Millimeter waves (mmWaves) provide new opportunities for wireless communications and sensing due to the ample bandwidth, narrow beams, high aperture gains and spatial resolution, and high information capacity. MmWaves...
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Classification of fruits into different classes based on their species, cultivars, shape and other aspects has been performed for a very long time. However, these processes had been largely manual in nature and were i...
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In this paper, we explored the application of both the Random Forest and K-Nearest Neighbors (KNN) algorithms for fraud detection. Fraudulent activities pose significant threats to various industries, making their det...
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Vendor selection in supply chain management is a complex but extremely important process that requires the evaluation of multiple factors such as cost, quality, delivery time, and responsiveness. This study presents a...
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The detection of unpredicted events or rare patterns in traffic data plays an important role in intelligence traffic management, that offers alerts of incidents. To address the problem of less accuracy in industrial n...
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The district of San Juan de Lurigancho (SJL) in Lima—Peru, is one of the districts crowed in the capital and has one of the highest amounts solid domestic wastes. To fix this problem, a model was developed to map the...
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As oil reserves decline, fossil fuel transportation's political, economic, and environmental issues worsen. EVs, a new green technology, might reduce oil use, increase sustainable road transport, and reduce greenh...
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Maternal health is among the greatest challenges in the world, especially in rural areas as there lack medical practitioners, they do not have easily accessible publics clinics and transport is difficult. Therefore, h...
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ISBN:
(纸本)9783031770777
Maternal health is among the greatest challenges in the world, especially in rural areas as there lack medical practitioners, they do not have easily accessible publics clinics and transport is difficult. Therefore, high rates of maternal as well as infant morbidity and mortalities are recorded. This research utilizes Artificial Intelligence (AI) with machine learning algorithms to forecast and address maternal health hazards right at their onset stage. The current research utilizes the concept of AI along with many Machine Learning (ML) methods like the Ensemble Learning Model (ELM), Random Forest (RF), K-Nearest Neighbour (KNN), Decision-Tree (DT), XG-Boost (XGB), Cat Boost (CB), and Gradient Boosting (GB), along with Synthetic Minority Over-sampling Technique (SMOTE) algorithm used for dealing with the problem class imbalance within the data set. SMOTE algorithm is utilized for the dataset balancing process. The handling system involves refining data preprocessing with the help of feature engineering and robust data cleaning which makes sure that anomalies do not erode the reliability of the predictive model. The existing methods [1] used RF (90%), DT (87%), XGB (85%), CB (86%), and GB (81%) algorithms and were compared with the accuracies of the proposed models like Logistic Regression (LR), Ensemble Learning Bagging (ELB), Ensemble Learning Stacking (ELS), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The existing methods used only imbalance dataset. The accuracies of the proposed models with using SMOTE algorithm (balanced dataset) are LR (61.33%), KNN (81%), ELB (92.33%), ELS (90.66%) CNN (40.67%), RNN (59.67%), LSTM (54%), GRU (56%) respectively. Among these methods, ELB achieved 92.33% of accuracy with using SMOTE algorithm using imbalanced dataset. Whereas the accuracies of the proposed models without using SMOTE algorithm (imbalanced dataset) are LR (66.09%), KNN (68.47%)
This study develops and evaluates a predictive model for estimating glomerular filtration rate using advanced machine learning algorithms. We trained and tested seven models, including K-nearest neighbors, support vec...
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Recommender systems based on collaborative filtering are vulnerable to shilling assaults owing to its openness. Shiller’s introduce fictitious profiles into the database of the system with the goal of modifying the r...
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