Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب Se-Hee Jo (20554623)

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Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. حسب Benjamin Gallois (10131683)

Schematic of iteration process of IDE-IIGA. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

Datasets and their properties. حسب Olaide N. Oyelade (14047002)

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Parameter settings. حسب Olaide N. Oyelade (14047002)

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Fig 2 - حسب Olaide N. Oyelade (14047002)

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Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization حسب Sandeep Jagonda Patil (22048337)

"…The performance of the proposed LEGAN-BEPO-BCMANET technique attains 29.786%, 19.25%, 22.93%, 27.21%, 31.02%, 26.91%, and 25.61% greater throughput, compared to existing methods like Blockchain-based BATMAN protocol utilizing MANET with an ensemble algorithm (BATMAN-MANET), Block chain-based trusted distributed routing scheme with optimized dropout ensemble extreme learning neural network in MANET (DEELNN-MANET), A secured trusted routing utilizing structure of a new directed acyclic graph-blockchain in MANET internet of things environment (DAG-MANET), An Optimized Link State Routing Protocol with Blockchain Framework for Efficient Video-Packet Transmission and Security over MANET (OLSRP-MANET), Auto-metric Graph Neural Network based Blockchain Technology for Protected Dynamic Optimum Routing in MANET (AGNN-MANET) and Data security-based routing in MANETs under key management process (DSR-MANET) respectively.…"

Feature selection convergence time comparison of various binary metaheuristic algorithms. حسب Amal H. Alharbi (21755906)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. حسب Olaide N. Oyelade (14047002)

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The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms. حسب Ahmed M. Elshewey (21463867)

DE algorithm flow. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

Test results of different algorithms. حسب Ling Zhao (111365)

"…In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. …"

The data processing and analysis pipeline. حسب Xin Zhang (35492)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

The result of the accuracy of tested algorithms. حسب Nebojsa Bacanin (13932723)

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Feature selection ratio results for tested algorithms. حسب Nebojsa Bacanin (13932723)

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Best fitness value results for tested algorithms. حسب Nebojsa Bacanin (13932723)

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Mean fitness value results for tested algorithms. حسب Nebojsa Bacanin (13932723)

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Standard deviation of fitness value results for tested algorithms. حسب Nebojsa Bacanin (13932723)

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An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. حسب Olaide N. Oyelade (14047002)

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