Search Results - (( based optimization based algorithm ) OR ( based detection using algorithm ))
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1
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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2
Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…Optimization algorithms are widely used for the identification of intrusion. …”
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3
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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4
Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…Using a number of candidate detectors from an improved Apriori Algorithm with Particle Swarm Optimization, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. …”
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5
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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6
Overhead view based person counting using deep learning
Published 2022“…Third, the accurate tracking of each detected person is performed using the deep learning based tracking framework, known as DeepSORT. …”
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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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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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9
Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm
Published 2020“…The Gradient-Based Cuckoo Search (GBCS) algorithm was used to achieve the final objective. …”
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10
Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…These issues affect the system's performance and reduce diabetic disease detection accuracy. Hence, the research objective is to create an improved diabetic disease detection system using a Flock Optimization Algorithm-Based Deep Learning Model (FOADLM) feature modeling approach that leverages the PIMA Indian dataset to predict and classify diabetic disease cases. …”
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11
Neural network algorithm-based fall detection modelling
Published 2020“…This article presents results of modelling for fall detection system by using nonlinear autoregression neural network NARnet algorithm. …”
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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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A novel peak detection algorithm using particle swarm optimization for chew count estimation of a contactless chewing detection
Published 2022“…In accordance with the result, this article proposes a novel chew count estimation based on particle swarm optimization (PSO). First, the base of the algorithm is developed based on counting the peak of the chewing signal. …”
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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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15
A reinforcement learning-based energy-efficient spectrum-aware clustering algorithm for cognitive radio wireless sensor network
Published 2016“…In this thesis, a Reinforcement Learning (RL) based clustering algorithm is proposed to address energy and Primary Users (PUs) detection challenges in CR-WSN. …”
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16
An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization
Published 2019“…To adaptively switches between the two algorithms, an adaptive switching algorithm based on a Generalized Likelihood Ratio Test (GLRT) is proposed. …”
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17
Dingle's Model-based EEG Peak Detection using a Rule-based Classifier
Published 2015“…Rule-based classifier with an estimation technique based on particle swarm optimization (PSO) is employed in the classification stage. …”
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Mobile robot path planning using hybrid genetic algorithm and traversability vectors method
Published 2004“…Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. …”
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Removal of high density salt and pepper noise from image and video based on optimal decision based algorithm
Published 2014“…This paper proposes an optimal method to suppress the noise with high density properly based on a nonlinear filter and decision-based approach. …”
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20
Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm
Published 2022“…Software based solutions using traditional algorithms such as Histogram of Gradients (HOG) and Gaussian Mixed Model (GMM) are computationally slow and not suitable for real-time traffic detection. )erefore, the paper will review and evaluate different vehicle detection methods. …”
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