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Showing 1 - 20 results of 521 for search '(( elements method algorithm ) OR ((( tests using algorithm ) OR ( sensor using algorithm ))))', query time: 0.15s Refine Results
  1. 1

    Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

    Published 2024
    “…This paper presents a novel hybrid optimization method to solve the resource allocation problem for multi-target multi-sensor tracking of drones. This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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  2. 2

    Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

    Published 2005
    “…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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    Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer by M. Premkumar (12757280)

    Published 2023
    “…Based on the average Friedman’s ranking test values, the proposed algorithm stands first with 1.82 for numerical and real-world scheduling problems. …”
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    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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    An incremental approach for test scheduling and synthesis using genetic algorithms by Harmanani, H.

    Published 2017
    “…This paper presents a new and an efficient method for concurrent BIST synthesis and test scheduling. This method maximizes concurrent testing of modules while performing the allocation of functional units, test registers, and multiplexers. …”
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    A hybrid distributed test generation method using deterministic and genetic algorithms by Harmanani, H.

    Published 2017
    “…The algorithm is parallelized based on a cluster of workstations using the message passing interface (MPI) library. …”
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    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

    Published 2022
    “…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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    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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    Empirical comparison of regression test selection algorithms by Mansour, Nashat

    Published 2001
    “…The empirical results show that the five algorithms can be used for different requirements of regression testing. …”
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    Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

    Published 2018
    “…We formulate the testing problem as an optimization problem and use a simulated annealing (SA) metaheuristic algorithm to generate test cases as sequences of events while keeping the test suite size reasonable. …”
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    Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods by Sivakavi Naga Venkata Bramareswara Rao (15944992)

    Published 2022
    “…The effectiveness of these optimization algorithms is verified in terms of training, test, validation, and error analysis. …”
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    Optimization of Piezoelectric Sensor-Actuator for Plate Vibration Control Using Evolutionary Computation: Modeling, Simulation and Experimentation by Asan G. A. Muthalif (16888818)

    Published 2021
    “…The Optimal location of the collocated sensor-actuator, as well as PID controller gains, are determined using Ant Colony Optimization (ACO) technique, then compared with the Genetic Algorithm (GA) and enumerative method (EM). …”