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.…"

One advantage of our algorithm is that it is not binary in nature. حسب Yong Kuk Kim (13955214)

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)

الموضوعات:

CSTP-MAC algorithm backoff time-slots vs IEEE 802.15.4 binary backoff exponential algorithm backoff time-slots. حسب Innocent Uzougbo Onwuegbuzie (9243166)

Analysis and design of algorithms for the manufacturing process of integrated circuits حسب Sonia Fleytas (16856403)

"…This process can be modeled as a combinatorial optimization problem where the objective is to reduce the total distance the robotic arm must travel to pick up each chip and place it in its corresponding position within the support structure. …"

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

Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things حسب Ashok Kumar K (21441108)

"…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …"

Optimal Timings Codebook.xlsx حسب Emma Spillane (11249121)

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data حسب Changhun Kim (682542)

"…However, ToxCast assays differ in the amount of data and degree of class imbalance (CI). Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"

Proposed Algorithm. حسب Hend Bayoumi (22693738)

"…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Optimal Time Intervals of Breech Births Dataset حسب Emma Spillane (11249121)

Parameter settings of the comparison algorithms. حسب Ying Li (38224)

"…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …"

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. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging حسب D. Andrew Brown (6584837)

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

الموضوعات:

Comparisons between ADAM and NADAM optimizers. حسب Hend Bayoumi (22693738)

"…EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …"

Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF حسب Maya Khatun (7437011)

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. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

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. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"

An illustration and comparison of the fitness convergence curves for the Large-scale dataset (WaveformEW), medium-scale dataset (Zoo dataset), and Small-scale (Wine dataset) using... حسب Olaide N. Oyelade (14047002)

الموضوعات: