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201
Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques
Published 2025“…The generated IMF components are then fed into the Random Forest (RF) algorithm designed for shading detection and classification. …”
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202
Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma
Published 2019“…We extend the method to bidirectional LSTMs (BiLSTMs) and use it in the context of predicting future clinical outcomes using patients’ EHR historical visits.…”
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203
Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network
Published 2024“…Advanced machine learning algorithms are used in this study to figure out the complicated relationship between the crashworthiness parameters of the hexagonal composite ring specimens under lateral compressive, energy absorption, and failure modes. …”
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204
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205
Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…”
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206
A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security
Published 2023“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”
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207
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test
Published 2019“…Furthermore, personal information such as age, ethnicity and body-mass index was also a part of the data-set. Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. …”
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208
Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE
Published 2018“…The main purpose is to bridge the gap between EDM and International Assessments in the Arab world by applying EDM to predict Grade-4 student levels in TIMSS assessments in the UAE. We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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209
Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling
Published 2017“…Fluid-structure interaction (FSI) modeling is adapted in these models to account for counter-interacting forces of flowing blood and deforming leaflets for most accurate results. However, implementation of this approach is difficult using custom built codes and algorithms. …”
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210
Assessment of calcified aortic valve leaflet deformations and blood flow dynamics using fluid-structure interaction modeling
Published 2017“…Fluid-structure interaction (FSI) modeling is adapted in these models to account for counter-interacting forces of flowing blood and deforming leaflets for most accurate results. However, implementation of this approach is difficult using custom built codes and algorithms. …”
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211
Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
Published 2020“…A dataset publicly available for a smart home, along with weather conditions, is used for the methodology validation. The proposed algorithm is used to detect the spamicity score of the connected IoT devices in the network. …”
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212
Blue collar laborers’ travel pattern recognition: Machine learning classifier approach
Published 2021“…A bagged Clustering algorithm was employed to identify the number of clusters, then the C-Means algorithm and the Pamk algorithm were implemented to validate the results. …”
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213
MAESTRO: Orchestrating Computational Offloading to Multiple FemtoClouds in Various Communication Environments
Published 2022“…<p dir="ltr">Many novel IoT-based applications demand low latency, large compute resources, and high privacy. …”
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214
Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan
Published 2017“…Different classification algorithms were applied to the dataset using the Rapidminer tool. …”
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215
QU-GM: An IoT Based Glucose Monitoring System From Photoplethysmography, Blood Pressure, and Demographic Data Using Machine Learning
Published 2024“…Bagged Ensemble Trees outperform other algorithms in estimating blood glucose level with a correlation coefficient of 0.90. …”
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216
Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices
Published 2024“…Based on the performance metrics, such as confusion matrix, training time, prediction time, accuracy, and Area Under the Receiver Operating Characteristic curve (AUC-ROC), it was established that SDN-ML-IoT, when applied to RF, outperforms other ML algorithms, as well as similar approaches related to our work. …”
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217
Tailoring motivational health messages for smoking cessation using an mHealth recommender system integrated with an electronic health record: a study protocol
Published 2018“…Patients’ feedback on the messages and their interactions with the app will be analyzed and evaluated following an observational prospective methodology to a) assess the perceived quality of the mobile-based health recommender system and the messages, using the precision and time-to-read metrics and an 18-item questionnaire delivered to all patients who complete the program, and b) measure patient engagement with the mobile-based health recommender system using aggregated data analytic metrics like session frequency and, to determine the individual-level engagement, the rate of read messages for each user. …”
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218
Smart non-intrusive appliance identification using a novel local power histogramming descriptor with an improved k-nearest neighbors classifier
Published 2021“…Specifically, short local histograms are drawn to represent individual appliance consumption signatures and robustly extract appliance-level data from the aggregated power signal. Furthermore, an improved k-nearest neighbors (IKNN) algorithm is presented to reduce the learning computation time and improve the classification performance. …”
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219
A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Published 2024“…The novelty of this work is, a recently developed DRF optimization methodology incorporated with the machine learning algorithm is utilized for maximizing the security level of IoT systems. …”
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220
State-of-Charge Estimation Using Triple Forgetting Factor Adaptive Extended Kalman Filter for Battery Energy Storage Systems in Electric Bus Applications
Published 2025“…The performance of the proposed TFF-AEKF is evaluated and compared to the conventional adaptive extended Kalman filter (AEKF) and the dual forgetting factor AEKF (DFF-AEKF), considering low and high measurement noise levels. It has been validated that the proposed algorithm can provide faster convergence and better accuracy when considering a high measurement noise level. …”