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

被引:8
作者
Sarabi, Shahryar [1 ]
Han, Qi [1 ]
de Vries, Bauke [1 ]
Romme, A. Georges L. [2 ]
Almassy, Dora [3 ]
机构
[1] Eindhoven Univ Technol, Dept Built Environm, Informat Syst Built Environm ISBE Grp, Groene Loper 3, NL-5612 AE Eindhoven, Netherlands
[2] Eindhoven Univ Technol, Dept Ind Engn & Innovat Sci, Groene Loper 3, NL-5612 AE Eindhoven, Netherlands
[3] Cent European Univ, Dept Environm Sci & Policy, Vienna, Austria
关键词
Nature-based solutions; NBS; Expert system; Artificial intelligence; Knowledge extraction; Case-based reasoning; NEURAL-NETWORK; SUPPORT-SYSTEMS;
D O I
10.1016/j.jenvman.2022.116413
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页数:8
相关论文
共 65 条
  • [11] Rule-induction and case-based reasoning: Hybrid architectures appear advantageous
    Cercone, N
    An, AJ
    Chan, C
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 1999, 11 (01) : 166 - 174
  • [12] Mapping the effectiveness of nature-based solutions for climate change adaptation
    Chausson, Alexandre
    Turner, Beth
    Seddon, Dan
    Chabaneix, Nicole
    Girardin, Cecile A. J.
    Kapos, Valerie
    Key, Isabel
    Roe, Dilys
    Smith, Alison
    Woroniecki, Stephen
    Seddon, Nathalie
    [J]. GLOBAL CHANGE BIOLOGY, 2020, 26 (11) : 6134 - 6155
  • [13] Cohen-Shacham E., 2016, IUCN, DOI [10.2305/IUCN.CH.2016.13, DOI 10.2305/IUCN.CH.2016.13]
  • [14] Corchado J.M., 2001, Soft Computing in Case Based Reasoning, P293, DOI [10.1007/978-1-4471-0687-6_13, DOI 10.1007/978-1-4471-0687-6_13]
  • [15] Effectiveness of Nature-Based Solutions on Pluvial Flood Hazard Mitigation: The Case Study of the City of Eindhoven (The Netherlands)
    Costa, Sandra
    Peters, Rik
    Martins, Ricardo
    Postmes, Luuk
    Keizer, Jan Jacob
    Roebeling, Peter
    [J]. RESOURCES-BASEL, 2021, 10 (03):
  • [16] Craig R.D., 2002, SYSTEMATIC SOFTWARE
  • [17] Case Based Reasoning as a Model for Cognitive Artificial Intelligence
    Craw, Susan
    Aamodt, Agnar
    [J]. CASE-BASED REASONING RESEARCH AND DEVELOPMENT, ICCBR 2018, 2018, 11156 : 62 - 77
  • [18] Cunningham P., 1998, Tasks and Methods in Applied Artificial Intelligence. 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-98-AIE. Proceedings, P517, DOI 10.1007/3-540-64574-8_437
  • [19] Integrating spatial relations into case-based reasoning to solve geographic problems
    Du, Y.
    Liang, F.
    Sun, Y.
    [J]. KNOWLEDGE-BASED SYSTEMS, 2012, 33 : 111 - 123
  • [20] FORD FN, 1985, INFORM MANAGE, V8, P21, DOI 10.1016/0378-7206(85)90066-7