首页|Recent Findings in Machine Learning Described by a Researcher from Mehran University of Engineering and Technology (Machine learning, Water Quality Index, and GIS-based analysis of groundwater quality)
Recent Findings in Machine Learning Described by a Researcher from Mehran University of Engineering and Technology (Machine learning, Water Quality Index, and GIS-based analysis of groundwater quality)
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Iwa Publishing
Investigators publish new report on artificial intelligence. According to news originating from Mehran University of Engineering and Technology by NewsRx correspondents, research stated, “Water is essential for life, as it supports bodily functions, nourishes crops, and maintains ecosystems.” Our news reporters obtained a quote from the research from Mehran University of Engineering and Technology: “Drinking water is crucial for maintaining good health and can also contribute to economic development by reducing healthcare costs and improving productivity. In this study, we employed five different machine learning algorithms - logistic regression (LR), decision tree classifier (DTC), extreme gradient boosting (XGB), random forest (RF), and K-nearest neighbors (KNN) - to analyze the dataset, and their prediction performance were evaluated using four metrics: accuracy, precision, recall, and F1 score. Physiochemical parameters of 30 groundwater samples were analyzed to determine the Water Quality Index (WQI) of Pano Akil City, Pakistan. The samples were categorized into the following four classes based on their WQI values: excellent water, good water, poor water, and unfit for drinking. The WQI scores showed that only 43.33% of the samples were deemed acceptable for drinking, indicating that the majority (56.67%) were unsuitable. The findings suggest that the DTC and XGB algorithms outperform all other algorithms, achieving overall accuracies of 100% each.”
Mehran University of Engineering and TechnologyAlgorithmsCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
Iwa Publishing
