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Showing 1 - 17 results of 17 for search 'core ((genetic algorithm) OR (detection algorithm))', query time: 0.07s Refine Results
  1. 1
    Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem

    Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

    Published 1999
    “…The core of the proposed algorithm is based on genetic algorithms. …”
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  2. 2
    A novel linear time corner detection algorithm

    A novel linear time corner detection algorithm by Sarfraz, M.

    Published 2005
    “…We have presented a novel scheme for detecting corners of a planner object SRM05. The core of the algorithm is based upon slope analysis. …”
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  3. 3
    Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem

    Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem by Montawy, A.H.

    Published 2020
    “…The core of the proposed algorithm is based on genetic algorithms. …”
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  4. 4
    Power-constrained system-on-a-chip test scheduling using a genetic algorithm

    Power-constrained system-on-a-chip test scheduling using a genetic algorithm by Harmanani, Haidar M.

    Published 2006
    “…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. …”
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  5. 5
    Optimizing Energy Consumption In Cloud Datacenters

    Optimizing Energy Consumption In Cloud Datacenters by Khan, Mueez Ahmad

    Published 2024
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  6. 6
    Logistics Optimization Using Hybrid Genetic Algorithm (HGA): A Solution to the Vehicle Routing Problem With Time Windows (VRPTW)

    Logistics Optimization Using Hybrid Genetic Algorithm (HGA): A Solution to the Vehicle Routing Problem With Time Windows (VRPTW) by Ayesha Maroof (17984053)

    Published 2024
    “…This research introduces a cutting-edge Hybrid Genetic Algorithm-Solomon Insertion Heuristic (HGA-SIH) solution, reinforced by the powerful Solomon Insertion constructive heuristic to solve the VRPTW as an NP-hard problem. …”
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  7. 7
    Fine-grain watermarking for intellectual property protection

    Fine-grain watermarking for intellectual property protection by Stefano Giovanni Rizzo (18615112)

    Published 2019
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  8. 8
    Edge intelligence for network intrusion prevention in IoT ecosystem

    Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura, Habiba

    Published 2023
    “…As a result, the Intrusion Detection System (IDS) is a core component of a modern IoT platform. …”
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  9. 9
    Edge intelligence for network intrusion prevention in IoT ecosystem

    Edge intelligence for network intrusion prevention in IoT ecosystem by Mansura Habiba (17808302)

    Published 2023
    “…As a result, the Intrusion Detection System (IDS) is a core component of a modern IoT platform. …”
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  10. 10
    Test bus assignment, sizing, and partitioning for system-on-chip

    Test bus assignment, sizing, and partitioning for system-on-chip by Harmanani, Haidar M.

    Published 2007
    “…In this paper, an efficient genetic algorithm for designing test access architectures while investigating test bus sizing and concurrently assigning cores to test buses is proposed. …”
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  11. 11
    A method for optimizing test bus assignment and sizing for system-on-a-chip

    A method for optimizing test bus assignment and sizing for system-on-a-chip by Harmanani, Haidar M.

    Published 2017
    “…In this paper, we propose an efficient genetic algorithm to design test access architectures while investigating test bus sizing and assignment of cores to test buses in the system. …”
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  12. 12
    A Literature Review on System Dynamics Modeling for Sustainable Management of Water Supply and Demand

    A Literature Review on System Dynamics Modeling for Sustainable Management of Water Supply and Demand by Khawar Naeem (17984062)

    Published 2023
    “…The solution approaches included the genetic algorithm (GA), particle swarm optimization (PSO), and the non-dominated sorting genetic algorithm (NSGA-II). …”
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  13. 13
    Inferential sensing techniques in industrial applications

    Inferential sensing techniques in industrial applications by Shakil,, Muhammad

    Published 0007
    “…System delays are obtained by approximating the model by a linear model. Genetic algorithm, which is a heuristic optimization technique, is used to ¯nd the system delays of the linear model, which are used in dynamical neural network model. …”
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  14. 14
    Data redundancy management for leaf-edges in connected environments

    Data redundancy management for leaf-edges in connected environments by Mansour, Elio

    Published 2022
    “…DRMF considers both static and mobile edge devices, and provides two algorithms for temporal and spatio-temporal redundancy detection. …”
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  15. 15
    Test time minimization for system-on-chip with test bus assignment and sizin

    Test time minimization for system-on-chip with test bus assignment and sizin by Harmanani, Haidar M.

    Published 2017
    “…In this paper, we propose a genetic algorithm to design test access architectures while investigating test bus sizing concurrently with assigning cores to test buses. …”
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  16. 16
    Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects

    Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects by Majdi Mansouri (16869885)

    Published 2021
    “…Thus, the data representation learning is the core stage of intelligent FDD techniques. Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”
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  17. 17
    Data Redundancy Management in Connected Environments

    Data Redundancy Management in Connected Environments by Mansour, Elio

    Published 2020
    “…We describe its modules, and clustering-based algorithms. Moreover, our proposal detects temporal, and spatial-temporal redundancies in order to consider both static and mobile devices/sensors. …”
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