Showing 141 - 160 results of 450 for search '(( element rf algorithm ) OR ((( data processing algorithm ) OR ( based finding algorithm ))))*', query time: 0.12s Refine Results
  1. 141
  2. 142

    A time-domain algorithm for the analysis of second-harmonicgeneration in nonlinear optical structures by Al-Sunaidi, M. A.

    Published 2000
    “…A time-domain simulator of integrated optical structures containing second-order nonlinearities is presented. The simulation algorithm is based on nonlinear wave equations representing the propagating fields and is solved using the finite-difference time-domain method. …”
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  3. 143

    A time-domain algorithm for the analysis of second-harmonicgeneration in nonlinear optical structures by Alsunaidi, M.A.

    Published 2000
    “…A time-domain simulator of integrated optical structures containing second-order nonlinearities is presented. The simulation algorithm is based on nonlinear wave equations representing the propagating fields and is solved using the finite-difference time-domain method. …”
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  4. 144

    UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks by Ebrahimi, Dariush

    Published 2018
    “…Among the emerging markets, Internet of Things (IoT) use cases are standing out with the proliferation of a wide range of sensors that can be configured to continuously monitor and transmit data for intelligent processing and decision making. …”
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  5. 145

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

    Published 2022
    “…An efficient optimization method is needed to address complicated problems and find optimal solutions. The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
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  6. 146

    Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

    Published 2022
    “…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …”
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  9. 149

    A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption by Azadeh, Ali

    Published 2019
    “…Design/methodology/approach In the proposed approach, the parameter tuning process is performed on all parameters of genetic algorithm (GA), and the finest coefficients with minimum errors are identified. …”
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  10. 150

    Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem by Haraty, Ramzi A.

    Published 2018
    “…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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  11. 151

    GIJA:Enhanced geyser‐inspired Jaya algorithm for task scheduling optimization in cloud computing by Abualigah, Laith

    Published 2024
    “…The motivation for this research stems from the increasing demand for efficient resource utilization and task management in cloud computing, driven by the proliferation of Internet of Things (IoT) devices and the growing reliance on cloud‐based services. Traditional task scheduling algorithms often face challenges in handling dynamic workloads, heterogeneous resources, and varying performance objectives, necessitating innovative optimization techniques. …”
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  12. 152

    Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands by Peng, Wang

    Published 2020
    “…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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  13. 153
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    Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

    Published 2020
    “…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”
  16. 156

    KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

    Published 2021
    “…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …”
  17. 157

    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
  18. 158

    A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group by Iqtadar Hussain (14147850)

    Published 2023
    “…The presented algorithm is mainly based on the Shannon idea of substitution–permutation network where the process of substitution is performed by the proposed S<sub>8</sub> semifield substitution boxes and permutation operation is performed by the binary cyclic shift of substitution box transformed data. …”
  19. 159

    Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

    Published 2022
    “…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. However, these schemes have limitations like slow convergence and longer training time. …”
  20. 160

    Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare by Haraty, Ramzi A.

    Published 2007
    “…Since even segmenting the log into clusters may not solve the problem, as clusters/segments may grow to be humongous in size, this is in case of high data/transaction dependency, we suggest a method for segmenting the log into clusters and its sub-clusters; i.e, segmenting the cluster; based on exact data dependency [12], into sub-clusters; based on two different criteria: number of data items or space occupied. …”
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