Removal of bacterial indicators in on-site two-stage multi-soil-layering plant under arid climate (Morocco): prediction of total coliform content using K-nearest neighbor algorithm

Zidan, Khadija; Sbahi, Sofyan; Hejjaj, Abdessamed; Ouazzani, Naaila; Assabbane, Ali; Mandi, Laila

doi:10.1007/s11356-022-21194-x

Cited by 8 publications

(5 citation statements)

References 74 publications

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“…The reduction of indicator bacteria can be due to various physico-chemical and/or biological processes, namely infi ltration by sedimentation; competition with native species, predation by bacteriophage species (zooplankton), production of natural inhibiting or bactericidal substances (e.g. antibiotics) by certain bacteria and micro-algae, leading to the death of or a reduction in the reproduction of indicator germs [Ndip et al, 2008;Zidan et al, 2022]. However, the lagoon treatment adopted exceeds the values destined for irrigation (1000 CFU/100 ml).…”

Section: Removal Of Fecal Contaminationmentioning

confidence: 99%

Study the Effectiveness of the Natural Lagoons for Removal of Organic Matter, Nutrients and Fecal Coliform from Urban Domestic Wastewater under Arid Climate (Morocco)

Osmane¹,

Zidane²,

Benaddi³

et al. 2023

J. Ecol. Eng.

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Morocco is one of the countries most affected by the scarcity of water resources and the poor distribution of rainfall. Natural lagoon is the most widely used treatment process in Morocco. Indeed, Morocco is a sunny country throughout the year. The lagoon system requires minimal effort in operation and maintenance. Moreover, this system is the best process for removing bacteria indicators. For these reasons, a study of the purification performance of natural lagoons during five years, located in Chichaoua region (Morocco) was carried out. The lagoon system was monitored for five years, with measurements taken every three months at the input and output of the system. It received a hydraulic loading rate (HLR) between 1171 and 2760 m 3 with an average of 2053 m 3 /day. The obtained results show the removal of 37% of TSS, 63% of BOD 5 , 60% of COD, 61% of NH 4 + , 37% of TP, and 6.5 log units of coliforms during the mentioned monitoring period. Thus, the effluent values do not always comply with the Moroccan water quality requirement for irrigation reuse. Additionally, the statistical analyses confirm the presence of a strong linear correlation between almost all variables in the lagoon output. Therefore, the performance efficiency of the lagoon in removing organic matter and nutrients was significantly (p < 0.05) dependent on the season. However, the fecal contamination was not significantly (p > 0.05) affected by the seasons in this study. At the end of this study a complementary treatment before the reuse of treated wastewater, was proposed.

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Section: Removal Of Fecal Contaminationmentioning

confidence: 99%

Study the Effectiveness of the Natural Lagoons for Removal of Organic Matter, Nutrients and Fecal Coliform from Urban Domestic Wastewater under Arid Climate (Morocco)

Osmane¹,

Zidane²,

Benaddi³

et al. 2023

J. Ecol. Eng.

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“…Ravi et al [65] applied the model to understand and examine the underlying factors that could cause septic failures. Zidan et al [31] used the KNN model in the prediction of total coliform removal from urban wastewater by an on-site, two-stage multi-soil-layering plant. The KNN algorithm was used by Hmoud and Waselallah [66] to predict the water quality as well as the effluent total nitrogen from a large-scale wastewater treatment facility [56].…”

Section: K-nearest Neighbors (Knn)mentioning

confidence: 99%

“…Konstantina et al [30] showed the feasibility of using machine learning for optimal irrigation purposes. Machine learning can also be used to discover the performance of wastewater treatment processes, such as biological nutrient removal, with a high degree of accuracy [31,32]. These models can be used in the modification of processing processes by identifying optimal conditions for maximum performance while minimizing the use of resources.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence and Wastewater Treatment: A Global Scientific Perspective through Text Mining

El Alaoui El Fels,

Mandi,

Kammoun

et al. 2023

Water

Self Cite

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The concept of using wastewater as a substitute for limited water resources and environmental protection has enabled this sector to make major technological advancements and, as a result, has given us an abundance of physical data, including chemical, biological, and microbiological information. It is easier to comprehend wastewater treatment systems after studying this data. In order to achieve this, a number of studies use machine learning (ML) algorithms as a proactive approach to solving issues and modeling the functionalities of these processing systems while utilizing the experimental data gathered. The goal of this article is to use textual analysis techniques to extract the most popular machine learning models from scientific documents in the “Web of Science” database and analyze their relevance and historical development. This will help provide a general overview and global scientific follow-up of publications dealing with the application of artificial intelligence (AI) to overcome the challenges faced in wastewater treatment technologies. The findings suggest that developed countries are the major publishers of articles on this research topic, and an analysis of the publication trend reveals an exponential rise in numbers, reflecting the scientific community’s interest in the subject. As well, the results indicate that supervised learning is popular among researchers, with the Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM), Linear Regression (LR), Adaptive Neuro-Fuzzy Inference System (ANFIS), Decision Tree (DT), and Gradient Boosting (GB) being the machine learning models most frequently employed in the wastewater treatment domain. Research on optimization methods reveals that the most well-known method for calibrating models is genetic algorithms (GA). Finally, machine learning benefits wastewater treatment by enhancing data analysis accuracy and efficiency. Yet challenges arise as model training demands ample, high-quality data. Moreover, the limited interpretability of machine learning models complicates comprehension of the underlying mechanisms and decisions in wastewater treatment.

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“…To generate recommendations based on the classification technique (Panigrahi et al, 2021), the user is classified into a group that has users with similar behavior. The K-nearest neighbors (KNN) algorithm is considered the most useful technique in this domain (Zidan et al, 2022).…”

Section: Classificationmentioning

confidence: 99%

Web Mining Techniques - A Framework to Enhance Customer Retention

Ouf

Helmy

Ashraf

2023

International Journal of E-Collaboration

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In e-commerce, retaining customers on the web is a difficult task that requires a good understanding of customers' behavior to be able to predict their needs and interests. Web usage mining (WUM), which is the application of data mining techniques to improve business, helps in understanding customers' behavior on the web. Therefore, this paper proposes and implements a framework to enhance the quality of customer recommendations. Providing customers with what they are looking for helps increase their satisfaction, which will lead to improved retention with the company. The proposed framework was tested and evaluated. The result of testing the proposed framework illustrates that the recommendations based on merged techniques (like clustering, classification, association, and sequential discovery) achieve strong accuracy with a precision value of 74%, coverage of 100%, and an average overall efficiency of F-measure of 86%. which means that the merged technique outperformed each technique and attained much higher overall coverage.

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Removal of bacterial indicators in on-site two-stage multi-soil-layering plant under arid climate (Morocco): prediction of total coliform content using K-nearest neighbor algorithm

Cited by 8 publications

References 74 publications

Study the Effectiveness of the Natural Lagoons for Removal of Organic Matter, Nutrients and Fecal Coliform from Urban Domestic Wastewater under Arid Climate (Morocco)

Study the Effectiveness of the Natural Lagoons for Removal of Organic Matter, Nutrients and Fecal Coliform from Urban Domestic Wastewater under Arid Climate (Morocco)

Artificial Intelligence and Wastewater Treatment: A Global Scientific Perspective through Text Mining

Web Mining Techniques - A Framework to Enhance Customer Retention

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