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💡[Feature]: Addition Of Groundwater Quality Predictor #1645

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Closed
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Stuti333 opened this issue Nov 8, 2024 · 2 comments
Closed
4 tasks done

💡[Feature]: Addition Of Groundwater Quality Predictor #1645

Stuti333 opened this issue Nov 8, 2024 · 2 comments
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enhancement New feature or request

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@Stuti333
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Stuti333 commented Nov 8, 2024

Is there an existing issue for this?

  • I have searched the existing issues

Feature Description

Groundwater contamination with arsenic is a serious problem in many parts of the world, and can have severe health consequences for those who consume it. In this project, we aim to predict the arsenic content in groundwater using artificial neural networks (ANN), specifically backpropagation neural network (BPNN), and Whale Optimization Algorithm (WOA).The project involves collecting data on arsenic levels in groundwater from various locations, along with information on environmental factors that may affect the arsenic content. The data is then preprocessed to clean and transform it, and split into training and testing datasets.We use BPNN and WOA to build prediction models based on the training dataset. BPNN is a commonly used neural network model for regression and classification tasks, while WOA is a nature-inspired optimization algorithm that can be used to optimize the weights and biases of the neural network.The performance of the BPNN and WOA models is then evaluated using the testing dataset, and compared against each other to determine which method yields better results. We also evaluate the impact of different input variables on the prediction accuracy of the models.The results of this project can have important implications for water management and public health, as accurate prediction of arsenic levels in groundwater can help prevent exposure to this toxic element. Furthermore, the use of advanced machine learning techniques like ANN and WOA can provide insights into the complex relationships between arsenic content and environmental factors, and may lead to the development of more effective strategies for managing groundwater resources.

Use Case

Predicting Arsenic Levels for Water Safety Monitoring
Environmental Impact Assessments
Water Treatment and Management
Public Health and Risk Mitigation
Agriculture decision support

Benefits

Predicting Arsenic Levels for Water Safety Monitoring
Environmental Impact Assessments
Water Treatment and Management
Public Health and Risk Mitigation
Agriculture decision support

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Loss and accuracy
RMSE Graph

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High

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@Stuti333 Stuti333 added the enhancement New feature or request label Nov 8, 2024
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github-actions bot commented Nov 8, 2024

Thank you for creating this issue! 🎉 We'll look into it as soon as possible. In the meantime, please make sure to provide all the necessary details and context. If you have any questions reach out to LinkedIn. Your contributions are highly appreciated! 😊

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github-actions bot commented Nov 9, 2024

Hello @Stuti333! Your issue #1645 has been closed. Thank you for your contribution!

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