Search Results - (( evolution implementation learning algorithm ) OR ( service application optimization algorithm ))

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    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…Individual emotional states are highly variable and are subject to evolution from personal experiences. For this reason, the above system is designed to be able to perform learning and classification in real-time to account for inter-individual and intra-individual emotional drift over time. …”
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    Machine learning and deep learning approaches for cybersecurity: a review by Halbouni, Asmaa Hani, Gunawan, Teddy Surya, Habaebi, Mohamed Hadi, Halbouni, Murad, Kartiwi, Mira, Ahmad, Robiah

    Published 2022
    “…It discusses recent machine learning and deep learning work with various network implementations, applications, algorithms, learning approaches, and datasets to develop an operational intrusion detection system.…”
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    Article
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    Modelling and optimization of a transit services with feeder bus and rail system / Mohammadhadi Almasi by Mohammadhadi, Almasi

    Published 2015
    “…In this study, optimized transit services and coordinated schedules are developed using metaheuristic algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), water cycle algorithm (WCA) and imperialist competitive algorithm (ICA). …”
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    Thesis
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    Optimized crossover genetic algorithm for vehicle routing problem with time windows by Nazif, Habibeh, Lee, Lai Soon

    Published 2010
    “…Problem statement: In this study, we considered the application of a genetic algorithm to vehicle routing problem with time windows where a set of vehicles with limits on capacity and travel time are available to service a set of customers with demands and earliest and latest time for serving. …”
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    Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich by Bathich, Ammar

    Published 2019
    “…The main objective of this work is to propose and implement an efficient handover decision procedure based on users’ profiles using Q-learning technique in a LTE-A macrocell-femtocell networks. …”
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    Dynamic Task Offloading Algorithm for optimising IoT network quality of service in the Mobile-Fog-Cloud System by Nwogbaga, Nweso Emmanuel

    Published 2023
    “…Secondly, a hybrid Genetic Algorithm and Enhanced Inertia Weight Particle Swarm Optimization (GAEIWPSO) algorithm for optimal resource allocation to minimize the delay is proposed. …”
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    An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks by Al-Kharasani, Ameen Mohammed Abdulkarem, Othman, Mohamed, Abdullah, Azizol, Kweh, Yeah Lun

    Published 2016
    “…The quality of service (QoS) requirements do not define a marker algorithm for service classes and managing network traffic to provide fair bandwidth sharing among aggregate flows. …”
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    Artificial fish swarm optimization for multilayer network learning in classification problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam

    Published 2012
    “…Nature-Inspired Computing (NIC) has always been a promising tool to enhance neural network learning. Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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    Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2012
    “…The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Nowadays, many task allocation techniques are used but the most efficient technique needs to be figured out. Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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    Academic Exercise
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    Multi agent quality of service routing based on scheme ant colony optimization algorithm by Baygi, Maassoumeh Javadi

    Published 2014
    “…This research presents a per class QoS routing approach based on Ant Colony Optimization (ACO) called ACR-QoS to provide QoS for different Class of Services (CoSs). …”
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    Thesis
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    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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    Proposed algorithm for scheduling in computational grid using backfilling and optimization techniques by Dakkak, Omar, Awang Nor, Shahrudin, Che Mohamed Arif, Ahmad Suki

    Published 2016
    “…To allocate the suitable resources for the incoming jobs, a scheduling algorithm has to manage this process.In this paper, we provide a critical review the recent mechanisms in “grid computing” environment.In addition, we propose a new scheduling algorithm to minimize the delay for the end user, Gap Filling policy will be applied to improve the performance of the priority algorithm.Then, an optimization algorithm will perform in order to further enhance the initial result for that obtained from backfilling mechanism.The main aim of the proposed scheduling mechanism is to improve the QoS for the end user in a real grid computing environment.…”
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