Search Results - (( data detection means algorithm ) OR ( java application optimization algorithm ))
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…Clustering-based intrusion detection algorithm which trains on unlabeled data in order to detect new intrusions. …”
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4
Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
5
Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025Subjects:Article -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Article -
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Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]
Published 2023“…The purpose of this study is to apply the K-Means algorithm to perform clustering on COVID-19 data to determine the high spread of the virus in regions in Indonesia based on the frequency of the data. …”
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Book Section -
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Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. …”
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Article -
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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Thesis -
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Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
Published 2024“…The test results show promising results with obtained mean RMSE =1407.2303, mean MAPE =0.7135, and mean detection time =2.6129s for a data range of between 3955 to 9057.…”
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12
Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
Published 2024“…The test results show promising results with obtained mean RMSE =1407.2303, mean MAPE =0.7135, and mean detection time =2.6129s for a data range of between 3955 to 9057.…”
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Proceeding Paper -
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…The detectors: zero forcing block linear equalizer and minimum mean square error block linear equalizer algorithms are considered in this paper to recover the data. …”
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Article -
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works
Published 2023“…Barium compounds; Cybersecurity; Data mining; Decision trees; Evolutionary algorithms; K-means clustering; Learning algorithms; Malware; Network security; Sodium compounds; Support vector machines; 'current; Comparatives studies; Cyber security; K-means; Machine learning algorithms; Malware attacks; Malware detection; Metaheuristic; Recent researches; Systematic literature review; Nearest neighbor search…”
Conference Paper -
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Anomaly-based intrusion detection through K-means clustering and naives Bayes classification
Published 2013“…Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification
Published 2013“…Regrettably, the foremost challenge of this method is to minimize false alarm while maximizing detection and accuracy rate.We propose an integrated machine learning algorithm across K-Mean s clustering and Naïve Bayes Classifier called KMC+NBC to overcome the aforesaid drawbacks.K-Means clustering is applied to labeling and gathers the entire data into corresponding cluster sets based on the data behavior,i.e.…”
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K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm
Published 2025“…In the first phase, the best set of features is identified by the Genetic algorithm and is utilised by the K-means clustering algorithm to divide the dataset into groups with similar traits. …”
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Article -
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The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. …”
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Article -
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Combined generative adversarial network and fuzzy C-means clustering for multi-class voice disorder detection with an imbalanced dataset
Published 2020“…A generative adversarial network offers synthetic data to reduce bias in the detection model. Improved fuzzy c-means clustering considers the relationship between adjacent data points in the fuzzy membership function. …”
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