Search Results - (( simulation optimization rfid algorithm ) OR ( code classification learning algorithm ))

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  1. 1

    Optimization of supply chain management by simulation based RFID with XBEE Network by Soomro, Aftab Ahmed

    Published 2015
    “…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. …”
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    Thesis
  2. 2

    Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning by Elewe, Adel Muhsin, Hasnan, Khalid, Nawawi, Azli

    Published 2017
    “…The RFID network planning (RNP) problem belongs to the large-scale multi-objective hard optimization problems. …”
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    Article
  3. 3

    Optimization of RFID network planning using MDB-FA method by Elewe, Adel Muhsin, Hasnan, Khalid, Nawawi, Azli

    Published 2017
    “…The generated data are utilized as an input representation to apply into firefly algorithm based on Density-Based Algorithm (DBSCAN) to find the optimal network solution. …”
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    Article
  4. 4

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…Several machine learning techniques based on supervised learning have been adopted in the classification of malware. …”
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    Proceeding Paper
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    An efficient unknown detection approach for RFID data stream management system by Siti Salwani, Yaacob, Hairulnizam, Mahdin, Wijayanto, Inung, Muhammad Aamir, -, Mohd Izham, Mohd Jaya, Nabilah Filzah, Mohd Radzuan, Al Fahim, Mubarak Ali

    Published 2025
    “…This study highlights the potential for significant improvements in RFID system efficiency and paves the way for future research in optimizing RFID tag detection methodologies. …”
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    Article
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    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

    Published 2024
    “…The data was gathered using real-time packet capturing tools which were then processed and moved with model development using different deep learning algorithms such as, LSTM, MLP, RNN and Autoencoders. …”
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    Article
  9. 9

    Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

    Published 2023
    “…Aerial photography; Aircraft detection; Antennas; Codes (symbols); Discrete cosine transforms; Discrete wavelet transforms; Glossaries; Image classification; Image coding; Image enhancement; Learning algorithms; Learning systems; Object recognition; Remote sensing; Satellite imagery; Satellites; Unmanned aerial vehicles (UAV); Discrete tchebichef transforms; Discriminative features; Finite Ridgelet Transform; Histogram of oriented gradients; Image processing and computer vision; Scale invariant feature transforms; SIFT; Sparse coding; Classification (of information)…”
    Article
  10. 10

    An innovative approach for estimating the number of tags in RFID traffic monitoring systems by Chebil, Jalel, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul

    Published 2024
    “…This paper presents a new approach to estimate the number of tags within the reader's range in an RFID traffic monitoring system, with the goal of improving the dynamic framed slotted ALOHA anti-collision algorithm. …”
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    Proceeding Paper
  11. 11

    Source code classification using latent semantic indexing with structural and frequency term weighting by Yusof, Yuhanis, Alhersh, Taha, Mahmuddin, Massudi, Mohamed Din, Aniza

    Published 2012
    “…Furthermore,it is also learned that the use of structural information in the weighting scheme contribute to a better classification.…”
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    Article
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    Machine learning-based enhanced deep packet inspection for IP packet priority classification with differentiated services code point for advance network management by Khan, Fazeel Ahmed, Abubakar, Adamu

    Published 2024
    “…This study presents an approach to enhance intelligent packet forwarding priority classification on Differentiated Services Code Point (DSCP), leveraging classifiers from machine learning algorithms for Deep Packet Inspection (DPI). …”
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    Article
  14. 14

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…Learning programming from source code examples is a common behavior among novices. …”
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    Article
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    Maldroid- attribute selection analysis for malware classification by Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman

    Published 2019
    “…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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    Article
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    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

    Published 2018
    “…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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    Article
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    Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

    Published 2025
    “…Attack data was obtained from the ClaMP dataset, which has an unbalanced data set, and has very high noise, so it is necessary to analyze data packets in network logs and optimize feature extraction which is then analyzed statistically with machine learning algorithms. The purpose of the study is to detect, classify malware attacks using a variety of ML Algorithm models such as SVM, KNN and Neural Network and testing detection performance. …”
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    Article
  20. 20

    Classifying good and bad websites by Koo, Ee Woon

    Published 2015
    “…The classification process is made easy by using set of features generated from HTML codes. …”
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    Final Year Project Report / IMRAD