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  1. 1
    A Detection Method for Text Steganalysis Using Evolution Algorithm (EA) Approach

    A Detection Method for Text Steganalysis Using Evolution Algorithm (EA) Approach by Puriwat, Lertkrai

    Published 2012
    “…Therefore, this research employed a detection factor based on the evolution algorithm method for text steganalysis. …”
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  2. 2
    Fitness value based evolution algorithm approach for text steganalysis model

    Fitness value based evolution algorithm approach for text steganalysis model by Din, Roshidi, Samsudin, Azman, Tuan Muda, Tuan Zalizam, Lertkrai, P., Amphawan, Angela, Omar, Mohd Nizam

    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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  3. 3
    Text steganalysis using evolution algorithm approach

    Text steganalysis using evolution algorithm approach by Din, Roshidi, Tuan Muda, Tuan Zalizam, Lertkrai, Puriwat, Omar, Mohd Nizam, Amphawan, Angela, Aziz, Fakhrul Anuar

    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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  4. 4
    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Non detection zone decreases to around zero and the proposed method has the ability to detect islanding up to 0.1% power mismatch. …”
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  5. 5
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    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. 6
    Development Of Semi-Automatic Liver Segmentation Method For Three-Dimensional Computed Tomography Dataset

    Development Of Semi-Automatic Liver Segmentation Method For Three-Dimensional Computed Tomography Dataset by Chiang, Yi Fan

    Published 2017
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  7. 7
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
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  8. 8
    Differential evolution algorithm for linear frequency modulation radar signal denoising

    Differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan, Raja Abdullah, Raja Syamsul Azmir, Al-Dabbagh, Rawaa Dawoud Hassan, Hashim, Fazirulhisyam

    Published 2013
    “…These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. …”
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  9. 9
    A review on object detection algorithms based deep learning methods / Wan Xing ... [et al.]

    A review on object detection algorithms based deep learning methods / Wan Xing ... [et al.] by Wan Xing, Sultan Mohd, Mohd Rizman, Johari, Juliana, Ahmat Ruslan, Fazlina

    Published 2023
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  10. 10
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
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  11. 11
    Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method

    Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

    Published 2017
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  12. 12
    Framework for stream clustering of trajectories based on temporal micro clustering technique

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
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  13. 13
    Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization

    Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization by Yahya, Zainor Ridzuan

    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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  14. 14
    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu

    Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

    Published 2005
    “…For overall, the back-propagation algorithm has been proved as a method that can be used for recognition areas.…”
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  15. 15
    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising

    Optimized differential evolution algorithm for linear frequency modulation radar signal denoising by Al-Dabbagh, Mohanad Dawood Hasan

    Published 2013
    “…An improvement to the conventional DE algorithm has been made to change it from its classical form to be possibly applied for ambiguous targets range detection for radar system. …”
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  16. 16
    Fast recovery of unknown coefficients in DCT-transformed images

    Fast recovery of unknown coefficients in DCT-transformed images by Ong, Sim Ying, Li, Shujun, Wong, Kok Sheik, Tan, Kuan Yew

    Published 2017
    “…While the time complexity is polynomial, it is still too high for large images so faster methods are still desired. In this paper, we propose a fast hierarchical DCT coefficients recovery method by combining image segmentation and linear programming. …”
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  17. 17
    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

    Published 2017
    “…The first proposed method is applied to detect crack damage in a structure. …”
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  18. 18
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
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  19. 19
    ECONOMICAL OPTIMIZATION OF CONDUCTOR SELECTION IN PLANNING RADIAL DISTRIBUTION NETWORKS

    ECONOMICAL OPTIMIZATION OF CONDUCTOR SELECTION IN PLANNING RADIAL DISTRIBUTION NETWORKS by Ab Ghani, Mohd Ruddin

    Published 1999
    “…A new computer algorithm and program is presented for selection of optimal conductor type and size for each feeder segment. …”
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  20. 20
    Economical optimization of conductor selection in planning radial distribution networks

    Economical optimization of conductor selection in planning radial distribution networks by Islam, S.J., Ghani, M.R.A.

    Published 1999
    “…A new computer algorithm and program is presented for selection of optimal conductor type and size for each feeder segment. …”
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