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  1. 1

    Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

    Published 2023
    “…These retransmissions further enhance the delay in LoRa networks. This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”
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    Adaptive bias simulated evolution algorithm for placement by Youssef, H.

    Published 2001
    “…In this work, we propose an adaptive bias scheme which adjusts automatically to the quality of solution and makes the algorithm independent of the problem class or instance, as well as any user defined value. …”
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    article
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    Whale optimization algorithm: analysis and full survey by Abualigah, Laith

    Published 2024
    “…Various adaptations and hybridizations of the WOA are reviewed, including adaptive strategies, constrained and multiobjective optimization extensions, and combinations with other algorithms. …”
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    Squirrel Search Algorithm for Portfolio Optimization by Dhaini, Mahdi

    Published 2019
    “…In this paper, we design and adapt a Squirrel Search Algorithm (SSA) for the unconstrained and constrained portfolio optimization problems. …”
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    masterThesis
  8. 8

    Drones Tracking Adaptation Using Reinforcement Learning: Proximal Policy optimization by Alhadhrami, Esra Ebrahim

    Published 2023
    “…Proximal Policy Optimization (PPO), a state-of-the-art policy optimization algorithm, was employed to determine the optimal Q value that enhances tracking performance, as measured by Root Mean Square Error (RMSE). …”
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    Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT) by AlHamaydeh, Mohammad

    Published 2017
    “…The powerful genetic algorithm optimization technique is augmented with an innovative “domain-trimming” modification. …”
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    article
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    Parallel physical optimization algorithms for allocating data to multicomputer nodes by Mansour, Nashat

    Published 1994
    “…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …”
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    Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

    Published 2004
    “…The main contributions of this work are two evolutionary approaches to this optimization problem. In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …”
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    masterThesis
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    Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

    Published 1992
    “…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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    masterThesis
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    Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

    Published 2023
    “…In response to these challenges, this article introduces a cutting-edge edge computing architecture grounded in virtual organizations, federated learning, and deep reinforcement learning algorithms, tailored to optimize energy consumption within buildings/homes and facilitate demand response. …”
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    An ant colony optimization algorithm to improve software quality prediction models by Azar, D.

    Published 2011
    “…We use an ant colony optimization algorithm in the adaptation process. The approach is validated on stability of classes in object-oriented software systems and can easily be used for any other software quality characteristic. …”
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    Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog... by Mutasim Baba, Fuad

    Published 2023
    “…This paper aims to develop long-term adaptation strategies for the existing Canadian school buildings under extreme current and future climates using a developed methodology based on global and local sensitivity analysis and Multi-Objective Optimization Genetic Algorithm. …”
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