Search Results - intelligence valid ((tree algorithm) OR (((bat algorithm) OR (based algorithm))))

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  1. 1

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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    Thesis
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    A New Bats Echolocation-based Algorithm for Single Objective Optimisation by N. M., Yahya, Tokhi, M. Osman, Kasdirin, Hyreil Anuar

    Published 2016
    “…Bats sonar algorithm (BSA) as a swarm intelligence approach utilises the concept of echolocation of bats to find prey. …”
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    Article
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    Application of sampling-based motion planning algorithms in autonomous vehicle navigation by Khaksar, Weria, Mohamed Sahari, Khairul Salleh, Tang, Sai Hong

    Published 2016
    “…In this chapter, a novel sampling-based navigation architecture is introduced, which employs the optimal properties of RRT* planner and the low running time property of low-dispersion sampling-based algorithms. …”
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    Book Section
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    Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure by Othman, Mohamad Lutfi

    Published 2011
    “…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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    Thesis
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    Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

    Published 2004
    “…This project is involved with identification of the available algorithms used in data classification and the implementation of C4.5 decision tree induction algorithm in solving the data classifying task. …”
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    Final Year Project
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    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

    Published 2021
    “…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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    Conference or Workshop Item
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    Modeling of static and dynamic components of bio-nanorobotic systems by Gavgani, Hamidreza Khataee

    Published 2012
    “…In addition, a graph algorithm based on greedy methods is employed to compute a new set of optimal weighted electronic properties of the fullerenes via computing their Minimum Weight Spanning Trees (MWSTs). …”
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    Thesis
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    Improved Bat Algorithm for faster convergence in solving optimisation problem by Ramli, Mohamad Raziff

    Published 2021
    “…In this study, one of the metaheuristic algorithms known as the Bat Algorithm (BA) has been discussed. …”
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    Thesis
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    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

    Published 2022
    “…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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    Thesis
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    Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

    Published 2025
    “…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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    Article
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    Enhancing fairness and efficiency in teacher placement based on staff placement model: an intelligent teacher placement selection model for Ministry of Education Malaysia by Shamsul Saniron, Zulaiha Ali Othman, Abdul Razak Hamdan

    Published 2025
    “…The effectiveness of ITPS was evaluated using five machine learning algorithms: J48, Decision Tree, Naïve Bayes, Random Forest, and K-Nearest Neighbors. …”
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    Article
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    Optimizing the Social Force Model Using New Hybrid WOABAT-IFDO in Crowd Evacuation in Panic Situation by Hamizan, Sharbini, Roselina, Sallehuddin, Habibollah, Haron

    Published 2022
    “…Thus, this research proposes optimization using the one of the latest nature inspired algorithm namely WOABAT-IFDO (Whale-Bat and Improved Fitness-Dependent Optimization) in the SFM interaction component. …”
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    Proceeding
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    Task scheduling in cloud computing using Harris-Hawk Optimization by Iza A. A. Bahar, Azali Saudi, Abdul Kadir, Syed Nasirin Syed Zainol Abidin, Tamrin Amboala, Esmadi Abu Bin Abu, Abdullah B. Mohd. Tahir, Suddin Lada

    Published 2024
    “…In this study, the proposed HHO algorithm is simulated and compared with other well-known swarm intelligence algorithms, including Bat Algorithm (BA), Grey Wolf Optimization (GWO), and Particle Swarm Optimization (PSO). …”
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    Proceedings
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