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  1. 1
    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment

    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    Published 2016
    “…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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  2. 2
    A hybrid-based modified adaptive fuzzy inference engine for pattern classification

    A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

    Published 2011
    “…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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  3. 3
    Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim

    Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

    Published 2007
    “…In this paper, GA has been applied to find the minimum path, then result will be compared with Dijkstra's algorithm are presented.…”
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  4. 4
    Path optimization using genetic algorithm evolution

    Path optimization using genetic algorithm evolution by Low C.Y., Chong K.H., Salleh K., Johnny K.S.P.

    Published 2023
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  5. 5
    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…All algorithms showed more stability and accuracy when training size applied is more than 6% by the Equal Sample Rate (ESR) method with six variables. …”
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  6. 6
    The evolution and trend of chain code scheme

    The evolution and trend of chain code scheme by Wulandhari, Lily Ayu, Haron, Habibollah

    Published 2008
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  7. 7
    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…However, it cannot be applied when the sample size is less than the number of predictor variables. In addressing this problem, some robust procedures for high dimensional dataset via the RFCH algorithm are developed. …”
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  8. 8
    A modified single-stacked ensemble framework for prognostic analysis of leukemia relapse

    A modified single-stacked ensemble framework for prognostic analysis of leukemia relapse by Chuan, Zun Liang

    Published 2026
    “…Bone marrow transplant (BMT) is a life-saving treatment for acute leukemia, though relapse remains a risk due to donor compatibility, clinical variability, and healthcare resource limitations. This chapter introduces a modified single-stacked ensemble prognostic algorithm optimized for interpretability, transparency, and reliability, especially for small and imbalanced datasets. …”
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  9. 9
    An ensemble of neural network and modified grey wolf optimizer for stock prediction

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…Additionally, the research restricts the number of variables through feature selection to enhance the performance of the algorithm. …”
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  10. 10
    Boosting and bagging classification for computer science journal

    Boosting and bagging classification for computer science journal by Wibawa, Aji Prasetya, Putri, Nastiti Susetyo Fanany, Al Rasyid, Harits, Nafalski, Andrew, Hashim, Ummi Rabaah

    Published 2023
    “…In the DT algorithm, both variables are altered, whereas, in the GNB algorithm, just the estimator's value is modified. …”
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  11. 11
    Literature Review of Optimization Techniques for Chatter Suppression In Machining

    Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

    Published 2011
    “…In this paper, it can be observed that for chatter suppression, optimization focuses on spindle design, tool path, cutting process, and variable pitch. Various algorithms can be applied in the optimization of machining problems; however, Differential Evolution is the most appropriate for use in chatter suppression, being less time consuming, locally optimal, and more robust than both Genetic Algorithms, despite their wide applications, and Sequential Quadratic Programming, which is a famous conventional algorithm.…”
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  12. 12
    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators

    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

    Published 2024
    “…Interestingly, the manipulator's behaviours using the spiral dynamics algorithm for PID controller tuning were superior to those using alternative methods. …”
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  13. 13
    Fingerprint frontier: the evolution of biometric security

    Fingerprint frontier: the evolution of biometric security by Khalifa, Othman Omran

    Published 2023
    “…The author believes that "Fingerprint Frontier: The Evolution of Biometric Security" will serve as a complete reference, shining light on the current landscape while exposing potential future paths in this ever-changing subject. …”
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  14. 14
    Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz

    Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz by Muhammad Firdaus , Aziz

    Published 2022
    “…ML algorithms were used to examine significant variables utilising feature selection methods. …”
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  15. 15
    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin

    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

    Published 2013
    “…This mechanism is restricted to search the possible solutions in a critical path. Modification on the path by using neighborhood search significantly reduces the total length of the makespan. …”
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  16. 16
    A novel high performance routing technique for cross-referencing DMFBs

    A novel high performance routing technique for cross-referencing DMFBs by Pranab, Roy, Hafizur, Rahaman

    Published 2012
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  17. 17
    Soliton cellular automata constructed from a Uq(Dn[1])-crystal Bn,1 and kirillov-reshetikhin type bijection for Uq(E6[1])-crystal B6,1

    Soliton cellular automata constructed from a Uq(Dn[1])-crystal Bn,1 and kirillov-reshetikhin type bijection for Uq(E6[1])-crystal B6,1 by Mohamad, Mahathir

    Published 2012
    “…The algorithm only uses the structure of the crystal graph, hence could also be applied for other exceptional types. …”
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  18. 18
    A conceptual Malaysian private healthcare university-of-the-future business model: staying relevant in the digital and post-covid era

    A conceptual Malaysian private healthcare university-of-the-future business model: staying relevant in the digital and post-covid era by Saiid, Muhammad, Bah, Ahmadou Pathe, Ahmad Dahlan, Abdul Rahman

    Published 2022
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  19. 19
    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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  20. 20
    Predicting motorcycle customization preferences using machine learning

    Predicting motorcycle customization preferences using machine learning by Saputra, Ananta, Utoro, Rio Korio, Roedavan, Rickman, Soegiarto, Duddy, Moorthy, Kohbalan, Pratondo, Agus

    Published 2025
    “…The classification model was developed using the Random Forest algorithm, Support Vector Machine and Logistic Regression with 5-fold Cross validation. …”
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