Predicting Monthly River Flows by Genetic Fuzzy Systems
| dc.contributor.author | Turan, ME | |
| dc.contributor.author | Yurdusev, MA | |
| dc.date.accessioned | 2024-07-18T11:39:15Z | |
| dc.date.available | 2024-07-18T11:39:15Z | |
| dc.description.abstract | Reliable flow forecasts are key to developing river regulation schemes such as reservoirs. River flow prediction has conventionally been undertaken by physical and black-box models. Several black-box type models have been employed to achieve this end. Of these, genetic fuzzy systems have been used in this study as they have relatively attracted limited attention to date. Genetic-fuzzy systems are the fuzzy systems that have the capability of learning and tuning by Genetic Algorithms. Employing two different fuzzy inference systems, a case study on Gediz river basin has been performed in an attempt to find a suitable genetic fuzzy system for flow prediction. | |
| dc.identifier.issn | 0920-4741 | |
| dc.identifier.other | 1573-1650 | |
| dc.identifier.uri | http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/1506 | |
| dc.language.iso | English | |
| dc.publisher | SPRINGER | |
| dc.subject | EVAPOTRANSPIRATION | |
| dc.subject | MODEL | |
| dc.title | Predicting Monthly River Flows by Genetic Fuzzy Systems | |
| dc.type | Article |