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  1. 1
    The need for an enhanced IoT-based malware detection model using artificial intelligence (AI) algorithm: a review

    The need for an enhanced IoT-based malware detection model using artificial intelligence (AI) algorithm: a review by Maidin, Siti Sarah, Yahya, Norzariyah

    Published 2023
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  2. 2
    Empirical study on intelligent android malware detection based on supervised machine learning

    Empirical study on intelligent android malware detection based on supervised machine learning by Abdullah, Talal A.A., Ali, Waleed, Abdulghafor, Rawad Abdulkhaleq Abdulmolla

    Published 2020
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  3. 3
    An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection

    An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection by Shing, Chiang Tan, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Lim, Pey, Yun Goh, Chee, Peng Lim

    Published 2023
    “…In addition, DL-based malware detection methods often entail single classifiers. …”
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  4. 4
    Designing a new model for Trojan horse detection using sequential minimal optimization

    Designing a new model for Trojan horse detection using sequential minimal optimization by Madihah Mohd Saudi, Abuzaid A.M., Taib B.M., Abdullah Z.H.

    Published 2024
    Conference Paper
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  5. 5
    A new mobile malware classification for SMS exploitation

    A new mobile malware classification for SMS exploitation by Zaizi N.J.M., Khailani A., Madihah Mohd Saudi

    Published 2024
    Conference Paper
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  6. 6
    Designing a New Model for Trojan Horse Detection Using Sequential Minimal Optimization

    Designing a New Model for Trojan Horse Detection Using Sequential Minimal Optimization by Saudi, MM, Abuzaid, AM, Taib, BM, Abdullah, ZH

    Published 2024
    “…Based on the experiment conducted, the Sequential Minimal Optimization (SMO) algorithm has outperformed other machine learning algorithms with 98.2 % of true positive rate and with 1.7 % of false positive rate.…”
    Proceedings Paper
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  7. 7
    WiMAX Traffic Forecasting Based On Artificial Intelligence Techniques

    WiMAX Traffic Forecasting Based On Artificial Intelligence Techniques by Daw Abdulsalam Ali Daw

    Published 2024
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  8. 8
    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim

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

    Published 2024
    “…This research presents a mobile malware static detection method based on Naive Bayes. …”
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    Thesis
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  9. 9
    A New Algorithm For Prediction WIMAX Traffic Based On Artificial Neural Network Models

    A New Algorithm For Prediction WIMAX Traffic Based On Artificial Neural Network Models by Daw Abdulsalam Ali Daw, Kamaruzzaman Bin Seman, Madihah Mohd Saudi

    Published 2024
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  10. 10
    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin

    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin by Alsahag, Ali Mohammed, Mohd Ali, Borhanuddin, Noordin, Nor Kamariah, Mohamad, Hafizal

    Published 2014
    “…One example of such a network is called WiMAX which is driven by WiMAX Forum based on IEEE 802.16 Wireless MAN standard. …”
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  11. 11
    The application of neural networks and min-max algorithm in digital congkak

    The application of neural networks and min-max algorithm in digital congkak by Che Pa, Noraziah, Alwi, Asmidah, Mohamed Din, Aniza, Safwan, Muhammad

    Published 2013
    “…To make it intelligent, its player agent was developed using a combination of Neural Networks and Min-Max algorithm. …”
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  12. 12
    Designing and Developing an Intelligent Congkak

    Designing and Developing an Intelligent Congkak by Muhammad Safwan, Mohd Shahidan

    Published 2011
    “…and “Can Min-Max algorithm (MM) be speeded up by using NN as a forward-pruning method?”. …”
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  13. 13
    Data normalization techniques in swarm-based forecasting models for energy commodity spot price

    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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  14. 14
    A Cryptojacking Detection System With Product Moment Correlation Coefficient (Pmcc) Heatmap Intelligent

    A Cryptojacking Detection System With Product Moment Correlation Coefficient (Pmcc) Heatmap Intelligent by Kong, Jun Hao

    Published 2023
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    Undergraduates Project Papers
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  15. 15
    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks

    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

    Published 2013
    “…It reduces the number of handovers by 29.7% and 26.9%, respectively, compared to the conventional RSSI based handover algorithm and the previous worked, mobility improved handover (MIHO) algorithm. …”
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  16. 16
    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks

    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…Firstly is by enhancing the learning algorithm of a neural-fuzzy network; and secondly by devising an ensemble model to combine the predictions from multiple neural-fuzzy networks using an agent-based framework. …”
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  17. 17
    Modelling of intelligent intrusion detection system: making a case for snort

    Modelling of intelligent intrusion detection system: making a case for snort by Olanrewaju, Rashidah Funke, Ku zahir, Ku Nor Afiza, Asnawi, Ani Liza, Sanni, Mistura Laide, Ahmed, Abdulkadir Adekunle

    Published 2018
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    Proceeding Paper
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  18. 18
    Modified HOS based Eigenvector algorithm for improvement of poor SNR of Seismic data

    Modified HOS based Eigenvector algorithm for improvement of poor SNR of Seismic data by A.F.M., Hani, M.S., Younis

    Published 2007
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  19. 19
    Embedded Artificial Intelligent (AI) To Navigate Cart Follower

    Embedded Artificial Intelligent (AI) To Navigate Cart Follower by Tang, Khai Luen

    Published 2018
    “…One of the solution for the problem is to create an Artificial Intelligent (AI) cart follower. Therefore, this research is to create an AI system for the AI cart follower with a visual based sensor. …”
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    Monograph
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  20. 20
    Reactive memory model for ant colony optimization and its application to TSP

    Reactive memory model for ant colony optimization and its application to TSP by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2014
    “…The performances of six (6) ant colony optimization variants were evaluated to select the base for the proposed model.Based on the results, Max-Min Ant System has been chosen as the base for the modification.The modified algorithm called RMMAS, was applied to TSPLIB95 data and results showed that RMMAS outperformed the standard MMAS.…”
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