Search Results - (( using optimization based algorithm ) OR ( basic detection using algorithm ))
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1
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…The approach was tested on the KDD Cup99 intrusion detection dataset and the results proved the proposed PSO-RKFLN as an accurate, reliable, and effective classification algorithm.…”
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A hybrid particle swarm optimization - extreme learning machine approach for intrusion detection system
Published 2018“…However, the internal power parameters (weight and basis) of ELM are initialized at random, causing the algorithm to be unstable. The Particle swarm optimization (PSO) is a well-known meta-heuristic which is used in this research to optimize the ELM. …”
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Facial emotion detection using Guided Particle Swarm Optimization (GPSO)
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4
Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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5
Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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6
Classification of herbs plant diseases via hierarchical dynamic artificial neural network
Published 2010“…Once the image of a target is captured digitally, a myriad of image processing algorithms can be used to extract features from it. …”
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Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework
Published 2011“…Once the image of a target is captured digitally, a myriad of image processing algorithms can be used to extract features from it. …”
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Development of high speed booth multiplier with optimized stuck-at fault implementation
Published 2002“…Deterministic technique will be used to detect failure circuit base on test pattern generation. …”
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Power System State Estimation In Large-Scale Networks
Published 2010“…Hence. SE requires to use various techniques to ensure validity of the results and to detect and identify sources of errors. …”
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11
Abnormal event detection in video surveillance / Lim Mei Kuan
Published 2014“…These low-level descriptions are then integrated using a basic set of rule-packages, to discriminate the different events. …”
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12
Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…Power system state estimation is the heart of data processing activities of modern electric utility energy control center. By using real time measurements and historical data base, power system state estimator detects errors in measurements and the data base; and calculates an optimal estimate of the system state vector of the bus voltage magnitudes and angles. …”
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WEBCAM MOTION DETECTION USINGVISUAL BASIC
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A Collision Detection Algorithm For Virtual Robot-Centered Flexible Manufacturing Cell
Published 2008“…The technique utilizes the narrow phase approach in detecting collision detection of non-convex object by testing collision between basic primitive and polygon. …”
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15
Boundary extraction and corner point detection for map of kariah Kg. Bukit Kapar / 'Afina AmirHussin
Published 2019“…Furthermore, two widely feature detection algorithms, which is Harris Corner Detector and FAST Corner Detector are used to compare in terms of the amount of corner point detection and run time of processing. …”
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16
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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17
The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model
Published 2017“…In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. …”
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Distance approximation using pivot point in narrow phase collision detection
Published 2013“…Thus, an algorithm for the optimal distance computation algorithm for continuous collision detection is shown in this paper. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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20
Shot boundary detection based on orthogonal polynomial
Published 2019“…The design of SBD algorithms developed from simple feature comparison to rigorous probabilistic and using of complex models. …”
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