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  1. 1
    Neural Networks based fault diagnosis of ac motors

    Neural Networks based fault diagnosis of ac motors by K.S., Rama Rao, Muhammad, Aariff Yahya

    Published 2008
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  2. 2
    Balancing exploration and exploitation in ACS algorithms for data clustering

    Balancing exploration and exploitation in ACS algorithms for data clustering by Jabbar, Ayad Mohammed, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2019
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  3. 3
    Adaptive parameter control strategy for ant-miner classification algorithm

    Adaptive parameter control strategy for ant-miner classification algorithm by Al-Behadili, Hayder Naser Khraibet, Sagban, Rafid, Ku-Mahamud, Ku Ruhana

    Published 2020
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  4. 4
    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement

    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement by Karami, Mahdi

    Published 2011
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  5. 5
    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network

    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

    Published 2020
    “…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
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  6. 6
    A New Near Optimal Harmonics Elimination PWM Algorithm For AC Traction Drives

    A New Near Optimal Harmonics Elimination PWM Algorithm For AC Traction Drives by Salam, Zainal, Chew, Tit Lynn

    Published 2002
    “…One well-known solution to ensure that the unwanted harmonics do not appear on the spectra is by using the harmonics elimination PWM (HEPWM) switching method. However, the application of HEPWM has been somewhat limited by the fact that the switching angles cannot be calculated online by a microprocessor-based waveform generator. …”
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  7. 7
    Fast algorithm for VQ-based wavelet coding system

    Fast algorithm for VQ-based wavelet coding system by Khalifa, Othman Omran

    Published 2003
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  8. 8
    Improvement DACS3 Searching Performance using Local Search

    Improvement DACS3 Searching Performance using Local Search by Md Rais, Helmi, Ali Othman, Zulaiha, Hamdan, Abdul Razak

    Published 2009
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  9. 9
    FPGA Based Optimized Discontinuous SVPWM Algorithm for Three Phase VSI in AC Drives

    FPGA Based Optimized Discontinuous SVPWM Algorithm for Three Phase VSI in AC Drives by Sutikno, Tole, Nik Idris, Nik Rumzi, Jidin , Auzani, JOPRI, MOHD HATTA

    Published 2013
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  10. 10
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
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  11. 11
    A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network

    A New Machine Learning-based Hybrid Intrusion Detection System and Intelligent Routing Algorithm for MPLS Network by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Abdullah F., Ahmad W.S.H.M.W.

    Published 2024
    “…The ML-based routing algorithm is compared to the conventional routing algorithm, Routing Information Protocol version 2 (RIPv2). …”
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  12. 12
    Ant colony optimization in dynamic environments

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…In order to achieve this objective, six ant algorithms namely Ant System (AS), Ant Colony System (ACS), Best-Worst Ant System (BWAS), Elitist Ant System (EAS), Max-Min Ant System (MMAS) and Rank-Based Ant System (RBAS) were implemented to solve a dynamic optimization problem in the form of the dynamic Traveling Salesman Problem (TSP). …”
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  13. 13
    Multi-label learning based on positive label correlations using predictive apriori

    Multi-label learning based on positive label correlations using predictive apriori by Al Azaidah, Raed Hasan Saleh

    Published 2019
    “…Along with that, two algorithms have been constructed by capturing the positive correlations where the first algorithm (MLR-PC) captures the positive global correlations and the second algorithm (MLCBA) proposes an adaption of AC algorithm to handle MLC based on the positive local correlations. …”
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  14. 14
    Detecting Duplicate Entry in Email Field using Alliance Rules-based Algorithm

    Detecting Duplicate Entry in Email Field using Alliance Rules-based Algorithm by Arif, Hanafi, Sulaiman, Harun, Enggari, Sofika, Rani, Larissa Navia

    Published 2016
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  15. 15
    Design issues and challenges of an FPGA-based orthogonal matching pursuit implementation for compressive sensing reconstruction

    Design issues and challenges of an FPGA-based orthogonal matching pursuit implementation for compressive sensing reconstruction by Mohd Nadzri,, Muhammad Muzakkir, Ahmad, Afandi, Tukiran, Zarina

    Published 2020
    “…To date, the implementation of practical applications of CS in hardware platforms, especially in real-time applications, still faces challenging issues due to the high computational complexity of its algorithms, hence leading to high power-consuming processes. …”
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  16. 16
    Energy efficiency mechanism using mobile-based fermat's spiral in wireless sensor networks

    Energy efficiency mechanism using mobile-based fermat's spiral in wireless sensor networks by Mantoro, Teddy, Shaukat Ali, Haroon, Ayu, Media Anugerah, Usino, Wendi

    Published 2011
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  17. 17
    Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy

    Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy by Ehteram, Mohammad, Banadkooki, Fatemeh Barzegari, Fai, Chow Ming, Moslemzadeh, Mohsen, Sapitang, Michelle, Ahmed, Ali Najah, Irwan, Dani, El-Shafie, Ahmed

    Published 2021
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  18. 18
    Application of memetic algorithm in modelling discrete-time multivariable dynamics systems

    Application of memetic algorithm in modelling discrete-time multivariable dynamics systems by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2008
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  19. 19
    Modified ACS centroid memory for data clustering

    Modified ACS centroid memory for data clustering by Jabbar, Ayad Mohammed, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2019
    “…Centroids will be identified based on the adaptive instance route. A comparison of the performance of several common clustering algorithms using real-world data sets shows that the accuracy of the proposed algorithm surpasses those of its counterparts.…”
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  20. 20
    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks

    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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