Search Results - (( parameter optimization based algorithm ) OR ( features detection system algorithm ))
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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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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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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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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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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…Optimization algorithms are successfully applied in the feature selection task in many systems. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification
Published 2022“…Then, the selected features are given as input to the DBN classifier which is trained using the Taylor-based bird swarm algorithm (Taylor-BSA). …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…Based on investigation different architecture and parameter, the suitable deep learning model has been presented to get optimize best result and testing time. …”
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Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application
Published 2021“…This study suggests the work to combine the optimization of feature selection and algorithm parameters to achieve higher accuracy and acquire more reliable comparison.…”
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Facial geometry and speech analysis for depression detection
Published 2017“…Optimal system performance was obtained using a nearest neighbour classifier on the decision fusion of geometrical features in the gender independent mode, and audio based features in the gender based mode; single visual and audio decisions were combined with the OR binary operation. © 2017 IEEE.…”
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Detection of corneal arcus using rubber sheet and machine learning methods
Published 2019“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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A novel islanding detection technique using modified Slantlet transform in multi-distributed generation
Published 2019“…Slantlet transform is utilized to derive the features in the required detection parameters measured from islanding and non-islanding events using identified Slantlet scales. …”
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High impedance fault detection and localization in 11kV distribution system / Mohd Syukri Ali
Published 2018“…In this process, the grey wolf optimization (GWO) technique is adopted in order to provide the optimal value of ANN parameters. …”
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Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data
Published 2018“…There was a need for efficient segmentation algorithm, optimization strategy, feature extraction and classification, and robust statistical and computational intelligence models to accomplish the set aims. …”
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Training feedforward neural networks for fault diagnosis of ball bearing
Published 2018“…The results show that the proposed approach produces comparable classification accuracy as parameters of the FNNs were optimized systematically using CFS algorithm.…”
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Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics
Published 2024“…In the map phase, the statisticalfeatures and the Principal Component Analysis (PCA) features are extracted. In the reduction phase, the optimal features are selected with theaid of the developed Hybrid Flower Pollination Bumblebees Optimization Algorithm (HFPBOA). …”
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LSR-YOLO: a lightweight and fast model for retail products detection
Published 2025“…The model introduces architectural optimizations, including the CSPHet-CBAM attention module, to strengthen feature representation, followed by a channel pruning algorithm tailored to the new architecture to reduce redundancy while maintaining accuracy. …”
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