Enhanced validity and reliability of spatial decision support systems (SDSS) for sustainable transportation decision-making

2014 ◽  
Vol 51 ◽  
pp. 65-71 ◽  
Author(s):  
Hwan Yong Kim ◽  
Hye Kyung Lee
2011 ◽  
pp. 614-636
Author(s):  
Shan Gao ◽  
David Sundaram

Spatial decision-making is a key aspect of human behaviour. Spatial decision support systems support spatial decision-making processes by integrating required information, tools, models and technology in a user-friendly manner. While current spatial decision support systems fulfil their specific objectives, they fail to address many of the requirements for effective spatial problem solving, as they are inflexible, complex to use and often domain-specific. This research blends together several relevant disciplines to overcome the problems identified in various areas of spatial decision support. We proposed a generic spatial decision-making process and a domain-independent spatial decision support system (SDSS) framework and architecture to support the process. We also developed a flexible SDSS to demonstrate an environment in which decision makers can utilize various tools and explore different scenarios to derive a decision. The use of the system is demonstrated in a number of real scenarios across location, allocation, routing, layout, and spatio-temporal problems.


2010 ◽  
pp. 532-555
Author(s):  
Shan Gao ◽  
David Sundaram

Spatial decision-making is a key aspect of human behaviour. Spatial decision support systems support spatial decision-making processes by integrating required information, tools, models and technology in a user-friendly manner. While current spatial decision support systems fulfil their specific objectives, they fail to address many of the requirements for effective spatial problem solving, as they are inflexible, complex to use and often domain-specific. This research blends together several relevant disciplines to overcome the problems identified in various areas of spatial decision support. We proposed a generic spatial decision-making process and a domain-independent spatial decision support system (SDSS) framework and architecture to support the process. We also developed a flexible SDSS to demonstrate an environment in which decision makers can utilize various tools and explore different scenarios to derive a decision. The use of the system is demonstrated in a number of real scenarios across location, allocation, routing, layout, and spatio-temporal problems.


Author(s):  
Shan Gao ◽  
David Sundaram

Spatial decision-making is a key aspect of human behaviour. Spatial decision support systems support spatial decision-making processes by integrating required information, tools, models and technology in a user-friendly manner. While current spatial decision support systems fulfil their specific objectives, they fail to address many of the requirements for effective spatial problem solving, as they are inflexible, complex to use and often domain-specific. This research blends together several relevant disciplines to overcome the problems identified in various areas of spatial decision support. We proposed a generic spatial decision-making process and a domain-independent spatial decision support system (SDSS) framework and architecture to support the process. We also developed a flexible SDSS to demonstrate an environment in which decision makers can utilize various tools and explore different scenarios to derive a decision. The use of the system is demonstrated in a number of real scenarios across location, allocation, routing, layout, and spatio-temporal problems.


2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Luciana Moura Mendes de Lima ◽  
Laísa Ribeiro de Sá ◽  
Ana Flávia Uzeda dos Santos Macambira ◽  
Jordana de Almeida Nogueira ◽  
Rodrigo Pinheiro de Toledo Vianna ◽  
...  

Abstract Background Decision making in the health area usually involves several factors, options and data. In addition, it should take into account technological, social and spatial aspects, among others. Decision making methodologies need to address this set of information , and there is a small group of them with focus on epidemiological purposes, in particular Spatial Decision Support Systems (SDSS). Methods Makes uses a Multiple Criteria Decision Making (MCDM) method as a combining rule of results from a set of SDSS, where each one of them analyzes specific aspects of a complex problem. Specifically, each geo-object of the geographic region is processed, according to its own spatial information, by an SDSS using spatial and non-spatial data, inferential statistics and spatial and spatio-temporal analysis, which are then grouped together by a fuzzy rule-based system that will produce a georeferenced map. This means that, each SDSS provides an initial evaluation for each variable of the problem. The results are combined by the weighted linear combination (WLC) as a criterion in a MCDM problem, producing a final decision map about the priority levels for fight against a disease. In fact, the WLC works as a combining rule for those initial evaluations in a weighted manner, more than a MCDM, i.e., it combines those initial evaluations in order to build the final decision map. Results An example of using this new approach with real epidemiological data of tuberculosis in a Brazilian municipality is provided. As a result, the new approach provides a final map with four priority levels: “non-priority”, “non-priority tendency”, “priority tendency” and “priority”, for the fight against diseases. Conclusion The new approach may help public managers in the planning and direction of health actions, in the reorganization of public services, especially with regard to their levels of priorities.


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