The AD-PSO-Guided WOA LSTM framework. حسب Ahmed M. Elshewey (21463867)

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"

Hyperparameters of the LSTM Model. حسب Ahmed M. Elshewey (21463867)

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"

Prediction results of individual models. حسب Ahmed M. Elshewey (21463867)

"…The capacity to confront and overcome this obstacle is where machine learning and metaheuristic algorithms shine. This study introduces the Adaptive Dynamic Particle Swarm Optimization enhanced with the Guided Whale Optimization Algorithm (AD-PSO-Guided WOA) for rainfall prediction. …"

OneDataShare: Data Transfer Optimization as a Service - Talk حسب Tevfik Kosar (8399697)

OneDataShare: Data Transfer Optimization as a Service - Poster حسب Tevfik Kosar (8399697)

The Pseudo-Code of the IRBMO Algorithm. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"

IRBMO vs. meta-heuristic algorithms boxplot. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"

IRBMO vs. feature selection algorithm boxplot. حسب Chenyi Zhu (9383370)

"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. …"

Comparative analysis of DDcGAN-GSOM’s True Positive Rate, False Alarm Rate, and Specificity. حسب Nanavath Kiran Singh Nayak (22184565)

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Architecture of proposed system model. حسب Nanavath Kiran Singh Nayak (22184565)

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F1-score analysis of DDcGAN-GSOM with existing methods. حسب Nanavath Kiran Singh Nayak (22184565)

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Accuracy analysis of DDcGAN-GSOM with existing techniques. حسب Nanavath Kiran Singh Nayak (22184565)

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Network simulation of the proposed method. حسب Nanavath Kiran Singh Nayak (22184565)

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Simulation parameters of SDN network. حسب Nanavath Kiran Singh Nayak (22184565)

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Generator loss of the proposed method. حسب Nanavath Kiran Singh Nayak (22184565)

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Simulation parameters of DDcGAN. حسب Nanavath Kiran Singh Nayak (22184565)

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Throughput analysis of DDcGAN-GSOM with prevailing approaches. حسب Nanavath Kiran Singh Nayak (22184565)

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Performance metrics. حسب Nanavath Kiran Singh Nayak (22184565)

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Performance comparison of proposed system with state-of-the-art approaches. حسب Nanavath Kiran Singh Nayak (22184565)

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Schematic representation of univariate ensemble-based feature selection. حسب Nanavath Kiran Singh Nayak (22184565)

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