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  1. 1

    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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    Article
  2. 2

    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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  3. 3
  4. 4

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…Alan Fan et aI., [2] use Support Vector Machine (SVM) to stock market prediction. The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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    Article
  5. 5

    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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    Article
  6. 6

    Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

    Published 2014
    “…In this algorithm, the user has to tune an appropriate variable which directly affects the power consumption and the data gathering latency. …”
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    Thesis
  7. 7

    A multi-objective parametric algorithm for sensor-based navigation in uncharted terrains by Khaksar W., Sahari K.S.M.

    Published 2023
    “…Sensor-based motion planning is one the most challenging tasks in robotics where various approaches and algorithms have been proposed to achieve different planning goals. …”
    Article
  8. 8

    EZ-SEP: extended Z-SEP routing protocol with hierarchical clustering approach for wireless heterogeneous sensor network by Nurlan, Zhanserik, Zhukabayeva, Tamara, Othman, Mohamed

    Published 2021
    “…To improve and extend the life of WSNs, scientists around the world regularly develop various routing protocols that minimize and optimize the energy consumption of sensor network nodes. …”
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    Article
  9. 9

    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

    Published 2009
    “…Furthermore, variable switching times are known to cause problems in the implementation of any numerical algorithm due to the variable location of discontinuities in the dynamics. …”
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    Thesis
  10. 10

    Maximum Power Point Tracking (MPPT) Based Particle Swarm Optimization (PSO) for hydrokinetic energy harnessing by Wan Ismail, Ibrahim, Mohd Rusllim, Mohamed, Raja Mohd Taufika, Raja Ismail, Mohd Riduwan, Ghazali, Ping, C. L. X.

    Published 2024
    “…This paper presents a design and modeling of the Particle Swarm Optimization (PSO)-based maximum power point tracking (MPPT) algorithm specifically tailored for variable-speed fixed-pitch vertical axis hydrokinetic turbines. …”
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    Conference or Workshop Item
  11. 11

    An intelligent optical fibre Al(lll) sensor based on advanced materials-sol-gel & polyaniline-porous nanocomposite / Faiz Bukhari Mohd Suah, Abdul Mutalib Md Jani and Mohd Nasir Ta... by Mohd Suah, Faiz Bukhari, Md Jani, Abdul Mutalib, Taib, Mohd Nasir

    Published 2006
    “…An orthogonal design is utilized to design the experimental protocol, in which three variables are varied simultaneously. Feedforward-type neural networks with faster back propagation (BP) algorithm are applied to model the system, and then optimization of the experimental conditions is carried out in the neural network with 3:7:1 structure, which have been confirmed to be able to provide the maximum performance. …”
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    Research Reports
  12. 12

    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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    Book Section
  13. 13

    Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm by Khan, Talha Ahmed, Shaikh, Faraz Ahmed, Khan, Sheroz, Abdul Kadir, Kushsairy, Mohd Su'ud, Mazliham, Shahid, Zeeshan, Yahya, Muhammad

    Published 2019
    “…Real-time data of over forty eight (48) hours has been collected from PIR, Ultrasonic sensor, Temperature sensor, CO2 sensor, Rainfall module, Pressure, and temperature sensor. …”
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    Proceeding Paper
  14. 14

    Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor by Terence Jerome Daim

    Published 2023
    “…These include exploring recognition of gestures performed by two hands simultaneously, scalability to different environments, optimal sensor placement, and addressing user variability. …”
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    Thesis
  15. 15

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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    Thesis
  16. 16

    PID-PSO DC motor position controller design for ankle rehabilitation system by Azizi, Muhammad Azizul Raziq

    Published 2023
    “…The control algorithms also aim to be analyzed using an incremental rotary encoder sensor device as closed-loop feedback for dorsiflexion and plantarflexion movement. …”
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  17. 17

    Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

    Published 2019
    “…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. With large variability in SOM, the field presents a special situation and thus, the result could be specific to the study site. …”
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    Article
  18. 18

    Non-weighted aggregate evaluation function of multi-objective optimization for knock engine modeling by Witwit, Azher Razzaq Hadi

    Published 2017
    “…Power and fuel economy can be maximized by optimizing some factors that affect the knocking phenomenon, such as temperature, throttle position sensor, spark ignition timing, and revolution per minute. …”
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    Thesis
  19. 19

    Development of a motion planning and obstacle avoidance algorithm using adaptive neuro fuzzy inference system for mobile robot navigation by Muslim, Farah Kamil Abid

    Published 2017
    “…The present algorithm exhibits attractive features such as high optimality, high stability, low running cost and zero failure rates. …”
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    Thesis
  20. 20

    Acoustic emission partial discharge localization in oil based on artificial bee colony by Lim, Zhi Yang, Azis, Norhafiz, Mohd Hashim, Ahmad Hafiz, Mohd Radzi, Mohd Amran, Norsahperi, Nor Mohd Haziq, Mohd Ariffin, Azrul

    Published 2025
    “…Comparisons with the genetic algorithm (GA), particle swarm optimization (PSO) and bat algorithm (BA) revealed that the distance error, maximum deviation and computation time for AE PD localization based on ABC are the lowest. …”
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    Article