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Internet-based fuzzy logic and stati...

Zeng, Yinghui.

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Internet-based fuzzy logic and statistics models for integrated solid waste management planning.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Internet-based fuzzy logic and statistics models for integrated solid waste management planning./
作者:	Zeng, Yinghui.
面頁冊數:	192 p.
附註:	Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1106.
Contained By:	Dissertation Abstracts International66-02B.
標題:	Engineering, Environmental. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3164557
ISBN:	0496990683

Internet-based fuzzy logic and statistics models for integrated solid waste management planning.
Zeng, Yinghui.

Internet-based fuzzy logic and statistics models for integrated solid waste management planning. - 192 p.

Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1106.

Thesis (Ph.D.)--University of Missouri - Columbia, 2004.

Huge volumes of solid waste are generated nationwide and the rate of generation is increasing as the population and economic activity increase. The available landfill volume is limited and new landfills are expensive to open and operate because of stringent regulations. This situation will cause problems if solid waste is not managed properly. To solve this problem, solid waste needs to be handled in a sustainable way. For a waste management system to be sustainable, it must be economically affordable, socially acceptable and environmentally sound. These constraints are often qualitative and sometimes conflicting and are difficult to model. The optimal combination of solid waste management options is also affected by the characteristics of the local waste stream, which varies with locations and seasons. The best solid waste management system for a given region has to be determined based on local waste stream conditions, the opinions of different stakeholders, and the social, economic and environmental effects, along with government regulations. Due to the uncertainties that exist in many intertwined system variables, the decision process for planning a sustainable integrated solid waste management system becomes extremely complicated.

ISBN: 0496990683Subjects--Topical Terms:

783782
Engineering, Environmental.

Internet-based fuzzy logic and statistics models for integrated solid waste management planning.
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520 $a Huge volumes of solid waste are generated nationwide and the rate of generation is increasing as the population and economic activity increase. The available landfill volume is limited and new landfills are expensive to open and operate because of stringent regulations. This situation will cause problems if solid waste is not managed properly. To solve this problem, solid waste needs to be handled in a sustainable way. For a waste management system to be sustainable, it must be economically affordable, socially acceptable and environmentally sound. These constraints are often qualitative and sometimes conflicting and are difficult to model. The optimal combination of solid waste management options is also affected by the characteristics of the local waste stream, which varies with locations and seasons. The best solid waste management system for a given region has to be determined based on local waste stream conditions, the opinions of different stakeholders, and the social, economic and environmental effects, along with government regulations. Due to the uncertainties that exist in many intertwined system variables, the decision process for planning a sustainable integrated solid waste management system becomes extremely complicated.
520 $a Because of the complexities involved in the decision process, sophisticated models are needed to address two important tasks. The first is to characterize the solid waste stream and the second is to select the best combination of waste management options. The objective of this study focused on developing new methods for these two tasks. A fuzzy multicriteria decision support framework is developed in this study. The fuzzy model manipulates the elements of integrated solid waste management and takes input data from six different input domains including the organization of stakeholders the definition of evaluation criteria, the determination of criteria values, waste characterization, the evaluation of the current status and alternatives for solid waste management and other information such regulations, market, etc. A statistical model was developed for waste characterization that is an important input domain for the fuzzy model. A case study was conducted for the City of Columbia to illustrate the application of statistical model and the Internet-based fuzzy model. Future work needs to be conducted to develop sub-models for other input domains and to develop case studies for those models.
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