Search Results - (( developing boosts detection algorithm ) OR ( java data optimization algorithm ))

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  1. 1

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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    Undergraduates Project Papers
  2. 2

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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    Article
  3. 3

    Object detection system using haar-classifier by Wan Najwa, Wan Ismail

    Published 2009
    “…An algorithm for the design object detection systems is presented. …”
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    Undergraduates Project Papers
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    Anomaly detection in network traffic using machine learning by Amir Muhammad Hafiz, Othman, Mohd Faizal, Ab Razak, Mohd Izham, Mohd Jaya, Nurul Azma, Abdullah, Alanda, Alde

    Published 2026
    “…These findings demonstrate that machine learning techniques have strong potential to enhance network security by improving anomaly detection, providing a promising direction for developing intelligent, adaptive intrusion detection.…”
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    Article
  6. 6

    Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

    Published 2017
    “…The performance of the developed system has been compared with the existing intelligent skin detection systems. …”
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    Thesis
  7. 7

    A random search based effective algorithm for pairwise test data generation by Sabira, Khatun, K. F., Rabbi, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2011
    “…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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    Conference or Workshop Item
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    Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

    Published 2018
    “…The results are used to develop the hybrid learning algorithm based on the AdaBoost, Bagging, and RUSBoost methods to predict the damage in the tower based on dynamic frequency domain. …”
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    Thesis
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    EasyA: Easy and effective way to generate pairwise test data by Rabbi, Khandakar Fazley, Sabira, Khatun, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2013
    “…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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    Conference or Workshop Item
  12. 12

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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    Thesis
  13. 13

    Bio-inspired for Features Optimization and Malware Detection by Mohd Faizal, Ab Razak, Nor Badrul, Anuar, Fazidah, Othman, Ahmad, Firdaus, Firdaus, Afifi, Rosli, Salleh

    Published 2018
    “…In recognizing the Android malware, it appears that AdaBoost is able to achieve good detection accuracy with a true positive rate value of 95.6%, using Android permissions. …”
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    Article
  14. 14

    Gene Selection For Cancer Classification Based On Xgboost Classifier by Teo, Voon Chuan

    Published 2022
    “…XGBoost Classifier is applied in this research, which it is an efficient open-source implementation of the gradient boosted trees algorithm. Gradient boosting is a supervised learning algorithm, which attempts to accurately predict a target variable by combining the estimates of a set of simplifier, weaker models. …”
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    Undergraduates Project Papers
  15. 15

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
  16. 16

    Bio-inspired for Features Optimization and Malware Detection by Razak, Mohd Faizal Ab, Anuar, Nor Badrul, Othman, Fazidah, Firdaus, Ahmad, Afifi, Firdaus, Salleh, Rosli

    Published 2018
    “…In recognizing the Android malware, it appears that AdaBoost is able to achieve good detection accuracy with a true positive rate value of 95.6%, using Android permissions. …”
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    Article
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    Skin burn degree detection using Convolutional Neural Network / Nur Amaleen Aishah Salehuddin by Salehuddin, Nur Amaleen Aishah

    Published 2024
    “…This project aims on the development of a Skin Burn Degree Detection system utilizing Convolutional Neural Network (CNN) algorithms. …”
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    Thesis
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    Detection of mature and immature oil palm from image Sentinel-2 using Google Earth Engine (GEE) / Nurul Ain Nabilah Sharuddin by Sharuddin, Nurul Ain Nabilah

    Published 2022
    “…Therefore, image Sentinel-2 efficiently detected mature and immature oil palms' land cover using the RF algorithm implemented in GEE.…”
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    Thesis
  20. 20

    Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.] by Afolabi, Akindele Segun, Akinola, Olubunmi Adewale, Odetoye, Oyinlolu Ayomidotun, Adetiba, Emmanuel

    Published 2025
    “…As a result of these benefits, a plethora of machine learning-based solutions for occupancy detection has been developed in the literature. However, many of these solutions have poor prediction accuracies. …”
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    Article