Search Results - candidate ((((control algorithm) OR (evolution algorithm))) OR (detection algorithm))

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  1. 1
    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE)

    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE) by Tijani, Ismaila Bayo, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2015
    “…Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance. …”
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  2. 2
    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…Thus, it can be concluded that QEEA algorithm is the most energy efficient and the best candidate for provisioning the QoS for the real time (RT) and non-real time (NRT) applications.…”
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  3. 3
    Last throughput and quality-of-service aware (LTQA) scheduling algorithm in long term evolution (LTE) femtocell network / Muhammad Naqiuddin Sahrani

    Last throughput and quality-of-service aware (LTQA) scheduling algorithm in long term evolution (LTE) femtocell network / Muhammad Naqiuddin Sahrani by Sahrani, Muhammad Naqiuddin

    Published 2022
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  4. 4
    Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network

    Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M.

    Published 2016
    “…Therefore, the purpose of peak detection algorithm is to distinguish an actual peak location from a list of peak candidates. …”
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  5. 5
    Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network

    Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network by Asrul, Adam, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai, Marizan, Mubin

    Published 2016
    “…Therefore, the purpose of peak detection algorithm is to distinguish an actual peak location from a list of peak candidates. …”
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  6. 6
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…The algorithms were examined on two real datasets, namely, NSL-KDD and Landsat. …”
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  7. 7
    Differential evolution for urban transit routing problem

    Differential evolution for urban transit routing problem by Buba, Ahmed Tarajo, Lai, Soon Lee

    Published 2016
    “…With this in mind, we propose a differential evolution (DE) algorithm for solving the UTRP with a specific objective of minimizing the average travel time of all served passengers. …”
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  8. 8
    3D face candidate region detection using background subtraction / Zulfikri Paidi and Nurzaid Muhd Zain

    3D face candidate region detection using background subtraction / Zulfikri Paidi and Nurzaid Muhd Zain by Paidi, Zulfikri, Muhd Zain, Nurzaid

    Published 2016
    “…Our focus is to solve the first challenge in face registration, which is to detect and identify face region. From the experiment, it shows some promising results related to using background subtraction in face candidate region detection algorithm. …”
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  9. 9
    Automated face localization and facial features detection using geometric information

    Automated face localization and facial features detection using geometric information by Chai, Tong Yuen, Mohd Rizon, Mohamed Juhari, Prof. Dr., Karthigayan, M., Sugisaka, M., Hazry, Desa, Dr., Ibrahim, Z.

    Published 2011
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  10. 10
    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes

    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

    Published 2015
    “…The DE algorithm generates new candidate solutions by first conducting the mutation operation which is then followed by the crossover operation. …”
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  11. 11
    Real-time detection of face and iris

    Real-time detection of face and iris by Chai, Tong Yuen, Mohamed Rizon, Mohamed Juhari, Prof. Dr., Muhammad Shazri

    Published 2011
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  12. 12
    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses

    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses by Tarajo, Buba Ahmed, Lee, Lai Soon

    Published 2019
    “…This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. …”
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  13. 13
    Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments

    Temporal video segmentation using squared form of Krawtchouk-Tchebichef moments by Abdulhussain, Sadiq H.

    Published 2018
    “…The fade transitions are detected based on the smoothed moments energy and the moments of gradients correlation for the candidate segments. …”
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  14. 14
    Skin detection using HSV color component subtraction and texture information / Rizal Mat Jusoh and Norhazimi Hamzah

    Skin detection using HSV color component subtraction and texture information / Rizal Mat Jusoh and Norhazimi Hamzah by Mat Jusoh, Rizal, Hamzah, Norhazimi

    Published 2010
    “…This thesis presents skin detection algorithm for detecting human skin regions in color images. …”
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  15. 15
    Automatic detection of face and facial features

    Automatic detection of face and facial features by Chai, Tong Yuen, Mohd Rizon, Mohamed Juhari, Prof. Dr., Woo, San San, Sugisaka, M.

    Published 2011
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  16. 16
    Improvement real-time detection of moving vehicle in a dynamic scene using shadow removal method / Khairul Azman Ahmad, Mohd Halim Mohd Noor,Mohamad Adha Mohamad Idin

    Improvement real-time detection of moving vehicle in a dynamic scene using shadow removal method / Khairul Azman Ahmad, Mohd Halim Mohd Noor,Mohamad Adha Mohamad Idin by Ahmad, Khairul Azman, Mohd Noor, Mohd Halim, Mohamad Idin, Mohamad Adha

    Published 2011
    “…Real-time processing is still feasible as these sophisticated algorithms are applied only a small number of candidates foreground pixels. …”
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  17. 17
    Improved Malware detection model with Apriori Association rule and particle swarm optimization

    Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2019
    “…These rule models are used together with extraction algorithm to classify and detect malicious android application. …”
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  18. 18
    Enhanced handover mechanism in long term evolution (LTE) networks

    Enhanced handover mechanism in long term evolution (LTE) networks by Hussein, Yaseein Soubhi, Mohd Ali, Borhanuddin, Varahram, Pooria, Sali, Aduwati

    Published 2011
    “…This paper investigates the improvement steps for HO mechanisms in long term evolution (LTE) system which is being formally submitted as a candidate 4G system. …”
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  19. 19
    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. Using a number of candidate detectors, the true positive rate of detecting malicious code is maximized, while the false positive rate of wrongful detection is minimized. …”
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  20. 20
    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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