Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Modelling Microcystis Cell Density in a Mediterranean Shallow Lake of Northeast Algeria (Oubeira Lake), Using Evolutionary and Classic Programming

Arif Salah, Djellal Adel, Djebbari Nawel, Belhaoues Saber, Touati Hassen, Guellati Fatma Zohra, Bensouilah Mourad

Geomatics and Environmental Engineering

2023

Vol. 17, no. 2

31--68

Caused by excess levels of nutrients and increased temperatures, freshwater cyanobacterial blooms have become a serious global issue. However, with the development of artificial intelligence and extreme learning machine methods, the forecasting of cyanobacteria blooms has become more feasible. We explored the use of multiple techniques, including both statistical [Multiple Regression Model (MLR) and Support Vector Machine (SVM)] and evolutionary [Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Bird Swarm Algorithm (BSA)], to approximate models for the prediction of Microcystis density. The data set was collected from Oubeira Lake, a natural shallow Mediterranean lake in the northeast of Algeria. From the correlation analysis of ten water variables monitored, six potential factors including temperature, ammonium, nitrate, and ortho-phosphate were selected. The performance indices showed; MLR and PSO provided the best results. PSO gave the best fitness but all techniques performed well. BSA had better fitness but was very slow across generations. PSO was faster than the other techniques and at generation 20 it passed BSA. GA passed BSA a little further, at generation 50. The major contributions of our work not only focus on the modelling process itself, but also take into consideration the main factors affecting Microcystis blooms, by incorporating them in all applied models.

Cyanobacteria Dynamics in a Mediterranean Reservoir of the North East of Algeria: Vertical and Seasonal Variability

Touati Hassen, Guellati Fatma Zohra, Arif Salah, Bensouilah Mourad

Journal of Ecological Engineering

2019

Vol. 20, nr 1

93--107

Harmful cyanobacterial efflorescence is of growing global concern and its prediction and management require a better understanding of the growth control factors and dominance of cyanobacteria. The Zit-Emba reservoir located in the North-East of Algeria, was constructed to provide drinking water, irrigation, and fishing. The vertical and seasonal distribution variation of cyanobacteria community associated with environmental factors was comprehensively investigated from April 2016 to December 2016 at five depths, based on a seasonal sampling. The cyanobacteria communities of this reservoir are composed of seven genera belonging to five orders. The average proportion of Microcystis to total cyanobacteria population was 43%, followed by Woronichinia 21%, Planktothrix 16%, Dolichospermum 13%, Oscillatoria 5%, and the remainder (Merismopedia, Spirulina) 2%. The average cyanobacterial abundance was 2702 cells/mL, ranging from 360 to 65 795 cells/mL and this abundance exceeds the alert level 1 throughout the year. The most recurrent periods of increase took place from spring to summer and autumn. However, the vertical distributions of cyanobacteria displayed a similar profile each season, and abundances tended to decrease with depth. The results of the statistical analysis suggested that the most abundant of cyanobacterial genera were positively related to chlorophyll-a and water temperature and negatively with the concentrations of NO3-N, NH4-N, and NO2-N. This demonstration of toxigenic cyanobacteria in this drinking water production dam involves regular monitoring of the cyanobacterial communities and cyanotoxins in raw water.