Open Access Open Access  Restricted Access Subscription or Fee Access

Construction of a Novel Water Quality Classifier: A case study in the Sebou region

Mariam ELKHECHAFI, Hanaa ACHIMI, Aouatif AMINE, Youssfi El KETTANI

Abstract



This study focuses on the evaluation of the water quality in the Sebou area, by applying the hybridization method of genetic algorithm (GA) by the algorithm of particle swarm optimization (PSO). This is initially transforming data from their raw format to a datamart ready to be interrogated by the statistical techniques that will be shown in the paper in order to specify the characteristics of the Sebou area. Iterative Principal Components Analysis (PCA) were then applied to resolve the problem of missing data. Then continue with the application of Support Vector Machine (SVM) polynomial classifier.
To be able to apply the (GA PSO) algorithm we need an objective function that serves as a criterion to determine the best solution to our problem, that’s why we opted for regression analysis(RA). The result achieved at the end of our study is represent by a classifier of water station according to a scale of 1 to 5 the most good quality to the worst. The novel water quality classifier is this helpful as supporting decision making for both the surface water and underground water.

Full Text: PDF


Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Even they continue the journal for indexing or not. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies. Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.