Search Results - (( pattern learning algorithm ) OR ((( patterns drops algorithm ) OR ( patterns path algorithm ))))

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  1. 1

    An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability by Bouke, Mohamed Aly, Abdullah, Azizol

    Published 2023
    “…In this paper, we investigate the impact of pattern leakage during data preprocessing on the reliability of Machine Learning (ML) based intrusion detection systems (IDS). …”
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    Article
  2. 2

    Destination prediction based on past movement history by Waheed, Mihsaan

    Published 2020
    “…In this paper we explore destination prediction using the past movement history, where the history is built using machine learning. Matching of the history with the user's movement is done through a simple pattern recognition technique. …”
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    Thesis
  3. 3

    A lightweight graph-based pattern recognition scheme in mobile ad hoc networks. by Raja Mahmood, Raja Azlina, Muhamad Amin, Anang Hudaya, Amir, Amiza, Khan, Asad I.

    Published 2012
    “…A lightweight, low-computation, distributed intrusion detection scheme termed the distributed hierarchical graph neuron (DHGN) was proposed to be incorporated into a cooperative intrusion detection system (IDS) in mobile ad hoc networks (MANETs). Its one-cycle learning and divide and distribute recognition task approach allows DHGN to detect similar patterns in short of time. …”
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    Book Section
  4. 4

    Advances in materials informatics: A review by Sivan, Dawn, Kumar, K. Satheesh, Aziman, Abdullah, Raj, Veena, Izan Izwan, Misnon, Ramakrishna, Seeram, Jose, Rajan

    Published 2024
    “…Progress of MI depends on the strength of database and artificial intelligence protocols comprising machine learning (ML) and deep learning (DL) frameworks. Conventional ML models are simple and interpretable, relying on statistical techniques and algorithms to learn patterns and make predictions with limited data. …”
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    Article
  5. 5

    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

    Published 2011
    “…It was found that (by the Group Method of Data Handling algorithm), length of the pipe, wellhead pressure, and angle of inclination have a pronounced effect on the pressure drop estimation under these conditions. …”
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    Thesis
  6. 6

    Machine Learning Based Detection for Compromised Accounts on Social Media Networks by K., Swapna, M., Rithika, K., Rukmini, S., Swachitha, Y., Komali

    Published 2025
    “…Behavioral features include changes in posting frequency, interaction patterns, and location data. We employ machine learning algorithms to train models that can accurately classify accounts as compromised or legitimate based on these features. …”
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    Article
  7. 7

    End to end performance analysis over IP RAN network / Armi Shahran Mohamad by Mohamad, Armi Shahran

    Published 2011
    “…The expected result from the test experiment is able to produce set of information such as uplink and downlink duration time, throughput downlink pattern comparison, bytes received comparison and data transfer time taken. …”
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    Thesis
  8. 8

    An integrated priority-based cell attenuation model for dynamic cell sizing by Amphawan, Angela, Omar, Mohd Nizam, Din, Roshidi

    Published 2012
    “…Real-time predicted mobile traffic from the EFuNN structure was used to control the size of all the cells.Results obtained demonstrate the robustness of the integrated module in recognizing the temporal pattern of the mobile traffic and dynamically controlling the cell size in order to reduce the number of calls dropped.…”
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    Article
  9. 9

    AI-Based Drug Design: Revolutionizing Drug Discovery through in Silico Analysis by Yamini Priya, Deepthimahanthi, Prakash, Balu, Wong, Ling Shing, Kumar, Krishnan, J., Manjunathan, K., Ashokkumar, M., Jayanthi, M., Suganthi, G., Abirami

    Published 2023
    “…By harnessing AI's virtuosity, drug discovery processes are imbued with unprecedented speed and precision. Machine learning algorithms harmonize with intricate biological datasets, unraveling patterns and relationships previously enshrouded in complexity. …”
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    Article
  10. 10

    Simulation performance comparison of A*, GLS, RRT and PRM path planning algorithms by Muhammad, Aisha, Nor Rul Hasma, Abdullah, Mohammad A.H., Ali, Shanono, Ibrahim Haruna, Rosdiyana, Samad

    Published 2022
    “…In this study, four robust path planning algorithms, namely: Probabilistic Roadmaps (PRMs), A-star, the Rapidly Exploring Random Trees (RRTs), and Generalized Laser Simulator (GLS), were simulated and their performance was measured and compared according to the total path distance covered, search time and path smoothness. …”
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    Conference or Workshop Item
  11. 11

    A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

    Published 2022
    “…The suggested algorithm outperforms the competition in terms of improving path cost, smoothness, and search time. …”
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    Thesis
  12. 12

    Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

    Published 2021
    “…For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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    Monograph
  13. 13

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. …”
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    Thesis
  14. 14
  15. 15

    A Scalable Algorithm for Constructing Frequent Pattern Tree by Noraziah, Ahmad, Herawan, Tutut, Zailani, Abdullah, Mustafa, Mat Deris

    Published 2014
    “…Frequent Pattern Tree (FP-Tree) is a compact data structure of representing frequent itemsets. …”
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    Article
  16. 16

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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    Thesis
  17. 17

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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    Article
  18. 18

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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    Article
  19. 19

    Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia by Ajibola, Lamidi-Sarumoh Alaba

    Published 2019
    “…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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    Thesis
  20. 20

    Scheduling of batch process plant / Abdul Aziz Abu Bakar by Abu Bakar, Abdul Aziz

    Published 1995
    “…Batch production is used throughout the process industries for the manufacture of fine chemical, plastics, pharmaceuticals, paints, ceramics, cosmetics, or whatever production quantities are small, product value is very high or product demand pattern is changeable. This research work is devoted to software development of scheduling and control algorithm of batch process plant using shortest path method developed by Dijkstra and K* shortest path method developed by Jin Y. …”
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    Student Project