Showing 121 - 140 results of 349 for search '(((( algorithm both function ) OR ( algorithm a function ))) OR ( algorithm cost function ))*', query time: 0.15s Refine Results
  1. 121

    Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms by Harmanani, H. M.

    Published 2007
    “…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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    article
  2. 122
  3. 123

    Spherical cavity-expansion forcing function in PRONTO 3D for application to penetration problems by Tabbara, Mazen R.

    Published 2017
    “…In this spirit, a forcing function which is derived from a spherical-cavity expansion analysis has been implemented in PRONTO 3D. …”
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    conferenceObject
  4. 124

    Online dynamic ensemble deep random vector functional link neural network for forecasting by Ruobin Gao (16003195)

    Published 2023
    “…<p>This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). …”
  5. 125
  6. 126

    Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks by Haris M. Khalid (17017743)

    Published 2023
    “…To address this issue, a median regression function (MRF)-based state estimation is presented in this paper. …”
  7. 127
  8. 128

    Efficient heuristic algorithms for influence propagation in social networks. (c2018) by Lamaa, Karine H.

    Published 2018
    “…Then we introduce the notion of an influence propagation function and use it to design an efficient algorithm across all types of networks. …”
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    masterThesis
  9. 129

    Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

    Published 2022
    “…For the purpose of predicting ground loss as a function of fruit zone, plant height, fruit production, slope, leaf loss, and blower damage, three ML models i.e., support vector regression (SVR), linear regression (LR), and random forest (RF)—were used. …”
  10. 130

    Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm by Ayman Khallel Al-Ani (17541447)

    Published 2023
    “…The proposed method is designed in such a way as to detect the number of loads that are present in a vehicle where functionality tasks are computed in the system. …”
  11. 131

    Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms by Zhongqiang Ma (13765801)

    Published 2023
    “…In addition, whether these algorithms have a search bias to the origin (i.e., the center of the search space) is investigated. …”
  12. 132
  13. 133

    An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection by Abu Zitar, Raed

    Published 2022
    “…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”
  14. 134

    Optimal multiobjective design of robust power system stabilizers using genetic algorithms by Abdel-Magid, Y.L.

    Published 2003
    “…The problem of robustly selecting the parameters of the power system stabilizers is converted to an optimization problem which is solved by a genetic algorithm with the eigenvalue-based multiobjective function. …”
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  15. 135

    Robust Coordinated Design of Excitation and TCSC-Based Stabilizers Using genetic algorithms by Abdel-Magid, Y. L.

    Published 2004
    “…The coordinated design problem of robust excitation and TCSC-based controllers over a wide range of loading conditions and system configurations is formulated as an optimization problem with an eigenvalue-based objective function. …”
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    article
  16. 136

    Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

    Published 2022
    “…They have been exposed to cyberattacks because of their integration with an insecure network. In the event of a violation in internet security, an attacker was able to interfere with the system's functions, which might result in catastrophic consequences. …”
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  17. 137

    Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

    Published 2022
    “…The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
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  18. 138

    Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System by Abualigah, Laith

    Published 2023
    “…Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability. This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. …”
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  19. 139

    Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact las... by Masurkar, Faeez

    Published 2020
    “…The functioning of the algorithm was successfully tested by carrying out extensive experiments on a real rail track in the presence of different types of surface and sub-surface defects on its head and web. …”
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  20. 140

    Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

    Published 2022
    “…The main objective of this paper is to apply GOA to estimate the optimal parameters of the Gaussian membership function in an IT2-FLS. The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. …”