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developing based » developing a (Expand Search), developing 21st (Expand Search)
data detection » data injection (Expand Search)
rast algorithm » jaya algorithm (Expand Search), rd algorithm (Expand Search)
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…In addition, the framework outperforms conventional detection algorithms in words of detection rate, the rate of the false positive, and calculation time, respectively.…”
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Anomaly Detection Based Framework for Profile Monitoring
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doctoralThesis -
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Application of Red Deer Algorithm in Optimizing Complex functions
Published 2021“…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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An Uncertainty Based Genetic Algorithm Approach for Project Resource Scheduling
Published 2016“…Several nonlinear optimization models were developed for this purpose assuming uniform resource availability and sequence based project tasks. …”
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Online Fuzzy Logic Base Algorithm for Electricity Price Prediction
Published 2017“…The captured parameters are fed to a fuzzy-logic-based algorithm to calculate electric energy prices. …”
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Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System
Published 2023“…This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. …”
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HVAC system attack detection dataset
Published 2021“…It aims to promote and support the research in the field of cybersecurity of HVAC systems in smart buildings by facilitating the validation of attack detection and mitigation strategies, benchmarking the performance of different data-driven algorithms, and studying the impact of attacks on the HVAC system.…”
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The buffered work-pool approach for search-tree based optimization algorithms
Published 2017“…This new trend has been motivated by hardness of approximation results that appeared in the last decade, and has taken a great boost by the emergence of parameterized complexity theory. Exact algorithms often follow the classical search-tree based recursive backtracking strategy. …”
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Android Malware Detection Using Machine Learning
Published 2024“…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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Developing a UAE-Based Disputes Prediction Model using Machine Learning
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VEGAWES: variational segmentation on whole exome sequencing for copy number detection
Published 2015“…VEGAWES is an extension to a variational based segmentation algorithm, VEGA: Variational estimator for genomic aberrations, which has previously outperformed several algorithms on segmenting array comparative genomic hybridization data. …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches
Published 2024“…Exploratory Data Analysis (EDA) highlights the class imbalance problem in detecting fake jobs, which tends the model to act aggressively toward the minority class. …”
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Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
Published 2020“…The obtained results illustrate the efficacy of the proposed algorithm to analyze the time series data from the IoT devices for spam detection.…”
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An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems
Published 2019“…Also, it is possible that the attack is not directly detected. Hence, this highlights the need for an algorithm that is capable of assessing the widespread damage scale before starting the repair of the inconsistent medical database. …”
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Cutting‐edge technologies for detecting and controlling fish diseases: Current status, outlook, and challenges
Published 2024“…Here, we highlighted the potential of machine learning algorithms in early pathogen detection and the possibilities of intelligent aquaculture in controlling disease outbreaks at the farm level. …”