Search Results - (( java simulation optimization algorithm ) OR ( network users learning algorithm ))

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    Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

    Published 2023
    “…Also, the proposed algorithms focus on the need for cooperative learning that maintains the quality of service, adapts to the network dynamics and achieves energy efficiency in dense small-cell networks. …”
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    Thesis
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    Phishing attack detection using machine learning method by Jupin, John Arthur

    Published 2019
    “…This spam message includes the email and the SMS message that received by the user. There are several algorithms that can be used in the machine learning method to prevent the both attacks. …”
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    Undergraduates Project Papers
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    Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal by Camellia , Mohd Kamal

    Published 2004
    “…Interactive Learning Package for Artificial Neural Network (Demonstration Module) is a learning package that allow the users to learn and enhance the understanding of the ANN subject in more detailed way and apply in the demonstration parts. …”
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    Thesis
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    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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    Thesis
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    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
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    An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

    Published 2015
    “…In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. …”
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    Article
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    Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki by Mohd Zaki, Sofea Najihah

    Published 2024
    “…Convolutional Neural Network (CNN) algorithm was chosen as one of the possible solutions after a thorough analysis of many algorithms for dyslexic handwriting identification. …”
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    Thesis
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    Development of deep reinforcement learning based resource allocation techniques in cloud radio access network by Amjad, Iqbal

    Published 2022
    “…Nextgeneration networks are envisioned to support management to maximize the user s ’ dynamic and agile network quality of service (QoS). …”
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    Final Year Project / Dissertation / Thesis
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    A network aware based recommender system for VOIP application service in eLearning environment / Nazdiana Ab. Wahab by Ab. Wahab, Nazdiana

    Published 2009
    “…This paper showed the integration of VOIP in a simple eLearning prototype system. A network aware based algorithm is used to recommend users the best VOIP services available at that point of time (whether audio, video or data) based on the real time data obtained from bandwidth measurement tool. …”
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    Thesis
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    Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media A., Abu Osman, Md. Tap

    Published 2011
    “…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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    Article
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    Stock indicator scanner customization tool using deep reinforcement learning by Cheong, Desmond YongHong

    Published 2022
    “…This project will deliver a web application with dynamic stock prediction model based on deep reinforcement learning or more particularly, Deep Q-Network (DQN) algorithm which enable input customization. …”
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    Final Year Project / Dissertation / Thesis
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    Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media Anugerah, Md. Tap, Abu Osman

    Published 2011
    “…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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    Article
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    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
    Review
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    Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

    Published 2022
    “…This is because the reinforcement learning agent is able to predict items directly by capture user latent information and explore large sparsity state space effectively. …”
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    Thesis
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    Applying learning to filter text by Sainin, Mohd Shamrie

    Published 2005
    “…The use of probabilistic approaches such as naïve Bayes algorithm is the effective algorithms currently known for learning to filter or classify text document.Naïve Bayes algorithm is one of the algorithms in Machine Learning that manipulates probability estimation or reasoning about the observed data.The growing of bulk e-mail or known as spam e-mail becomes a threat to users’ privacy and network load and in the case of e -mail filtering,naïve Bayes classifier can be trained to automatically detect spam messages.Similar to the e-mail, forum application may be misused by the user to send bad messages and in some extent may offence other readers.Forum filtering may be less important compared to e-mail spam filtering; however there is a possibility of using naïve Bayes to learn the messages and automatically detect bad messages.Most of the forum application found in the web is applying keyword based text filtering which scan the words and change the detected words into certain representation.Instead of defining a set of keywords to filter the forum messages, this paper will explains the experiment in applying a learning to filter text especially in the educational and anonymous forum message, where there is no user registration required to submit messages.…”
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    Conference or Workshop Item