Search Results - (( pattern machine algorithm ) OR ( between ((work algorithm) OR (swarm algorithm)) ))

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    Verification correctness properties for aggregation behavior of swarm robotics system using SPIN model checker / Siti Shafinaz Ali by Ali, Siti Shafinaz

    Published 2015
    “…This research work focused on a developed swarm algorithm aimed at swarm aggregation. …”
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    Thesis
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    Normative Fish Swarm Algorithm For Global Optimization With Applications by Tan, Weng Hooi

    Published 2019
    “…Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. …”
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    A Navigation Strategy for Swarm Robotics Based on Bat Algorithm Optimization Technique by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Bayuaji, Luhur, Muhammad, Syafrullah, Zulkifli, Musa

    Published 2018
    “…This paper aims to adapt Bat Algorithm (BA) optimization techniques to the swarm robotics system. …”
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    On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm by Faisal, Ali Raed, Hashim, Fazirulhisyam, Ismail, Mahamod, Noordin, Nor Kamariah

    Published 2015
    “…However, achieving equivalent backhaul reduction based on limited feedback channel state information is challenging when linear techniques, such as zero-forcing beamforming (BF) are used, which led to the use of stochastic algorithms instead. Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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    Conference or Workshop Item
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    Hybrid firely and particle swarm optimisation algorithm for optimal dimming level and energy saving in lecturer’s room by Nik Ahmad, Nik Sahidah

    Published 2022
    “…In order to identify the optimal dimming level, energy consumption, simulation time and luminaire performance, this research work presents the comparison between light-emitting diode (LED) and fluorescent luminaires using the HFPSO algorithm and using the particle swarm optimisation (PSO) algorithm and the firefly algorithm (FA). …”
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    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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    Machining surface roughness monitoring using acoustic emission method by Mohd Syazlan, Mohd Hatta

    Published 2010
    “…The objective of this project is to collect the data acquisition of the experiment by operating milling process, to study the correlation of AE parameter with work piece surface quality by comparing the AE signals with average roughness, Ra of the work piece’s surface measured by using Perthometer, and to develop algorithm for online machining condition monitoring. …”
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    Undergraduates Project Papers
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    A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis by Draman @ Muda, Azah Kamilah, Choo, Yun Huoy, Draman @ Muda, Noor Azilah

    Published 2014
    “…Many researches have been done to develop algorithms for extracting good features that can reflect the authorship with good performance. …”
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    Book Chapter
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    A new swarm-based framework for handwritten authorship identification in forensic document analysis by Pratama, Satrya Fajri, Draman @ Muda, Azah Kamilah, Choo, Yun Huoy, Draman @ Muda, Noor Azilah

    Published 2014
    “…Many researches have been done to develop algorithms for extracting good features that can reflect the authorship with good performance. …”
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    Book Chapter
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    An efficient IDS using hybrid Magnetic swarm optimization in WANETs by Sadiq, Ali Safa, Alkazemi, Basem Y., Mirjalili, Seyedali, Noraziah, Ahmad, Khan, Suleman, Ihsan, Ali, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

    Published 2018
    “…Our developed algorithm works in extracting the most relevant features that can assist in accurately detecting the network attacks. …”
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    Article
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    Hybrid optimal control-swarm intelligence for optimization of selected cancer chemotherapy model / Omar Ali Mohammad Shindi by Omar Ali , Mohammad Shindi

    Published 2018
    “…This research project proposes two hybrid techniques that’s combined between the optimal control theory (OCT) with the swarm intelligence (SI) and evolutionary algorithms (EA), and check the performance of this techniques, with the popular method that used purely SI and EA algorithms, such M-MOPSO, MOPOS, MOEAD, MODE. …”
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    Thesis
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    Particle swarm optimization technique of current tracking controller for electric power-assisted steering system by Bahmanshiri, Adel Amiri

    Published 2015
    “…In this case, three test procedure are done to show the performance of current tracking controller in different situations, also the current tracking performance with Particle Swarm Optimization (PSO)-PID controller compared to previous research that used Ant Colony Optimization (ACO)-PID controller [1] to show the percentage of error between reference motor current and actual motor current of proposed PSO optimization algorithm with 0.023% is much less than previous worked (ACO optimization algorithm) with 4.76%.So the proposed control strategy can improve otor current tracking performance in electric powers assisted steering (EPAS) systems.…”
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    Thesis
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    Predicting the success of suicide terrorist attacks using different machine learning algorithms by Hossain, Md Junayed, Abdullah, Sheikh Md, Barkatullah, Mohammad, Miahh, Md Saef Ulla, Sarwar, Talha, Monir, Md Fahad

    Published 2022
    “…With an accuracy rate of 98.4% and an AUC-ROC score of 99.9%, the Random Forest classifier was the most accurate among all other algorithms. This model is more trustworthy than previous work and provides a useful comparison between machine learning methods and an artificial neural network because it is less dependent and has a multiclass target feature.…”
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    Conference or Workshop Item