Search Results - intelligence based ((factors algorithm) OR (((bayes algorithm) OR (bees algorithm))))

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  1. 1

    Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging by Olanrewaju, Rashidah Funke, Al-Qudah, Dua'a Mahmoud Mohammad, Azman, Amelia Wong, Yaacob, Mashkuri

    Published 2016
    “…This work proposes a hybrid method that optimize cache replacement algorithm using Naïve Bayes (NB) based approach. Naïve Bayes is an intelligent method that depends on Bayes’ probability theory integrated with Adaptive Weight Ranking Policy (AWRP) via dynamic aging factor to improve the response time and network performance. …”
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    Article
  2. 2

    Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

    Published 2011
    “…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
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    Conference or Workshop Item
  3. 3

    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

    Published 2019
    “…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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    Monograph
  4. 4

    Machine Learning Applications in Offense Type and Incidence Prediction by Balaji, R., Manjula Sanjay, Koti, Harprith, Kaur

    Published 2024
    “…Naive Bayes, a probabilistic classifier based on Bayes' theorem, is particularly effective in handling large datasets and making accurate predictions. …”
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    Article
  5. 5

    Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

    Published 2011
    “…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
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    Final Year Project
  6. 6

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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    Thesis
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    Optimal design of step – cone pulley problem using the bees algorithm by Yusof, Noor Jazilah, Kamaruddin, Shafie

    Published 2021
    “…Most of these algorithms were developed based on the collective behavior of social swarms of ants, bees, a flock of birds, and schools of fish. …”
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    Book Chapter
  9. 9

    Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO) by Liew, Jia Hun

    Published 2024
    “…Swarm intelligence is a branch of artificial intelligence that studies the collective behavior of groups of social animals such as birds, fish, and bees. …”
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    Thesis
  10. 10

    Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Mohammed, Waheed Yasin, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

    Published 2016
    “…Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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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
  13. 13

    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim by Masmuhallim, Anis Athirah

    Published 2024
    “…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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    Thesis
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    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

    Published 2013
    “…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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    Thesis
  16. 16

    Artificial bee colony for inventory routing problem with backordering by Moin, N.H., Halim, H.Z.A.

    Published 2014
    “…We propose a metaheuristic method, Artificial Bee Colony (ABC) to solve the IRPB.The ABCalgorithm is a swarm based heuristics which simulates the intelligent foraging behaviour of a honey bee swarm and sharing that information of the food sources with the bees in the nest. …”
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    Conference or Workshop Item
  17. 17

    A quick gbest guided artificial bee colony algorithm for stock market prices prediction by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…In this respect, in the present manuscript, we propose an algorithm based on ABC to minimize the error in the trend and actual values by using the hybrid technique based on neural network and artificial intelligence. …”
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    Article
  18. 18

    Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems by Ibrahim, Hamidah, Yasin, Waheed, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati

    Published 2016
    “…Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. …”
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    Article
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    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

    Published 2017
    “…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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    Article