| Texto completo | |
| Autor(es): |
Bankole, Abayomi O.
;
Moruzzi, Rodrigo
;
Negri, Rogerio G.
;
Oishi, Cassio M.
;
Bankole, Afolashade R.
;
James, Abraham O.
Número total de Autores: 6
|
| Tipo de documento: | Artigo Científico |
| Fonte: | SOFTWARE IMPACTS; v. 20, p. 3-pg., 2024-05-23. |
| Resumo | |
This paper presents a scalable framework for modeling floc evolution and flocculation kinetics in water treatment. Unlike the existing methods that subjects Non-intrusive Dynamic Image Analysis (NiDIA) data to complex mathematical concepts, the proposed software devised a scaling concept for NiDIA data and designed an effective algorithm with the capability to predict varying floc lengths and the underlying kinetics under a broad flocculation conditions (Gf and Tf). Technically, the designed machine-intelligence framework (MINiDIA) involves data preprocessing, automatic parameter selection, validation and prediction of floc length evolution with metrics. For instance, MI-NiDIA-MLP recorded R2 of 0.95-1.0 for varying floc length at Gf60 s-1. (AU) | |
| Processo FAPESP: | 23/08052-1 - Misturadores de fractal e velocidade terminal dos agregados formados |
| Beneficiário: | Rodrigo Braga Moruzzi |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |