Supporting modeling and problem solving from precedent experiences: the role of workflows and case-based reasoning [An article from: Environmental Modelling and Software]
Book Details
PublisherElsevier
ISBN / ASINB000RR4L3S
ISBN-13978B000RR4L31
AvailabilityAvailable for download now
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Environmental Modelling and Software, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Environmental planners take advantage of Spatial Decision Support Systems (SDSS) to deal with data and models for problem solving. However, these kinds of software usually provide generic models, which require considerable effort to be specialized to fit particular situations. This paper explores a solution which couples Case-Based Reasoning (CBR) to an existing SDSS, named WOODSS, to help planners to profit from others' experiences. WOODSS is based on a Geographic Information System, and interactively documents planners' modeling activities by means of scientific workflows, that are stored in a database. This paper describes how CBR has been used as part of WOODSS' retrieval and storage mechanisms, to identify similar models to reuse in new decision processes. This adds a new dimension to the functionality of available SDSS.
Description:
Environmental planners take advantage of Spatial Decision Support Systems (SDSS) to deal with data and models for problem solving. However, these kinds of software usually provide generic models, which require considerable effort to be specialized to fit particular situations. This paper explores a solution which couples Case-Based Reasoning (CBR) to an existing SDSS, named WOODSS, to help planners to profit from others' experiences. WOODSS is based on a Geographic Information System, and interactively documents planners' modeling activities by means of scientific workflows, that are stored in a database. This paper describes how CBR has been used as part of WOODSS' retrieval and storage mechanisms, to identify similar models to reuse in new decision processes. This adds a new dimension to the functionality of available SDSS.
