Journal of Nuclear Energy Science & Power Generation TechnologyISSN: 2325-9809

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Architectures and Uses of Artificial Neural Networks in Water Resources Engineering: Infrastructure and Applications

In today's world, drinking water control is a key concern. A few of the essential factors in the assessment of groundwater parameters are oxygen concentration (DO), biological oxygen demand (BOD), pH, Total Coliforms (TCO), and temperatures (Temp). In Siruvani River, Puducherry Territory, South India, our objective is really to predict those characteristics. A useful computer approach for simulating complicated connections between different data is indeed the convolutional neural network. The ANN network is trained using information from 2019 to 2021, and the water pollution forecast was performed for the year 2020. The results conform with the water quality index (WQI), which has been established in India for a long time. This ANN method is a realistic, easy-to-use technique for assessing the water quality of the river.

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