Modeling Pollution Index Using Artificial Neural Network and Multiple Linear Regression Coupled with Genetic Algorithm

Abbas, Abdulhussain A.; Dawood, Ammar Salman

doi:10.12911/22998993/146177

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…The parameters that were used for models in this study were given using machine learning, which is one of the approaches that are utilized in artificial intelligence (Tables 1 and 2). In order to accurately predict the weir features and prove their efficacy, machine learning methods are now being used [51][52][53][54][55]. For this model, we used 90 run experiments.…”

Section: Modellingmentioning

confidence: 99%

Hydraulic Behavior of Weir-Gate Structure with Rectangular Side Obstacle under Free and Submerged Flow Conditions

Qasim,

Dawood

2023

I2M

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This research examines the behavior of a weir-gate hydraulic structure when subjected to the presence or absence of a side obstacle. The study focuses on two scenarios, free flow and submerged flow, and employs a side obstacle with dimensions of 15 cm in height, 30 cm in length, and 1 cm in thickness, located 30 cm downstream from the weir-gate structure. A correlation matrix is derived using measured and calculated data to establish the relationship between various variables, both dimensional and non-dimensional. The results show a clear correlation between Froude number and discharge coefficient, while a random trend is observed between discharge coefficient and Reynolds number. A proper trend is found between Reynolds number and Froude number at the downstream location. The discharge coefficient is significantly influenced by factors such as gate water depth, weir water head, and vertical distance between the weir and gate. Additionally, the study investigates the effect of average water depth at the downstream on discharge and flow velocity. Two models, linear regression and artificial neural network, are developed and tested to estimate the coefficient of discharge (Cd). The ANN model proves to be the best-fit model for all scenarios, with an MSE of 0.00013141 and an R-squared value of 0.99. The machine learning algorithms used in this study demonstrate an increase in prediction accuracy for Cd.

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Section: Modellingmentioning

confidence: 99%

Hydraulic Behavior of Weir-Gate Structure with Rectangular Side Obstacle under Free and Submerged Flow Conditions

Qasim,

Dawood

2023

I2M

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“…The WQI is advantageous in its capacity to enable researchers to evaluate water quality in specific locations and compare it between different locations [19]. The CPI uses a statistical formula to assess the level of pollution in bodies of water [20] and has been used for the same purpose as the WQI in several studies [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Influence of Reverse Osmosis on Lakes Using Water Quality Indices: A Case Study in Saudi Arabia

Aljassim,

AlMulla,

Berekaa

et al. 2024

Water

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A drastic level of resource degradation was revealed through a preliminary evaluation (completed in 2016) of water quality in a recreational lake in the second industrial city in Dammam, Saudi Arabia. The primary signs were a foul smell, algal bloom, high turbidity, and lack of aquatic life. This study aims to evaluate the influence of reverse osmosis (RO) on lake water quality. The recreational lake consists of two connected lakes (Lakes 1 and 2), which receive treated effluent from an industrial wastewater treatment plant. Composite samples were collected from the lakes to analyze their physiochemical parameters. Descriptive analyses were performed, and two water quality indices were developed to observe the variations in water quality conditions between the two periods (2016 and 2021). The results indicated that the water parameters of total dissolved solids (TDS), sulphate (SO42−), biological oxygen demand (BOD), and dissolved oxygen (DO) in 2016 (3356, 4100, 516, and 1.32 mg/L, respectively) were significantly improved in 2021 (2502, 1.28, 9.39, and 7.79 mg/L, respectively). The results of the water quality index (WQI) and comprehensive pollution index (CPI) indicated that the water quality in Lake 1 was significantly enhanced in 2021 (WQI = 85, CPI = 1) in comparison with assessment data from 2016 (WQI = 962, CPI = 8). However, the data from Lake 2 revealed higher pollution levels in 2021 (WQI = 1722, CPI = 18) than those recorded in 2016 (WQI = 1508, CPI = 13). As indicated by the absence of bad smells, algal blooms, and restoration of aquatic life, the RO intervention successfully improved the water quality in Lake 1. The WQI and CPI were helpful tools for evaluating lake water quality.

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Integration of an artificial neural network and a simulated annealing algorithm for the optimization of the river water pollution index

Dawood

Abbas

2022

Regional Studies in Marine Science

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Modeling Pollution Index Using Artificial Neural Network and Multiple Linear Regression Coupled with Genetic Algorithm

Cited by 5 publications

References 9 publications

Hydraulic Behavior of Weir-Gate Structure with Rectangular Side Obstacle under Free and Submerged Flow Conditions

Hydraulic Behavior of Weir-Gate Structure with Rectangular Side Obstacle under Free and Submerged Flow Conditions

Evaluating the Influence of Reverse Osmosis on Lakes Using Water Quality Indices: A Case Study in Saudi Arabia

Integration of an artificial neural network and a simulated annealing algorithm for the optimization of the river water pollution index

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