Search Results - (( data optimization based algorithm ) OR ( data detection system algorithm ))
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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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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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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Intrusion Detection Systems, Issues, Challenges, and Needs
Published 2021“…However, these algorithms suffer from many lacks especially when apply to detect new type of attacks, and need for new algorithms such as JAYA algorithm, teaching learning-based optimization algorithm (TLBO) algorithm is arise. …”
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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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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…This is attributable to the increasing number of audit data features and the decreasing performance of human-based smart Intrusion Detection Systems (IDS) regarding classification accuracy and training time. …”
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Rao-SVM machine learning algorithm for intrusion detection system
Published 2020“…Most of the intrusion detection systems are developed based on optimization algorithms as a result of the increase in audit data features; optimization algorithms are also considered for IDS due to the decline in the performance of the human-based methods in terms of their training time and classification accuracy. …”
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
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Failure detection analysis of grid-connected photovoltaic systems in tropical climate region / Nurmalessa Muhammad @ Atan
Published 2020“…A modified threshold-based technique was used to build the FD algorithm based on data from PV system installed at GERC UiTM, Malaysia. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data generated from network traffic are called concept drift. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…Irrelevant features in data collected from oil refineries affect system performance due to conflicts between normal data and detected faults. …”
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Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm
Published 2020“…For the second objective, the Analytic Hierarchy Process (AHP) was used to decide which stations can be used to monitor the railway system optimally. The Gradient-Based Cuckoo Search (GBCS) algorithm was used to achieve the final objective. …”
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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Feature selection based on particle swarm optimization algorithm for sentiment analysis classification
Published 2021“…An improved approach was proposed to increase the sentiment analysis accuracy based on text pre-processing and Naïve Bayes Classifier algorithm hybrid with Particle Swarm Optimization (NBC-PSO). …”
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An efficient IDS using hybrid Magnetic swarm optimization in WANETs
Published 2018“…In order to improve the effectiveness of intrusion detection systems (IDSs), data analysis methods such as data mining and classification methods are often integrated with IDSs. …”
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SVM for network anomaly detection using ACO feature subset
Published 2016“…Intrusion detection system detects the violation of confidentiality, integrity, and availability of the data. …”
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