Search Results - (( data detection ((a algorithm) OR (_ algorithm)) ) OR ( java simulation optimization algorithm ))
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1
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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2
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…Future work should be focusing on data collection of the E-Nose sensors and the improvement of the learning algorithm robustness towards environmental noise during data acquisition, such as evaporation and contamination of odor samples.…”
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3
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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4
Missing tags detection algorithm for radio frequency identification (RFID) data stream
Published 2019“…Thus in this research, an AC complement algorithm with hashing algorithm and Detect False Negative Read algorithm (DFR) is used to developed the Missing Tags Detection Algorithm (MTDA). …”
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5
A novel steganography algorithm using edge detection and MPC algorithm
Published 2019“…In this paper, we propose an efficient steganography algorithm which applies edge detection and MPC algorithm for data concealment in digital images. …”
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6
Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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7
Integrating genetic algorithms and fuzzy c-means for anomaly detection
Published 2005“…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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8
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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9
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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10
The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms
Published 2024“…This study proposes the procedure of detecting multiple outliers, particularly for univariate circular data based on agglomerative clustering algorithms. …”
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11
A hybrid digital watermarking algorithm
Published 2023“…A watermarking algorithm consists of the watermark structure, an embedding algorithm and an extraction, or detection, algorithm.…”
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A novel deadlock detection algorithm for neighbour replication on grid environment
Published 2012“…Therefore, an action must be taken to detect and solve this problem. A new framework and algorithm called Neighbour Replication on Grid Deadlock Detection (NRGDD) has been developed to handle deadlock cycles that exist during the transaction in Neighbour Replication on Grid (NRG) environment. …”
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13
Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system
Published 2022“…Recently, researchers suggested a deep belief network (DBN) algorithm to construct and build a network intrusion detection system (NIDS) for detecting attacks that have not been seen before. …”
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14
Improving the efficiency of clustering algorithm for duplicates detection
Published 2023“…In this paper, we propose a data pre-processing method that increases the efficiency of window algorithms in grouping similar records together. …”
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15
Fault detection with optimum March test algorithm
Published 2013“…The experiment result published in [1] shows BIST (Built-In-Self-Test) implementation with the new algorithm. It provides the same test length but with bigger area overhead, we therefore proposed a new 14N March Test Algorithm with fault coverage of more than 95% using solid 0s and 1s Data Background (DB). …”
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16
Experimental evaluation of data fusion algorithm for residual generation in detecting UAV servo actuator fault
Published 2023“…Algorithms; Data fusion; Hardware; Military vehicles; Redundancy; Software reliability; Unmanned aerial vehicles (UAV); Analytical redundancy; Data fusion algorithm; Experimental evaluation; Fault detection algorithm; Hostile environments; Model reference methods; On-board fault detection; Software and hardwares; Fault detection…”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…Thus, this study proposes the development of algorithms to detect and classify jamming attacks using a set of parameters on the physical layer and MAC in MANET. …”
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18
Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
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19
The fusion of edge detection and mathematical morphology algorithm for shape boundary recognition
Published 2016“…Edge detection algorithm is used to simplify image data by minimizing the amount of pixel to be processed, whereas the mathematical morphology is used for smoothing effects and localizing the object shape using mathematical theory sets.The discussion section focuses on the improved edge map and boundary morphology (EmaBm) algorithm as a new technique for shape boundary recognition.A comparative analysis of various edge detection algorithms is presented.It reveals that the LoG’s edge detection embedded in EmaBM algorithm performs better than the other edge detection algorithms for fruit shape boundary recognition. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…The generation of rule is considered a crucial process in data mining and the generated rules are in a huge number. …”
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