Fuzzy inference system as an aggregation operator: application to the design of a soil chemical quality index
| Autor: | Denys Yohana Mora-Herrera, Didier Snoeck, Serge Guillaume, Orlando Zúñiga Escobar |
|---|---|
| Přispěvatelé: | Universidad del Valle [Cali] (Univalle), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Performance des systèmes de culture des plantes pérennes (UPR Système de pérennes), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Aggregate (data warehouse) Fuzzy set Decision Multicriteria 04 agricultural and veterinary sciences 02 engineering and technology computer.software_genre Fuzzy logic Article Preference Set (abstract data type) Operator (computer programming) Choquet integral [SDE]Environmental Sciences 040103 agronomy & agriculture 0202 electrical engineering electronic engineering information engineering 0401 agriculture forestry and fisheries 020201 artificial intelligence & image processing Data mining Raw data Preference relation Fusion computer |
| Zdroj: | Communications in Computer and Information Science 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Jun 2020, Lisbon, Portugal. pp.447-456, ⟨10.1007/978-3-030-50143-3_35⟩ Information Processing and Management of Uncertainty in Knowledge-Based Systems ISBN: 9783030501426 IPMU (2) Information Processing and Management of Uncertainty in Knowledge-Based Systems |
| DOI: | 10.1007/978-3-030-50143-3_35⟩ |
| Popis: | International audience; Fuzzy logic is widely used in linguistic modeling. In this work, fuzzy logic is used in a multicriteria decision making framework in two different ways. First, fuzzy sets are used to model an expert preference relation for each of the individual information sources to turn raw data into satisfaction degrees. Second, fuzzy rules are used to model the interaction between sources to aggregate the individual degrees into a global score. The whole framework is implemented as an open source software called GeoFIS. The potential of the method is illustrated using an agronomic case study to design a soil chemical quality index from expert knowledge for cacao production systems. The data come from three municipalities of Tolima department in Colombia. The output inferred by the fuzzy inference system was used as a target to learn the weights of classical numerical aggregation operators. Only the Choquet Integral proved to have a similar modeling ability, but the weights would have been difficult to set from expert knowledge without learning. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|