Search Results - (( evolution detection a algorithm ) OR ( using codification using algorithm ))
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1
A Detection Method for Text Steganalysis Using Evolution Algorithm (EA) Approach
Published 2012“…Therefore, this research employed a detection factor based on the evolution algorithm method for text steganalysis. …”
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2
An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. …”
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3
Fitness value based evolution algorithm approach for text steganalysis model
Published 2013“…In this paper, we present a new alternative method for text steganalysis based on an evolution algorithm, implemented using the Java Evolution Algorithms Package (JEAP).The main objective of this paper is to detect the existence of hidden messages ased on fitness values of a text description.It is found that the detection performance has been influenced by two groups of fitness values which are good fitness value and bad fitness value. …”
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4
Text steganalysis using evolution algorithm approach
Published 2012“…This study presents a new alternative of steganalysis method in order to detect hidden messages in text steganalysis called Evolution Detection Steganalysis System (EDSS) based on the evolution algorithm approach under Java Genetic Algorithms Package (JGAP). …”
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5
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. …”
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6
Robust multi-user detection based on hybrid grey wolf optimization
Published 2020“…The search for an effective nature-inspired optimization technique has certainly continued for decades. In this paper, a novel hybrid Grey wolf optimization and differential evolution algorithm robust multi-user detection algorithm is proposed to overcome the problem of high bit error rate (BER) in multi-user detection under impulse noise environment. …”
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7
Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…One of the challenging issues for a grid-connected distributed generation is to find a suitable technique to detect an islanding problem. …”
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8
Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm
Published 2019“…Furthermore, the right and left occipital channels may help in identifying happiness, sadness, surprise and neutral emotional states. The DEFS_Ch algorithm raised the linear discriminant analysis (LDA) classification accuracy from 80% to 86.85%, indicating that DEFS_Ch may offer a useful way for reliable enhancement of the detection of different emotional states of the brain regions.…”
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9
A review on object detection algorithms based deep learning methods / Wan Xing ... [et al.]
Published 2023“…Deep learning-based object detection algorithms can be categorized into three main types: end-to-end algorithms, two-stage algorithms, and one-stage algorithms. …”
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10
The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
Published 2001“…Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. …”
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11
A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works
Published 2023Conference Paper -
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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…The standard DE algorithm is known as a fixed length optimizer, while our problem demands the need for methods that aren’t tolerated to a fixed individual size, and that was made by altering the mutation and crossover strategies as well as the selection operation. …”
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14
Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization
Published 2013“…Three soft computing techniques namely Genetic Algorithm (GA), Differential Evolution (DE) and Particle Swarm Optimization (PSO) are utilized for the desired manipulation of curves and surfaces. …”
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15
Collaborative Location-Based Mobile Game with Error Detection Algorithm
Published 2018“…The game takes advantage of the weakness of Wi-Fi localization where environmental influence is significant and makes it part of the gameplay. A simple error detection algorithm is also introduced to maximize the game playability value by balancing game responsiveness and accuracy level.…”
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16
Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method
Published 2017“…Color is a significant source of information for human skin detection, and some studies have discussed the effect of color space on skin detection. …”
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17
Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level
Published 2024thesis::doctoral thesis -
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Evolution strategy for collaborative beamforming in wireless sensor networks
Published 2013“…An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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19
Machine learning and deep learning approaches for cybersecurity: a review
Published 2022“…This paper reviewed intrusion detection systems and discussed what types of learning algorithms machine learning and deep learning are using to protect data from malicious behavior. …”
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Segmentation of Retinal Vasculature using Active Contour Models (Snakes)
Published 2009“…The results shows that the algorithm outperforms many other published methods and achieved an accuracy (ability to detect both vessel and non-vessel pixels) range of 0.92-0.94, a sensitivity (ability to detect vessel pixels) range of 0.91-0.95 and a specificity (ability to detect non-vessel pixels) range of0.78-0.85. …”
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Final Year Project
