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

Sarabi S., Han Q., de Vries B., Romme A. G. L., Almassy D.

JOURNAL OF ENVIRONMENTAL MANAGEMENT, cilt.324, 2022 (SCI-Expanded, Scopus) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 324
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1016/j.jenvman.2022.116413
  • Dergi Adı: JOURNAL OF ENVIRONMENTAL MANAGEMENT
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, International Bibliography of Social Sciences, PASCAL, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Communication Abstracts, EMBASE, Environment Index, Geobase, Greenfile, Index Islamicus, MEDLINE, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

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.