出版社,2005,80-105
[15]徐德智.数据仓库设计方法研究.企业技术开发,2004,20(2):7-9
[16]于宗民,刘义宁.数据仓库项目管理实践.北京:人民邮电出版社,2006,48-78
[17]王欣,徐腾飞,唐连章.SQL Server2005数据挖掘实例分析.北京:中国水利水电出版社,2008,120-145
[18]张磊,钟勇.一种新型数据仓库体系的实现.计算机应用,2003, 12(10):111-113
[19]赵阳.需求分析与维度设计.北京:北京迈思奇科技有限公司,2007,30-56
[20]栾诚,李玉忱.数据仓库维度建模技术在电信行业的应用研究.通信世界,2005,22(16):20-22
[21]张应利,周霞.基于数据仓库的企业营销决策支持系统的设计.华南理工大学学报(自然科学版),2001,10(5):33-33
[22]Rakesh Agrawal, Ramakrishnan Srikant. Fast Algorithms for Mining Association Rules. IBM Almaden Research Center 2008, 1-6
[23]Golfarelli M.Maio D.Rizzi S Conceptual design of data warehouses from E/R schemas ,1998
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[25] (美)ZHAOHUI TANG,JAMIE MACLENNAN著,邝祝芳,焦贤龙,高升译.数据挖掘原理与应用-SQL SERVER 2005数据库.北京:清华大学出版社, 2007,109-205
[26]B.Mobasher, R.Cooley, J. Srivastava. Automatic Personalization Based on Web Personalization, Communications of the ACM, 2000, Vol43(8):142-151
[27]Microsoft Corporation . Layered Application(分层应用程序).
[28]http://www.microsoft.com/china/MSDN/library/architecture/patterns/esp/ArcLayeredApplication.mspx,2004,04-19
[29]侯东风,陆昌辉,刘青宝等.联机分析处理的综述和分析.计算机科学,2008,32(10):12-16
[30]陈氢.几种新型决策支持系统的比较研究.情报科学,2005,24(1):34-37
[31]Inmon W H著,王志海译.数据仓库.北京:机械工业出版社,2003,10-25
[32]Robert J.Hocutt Informix/Red Brick数据仓库开发指南.北京:电子工业出版社,2001,35-56
[33]李中华,张力军,郭颖.基于数据仓库的中国专利审查联机分析处理系统.计算机工程与应用,2003,35-36
[34]A. Wood. Predicting Client/Server Availability. Computer, 2000, 28(4): 46-49
[2] Damien Watkins, Mark Hammond. Programming in the .NET Environment, 2003, 39-40
[3]张维明,邓苏,刘青宝,陈卫东,等.数据仓库原理与应用.北京:电子工业出版社,2002,3-17
[4]M.J.A.Berry and G. Linoff. Data Mining Techniques, New York: John Wiley & Sons,1997,80-105
[5]邢廷炎,吕建军,吴亮.城市环境模糊预测与综合评价信息系统.武汉:中国地质大学出版社,2006,1-72
[6]陈艳春.决策支持系统设计与开发.北京:人民邮电出版社,2007,22-83
[7] W.H.Inmon. Buliding the Data Warehouse Third Edition, John Wiley&Sons Inc, 2002, 26-100
[8]张应利,周霞.基于数据仓库的企业营销决策支持系统的设计.华南理工大学学报(自然科学版),2001,12(10):61-65
[9]鲍玉斌,史捷,王大玲,等.企业级数据仓库设计方法及其实施的关键因素研究.控制与决策,2004, 12(12):35-40
[10]荆著,赵宏霞.数据库与数据仓库.现代管理科学,2008, 56(2):19-22
[11]毛国君,段立娟,王实,等.数据挖掘原理与算法.北京:清华大学出版社,2005,36-66
[12]Peter G.W.Keen. Every Manager's Guide to Information Technology: A Glossary of Key Terms and Concepts for Today's Business Leader. Harvard Business School Press (January 1991),vol 10:113-131
[13]G.Linoff. Which Way to the Mine? . AS/400 System Management, 1998, Vol26:32-47
[14]陈文伟.决策支持系统教程.北京:清华大学出版社,2005,80-105
[15]徐德智.数据仓库设计方法研究.企业技术开发,2004,20(2):7-9
[16]于宗民,刘义宁.数据仓库项目管理实践.北京:人民邮电出版社,2006,48-78
[17]王欣,徐腾飞,唐连章.SQL Server2005数据挖掘实例分析.北京:中国水利水电出版社,2008,120-145
[18]张磊,钟勇.一种新型数据仓库体系的实现.计算机应用,2003, 12(10):111-113
[19]赵阳.需求分析与维度设计.北京:北京迈思奇科技有限公司,2007,30-56
[20]栾诚,李玉忱.数据仓库维度建模技术在电信行业的应用研究.通信世界,2005,22(16):20-22
[21]张应利,周霞.基于数据仓库的企业营销决策支持系统的设计.华南理工大学学报(自然科学版),2001,10(5):33-33
[22]Rakesh Agrawal, Ramakrishnan Srikant. Fast Algorithms for Mining Association Rules. IBM Almaden Research Center 2008, 1-6
[23]Golfarelli M.Maio D.Rizzi S Conceptual design of data warehouses from E/R schemas ,1998
[24]章水,鑫徐,宏炳于,等.立增量式ETL工具的研究与实现.现代计算机,2005,13(3):6-9
[25] (美)ZHAOHUI TANG,JAMIE MACLENNAN著,邝祝芳,焦贤龙,高升译.数据挖掘原理与应用-SQL SERVER 2005数据库.北京:清华大学出版社, 2007,109-205
[26]B.Mobasher, R.Cooley, J. Srivastava. Automatic Personalization Based on Web Personalization, Communications of the ACM, 2000, Vol43(8):142-151
[27]Microsoft Corporation . Layered Application(分层应用程序).
[28]http://www.microsoft.com/china/MSDN/library/architecture/patterns/esp/ArcLayeredApplication.mspx,2004,04-19
[29]侯东风,陆昌辉,刘青宝等.联机分析处理的综述和分析.计算机科学,2008,32(10):12-16
[30]陈氢.几种新型决策支持系统的比较研究.情报科学,2005,24(1):34-37
[31]Inmon W H著,王志海译.数据仓库.北京:机械工业出版社,2003,10-25
[32]Robert J.Hocutt Informix/Red Brick数据仓库开发指南.北京:电子工业出版社,2001,35-56
[33]李中华,张力军,郭颖.基于数据仓库的中国专利审查联机分析处理系统.计算机工程与应用,2003,35-36
[34]A. Wood. Predicting Client/Server Availability. Computer, 2000, 28(4): 46-49