Pseudoinverse learning of Fuzzy Cognitive Maps for multivariate time series forecasting
dc.creator | Vanhoenshoven F. | |
dc.creator | Nápoles G. | |
dc.creator | Froelich W. | |
dc.creator | Salmeron J.L. | |
dc.creator | Vanhoof K. | |
dc.date.accessioned | 2020-09-02T22:29:55Z | |
dc.date.accessioned | 2022-11-08T20:22:32Z | |
dc.date.available | 2020-09-02T22:29:55Z | |
dc.date.available | 2022-11-08T20:22:32Z | |
dc.date.created | 2020-09-02T22:29:55Z | |
dc.date.issued | 2020 | |
dc.identifier | 95, , - | |
dc.identifier | 15684946 | |
dc.identifier | https://hdl.handle.net/20.500.12728/6516 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/5144461 | |
dc.language | en | |
dc.publisher | Elsevier Ltd | |
dc.subject | Forecasting | |
dc.subject | Fuzzy Cognitive Maps | |
dc.subject | Learning | |
dc.subject | Time series | |
dc.subject | Cognitive systems | |
dc.subject | Forecasting | |
dc.subject | Fuzzy rules | |
dc.subject | Inverse problems | |
dc.subject | Time series | |
dc.subject | Forecasting modeling | |
dc.subject | Forecasting models | |
dc.subject | Fuzzy cognitive map | |
dc.subject | Fuzzy cognitive maps (FCMs) | |
dc.subject | Innovative approaches | |
dc.subject | Multi-step prediction | |
dc.subject | Multivariate time series | |
dc.subject | Real-world scenario | |
dc.subject | Learning algorithms | |
dc.title | Pseudoinverse learning of Fuzzy Cognitive Maps for multivariate time series forecasting | |
dc.type | Article |