The Nature-Based Solutions Case-Based System: A hybrid expert system

Date

2022-12-01

Author

Sarabi, Shahryar
Han, Qi
de Vries, Bauke
Romme, A. Georges L.
Sayman-almassy, Dora

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Deriving knowledge and learning from past experiences is essential for the successful adoption of Nature-Based Solutions (NBS) as novel integrative solutions that involve many uncertainties. Past experiences in implementing NBS have been collected in a number of repositories; however, it is a major challenge to derive knowledge from the huge amount of information provided by these repositories. This calls for information systems that can facilitate the knowledge extraction process. This paper introduces the NBS Case-Based System (NBS-CBS), an expert system that uses a hybrid architecture to derive information and recommendations from an NBS experience repository. The NBS-CBS combines a 'black-box' artificial neural networks model with a 'white-box' case-based reasoning model to deliver an intelligent, adaptive, and explainable system. Experts have tested this system to assess its functionality and accuracy. Accordingly, the NBS-CBS appears to provide inspirational recommendations and information for the NBS planning and design process.

URI

https://hdl.handle.net/11511/117572

Collections

Department of City and Regional Planning, Article