Mohsen Niazi; Ali Naghizadeh; Mansour Baziar
Abstract
AbstractBackground and purposeThe turbidity of treated water is measured as an important parameter in determining the quality of drinking or industrial water in all treatment plants. Due to the importance of the prevalence of pathogens such as Giardia and Cryptosporidium, which cause dangerous diseases ...
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AbstractBackground and purposeThe turbidity of treated water is measured as an important parameter in determining the quality of drinking or industrial water in all treatment plants. Due to the importance of the prevalence of pathogens such as Giardia and Cryptosporidium, which cause dangerous diseases such as dysentery, the relationship between reducing turbidity and increasing the elimination of these microorganisms has been proven in studies.Materials and methodsIn this study, an artificial neural network (ANN) model and multiple linear regression(MLR) were developed and their performance was compared to predict the turbidity of treated water of Tabas water treatment plant. Total dissolved solids, pH, temperature and input turbidity of raw water were used as input parameters of the models in the predictions. The best backpropagation algorithm and number of neurons were determined to optimize the model architecture.ResultsThe results showed that the Levenberg–Marquardt algorithm was selected as the best algorithm and the number of optimal neurons was determined to be 16.Also, the results of the sensitivity analysis of the neural network model showed that the input turbidity with a value of 29% is the most important parameter in the development of the ANN model.ConclusionThe results of correlation coefficient of MLR and ANN models were obtained for training data 0.63 and 0.8921 and for testing data 0.60 and 0.8571, respectively, which show the superiority of ANN model in Predicting the turbidity of the output of Tabas water treatment plant.
Ahmad Reza Yazdanbakhsh; Anoushiravan Mohseni bandpei; Abotaleb Bay; Mahdi Sadeghi
Abstract
Background and Aims: Swimming pools and Jacuzzis as sports and recreational centers are used by many people in different ages and classes. The aim of this study was to investigate the relationship between physicochemical characteristics and microbial contamination in Jacuzzi water and swimming pools ...
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Background and Aims: Swimming pools and Jacuzzis as sports and recreational centers are used by many people in different ages and classes. The aim of this study was to investigate the relationship between physicochemical characteristics and microbial contamination in Jacuzzi water and swimming pools in Golestan province. Materials and Methods: In the present cross-sectional study with descriptive-analytic approach, eight indoor swimming pool and Jacuzzi were chosen to be investigated in the Golestan province. Biological (Total coliform, E.coli, Streptococcus, Pseudomonas) and physiochemical parameters (temperature, pH, turbidity, free chlorine residual) were performed according to standard methods. Results: The obtained results showed a significant and positive correlation between turbidity and Pseudomonas in swimming pools (p=0.017). However, no significant relationship was observed between turbidity and other microorganisms. Also, it was revealed that there was a significant and positive correlation between total coliforms and fecal streptococci in the Jacuzzis . Beside an inverse relationship was found btween the free residual chlorine and indicator organisms. Conclusions:There is a high dispersion between microbial contamination and physicochemical variables in pools and Jacuzzis. In other wordو pools and Jacuzzis are very clean on some days and on some others, they are too polluted from the aspect of microorganisms’ presence and turbidity.. This indicates that there is no appropriate operation for pools and Jacuzzis in proportion of swimmer numbers and disinfection rate.