Hyperparameter settings for the optimization algorithms. by Ahmed M. Elshewey (21463867)

Descriptive analysis of the outcomes by the optimized LSTM using several optimization algorithms. by Ahmed M. Elshewey (21463867)

Performance of the bAD-PSO-Guided WOA algorithm compared with another algorithm. by Ahmed M. Elshewey (21463867)

Performance of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm. by Ahmed M. Elshewey (21463867)

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

Total computational cost of the proposed AD-PSO-Guided WOA-LSTM algorithm compared with another algorithm. by Ahmed M. Elshewey (21463867)

Adaptive dynamic algorithm for Australia rainfall. by Ahmed M. Elshewey (21463867)

The outcomes of the ANOVA results for the proposed AD-PSO-Guided WOA-LSTM algorithm for rainfall prediction. by Ahmed M. Elshewey (21463867)

Analysis plots of the obtained results using the proposed AD-PSO-Guided WOA LSTM algorithm. by Ahmed M. Elshewey (21463867)

The AD-PSO-Guided WOA LSTM framework. by 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. …”

Binary contingency table. by Lu Xiao (314030)

Hyperparameters of the LSTM Model. by 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. by 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. …”

Metrics for evaluating the performance of the proposed model. by Ahmed M. Elshewey (21463867)

Data_Sheet_1_Posiform planting: generating QUBO instances for benchmarking.pdf by Georg Hahn (12530469)

Secure MANET routing with blockchain-enhanced latent encoder coupled GANs and BEPO optimization by 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.…”

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

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

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

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)