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161
Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022Subjects: -
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A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks
Published 2022“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”
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C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments
Published 2023“…The aim of streaming conformance checking is to find dis crepancies between process executions on streaming data and the refer ence process model. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Get full text
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Random Forest Bagging and X‐Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data
Published 2021“…In addition, for grouping similar antipatterns, a clustering process was performed to eradicate the design errors. …”
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170
Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis
Published 2021“…This work leverages the output of wearable technology to provide automatic stress and stressor identification model. In particular, this study proposes a novel algorithm that first detects instances of stress and then classifies the stressor type using photoplethysmography (PPG) data from wearable smartwatches. …”
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171
Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
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172
Diagnostic structure of visual robotic inundated systems with fuzzy clustering membership correlation
Published 2023“…Additionally, a clustering algorithm with a fuzzy membership function is implemented, allowing the robots to advance in accordance with predefined clusters and arrive at their starting place within a predetermined amount of time. …”
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173
Severity-Based Prioritized Processing of Packets with Application in VANETs
Published 2019“…Also, the proposed heuristic is tested against a non-prioritized processing algorithm that works using first come first served policy. …”
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Label dependency modeling in Multi-Label Naïve Bayes through input space expansion
Published 2024“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. We subject our enhanced iMLNB model to a rigorous empirical evaluation, utilizing six benchmark datasets. …”
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Defining quantitative rules for identifying influential researchers: Insights from mathematics domain
Published 2024“…Within each categorical grouping, we meticulously selected the five most pivotal parameters. This selection process was guided by an importance score, that was derived after assessing its influence on the model's performance in the classification of data pertaining to both awardees and non awardees. …”
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178
Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation
Published 2022“…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”
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Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review
Published 2021“…With the massive smart meter integration, DL takes advantage of the large-scale and multi-source data representations to achieve a spectacular performance and high PV forecastability potential compared to classical models. …”
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Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”