Development of adaptive neuro-fuzzy inference system model for predict trihalomethane formation potential in distribution network simulation test
| dc.authorid | 0000-0003-2734-8544 | |
| dc.authorid | 0000-0003-2734-8544 | |
| dc.authorid | 0000-0002-2365-3093 | |
| dc.contributor.author | Alver, Alper | |
| dc.contributor.author | Baştürk, Emine | |
| dc.contributor.author | Kılıç, Ahmet | |
| dc.date.accessioned | 2021-04-27T10:24:16Z | |
| dc.date.available | 2021-04-27T10:24:16Z | |
| dc.date.issued | 2021 | |
| dc.department | Mühendislik Fakültesi | |
| dc.description | *Alver, Alper ( Aksaray, Yazar ) | |
| dc.description.abstract | Trihalomethanes (THMs), which is one of the major classes of DBP known to be highly cytotoxic and genotoxic, were formed and modeled under controlled conditions by laboratory-scale distribution network simulation test. The formation potentials of THM depending on the parameters such as natural organic matter, bromide, chlorine, pH, and contact time were determined. Subsequently, the Adaptive Neuro-Fuzzy Inference System (ANFIS) model was developed using these parameters as inputs and THM formation potentials as output, and the correlation coefficient was 0.9817. In the range of the inputs, the ANFIS model representing the simulation test results were compared with THM formations of an actual distribution network system in dry and wet seasons. As a result, the predictions of the ANFIS model were little affected by the unidentified factors that were not used in model training but are known to affect THM formations in real waters and gave more consistent results than the EPA model. | |
| dc.identifier.doi | 10.1007/s11356-020-11801-0 | |
| dc.identifier.endpage | 15882 | en_US |
| dc.identifier.issue | 1 | en_US |
| dc.identifier.pmid | 33244689 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.startpage | 15870 | en_US |
| dc.identifier.uri | https:/dx.doi.org/10.1007/s11356-020-11801-0 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12451/7903 | |
| dc.identifier.volume | 5 | en_US |
| dc.identifier.wos | WOS:000593014400006 | |
| dc.identifier.wosquality | Q2 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.indekslendigikaynak | PubMed | |
| dc.language.iso | en | |
| dc.publisher | American Institute of Physics | |
| dc.relation.ispartof | APL Bioengineering | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Başka Kurum Yazarı | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Natural Organic Matter | |
| dc.subject | Disinfection by-products | |
| dc.subject | Trihalomethanes | |
| dc.subject | Simulation Test | |
| dc.subject | Adaptive Neuro-fuzzy Inference System | |
| dc.title | Development of adaptive neuro-fuzzy inference system model for predict trihalomethane formation potential in distribution network simulation test | |
| dc.type | Article |
