Read more about Deep reinforcement learning could redefine insulin delivery for diabetes patients on Devdiscourse ...

The study underscores the potential of bio-inspired algorithms ... swarm optimization (PSO) to enhance the efficiency and effectiveness of cybersecurity solutions in resource-constrained IoT ...

potentially revealing previously undetected biological signals to improve cancer classification. Methods: We implemented a quantum-classical hybrid algorithm that frames feature selection as a ...

Performance Metrics of the Model: The effectiveness of AI-based hardware Trojan (HT) detection models can be assessed by a range of classification metrics, including accuracy, precision, recall (true ...

After obtaining feasible solutions from classical optimization, MicroAlgo CBQOA employs Continuous-Time Quantum Walk (CTQW) to search the solution space. CTQW is a random walk model in quantum ...

By utilizing the region partitioning and constraint filtering techniques, the actual number of simulations in the optimization can be significantly reduced. The experimental results demonstrate that ...

To address these challenges, we propose a fairness-aware interval constrained many-objective optimization method for joint vehicle ... level interval constrained many-objective evolutionary algorithm ...

Pillo and Grippo in [1-3] proposed a class of augmented Lagrange function methods which have nice equivalence between the unconstrained optimization and the primal constrained problem and get good ...

platform for evolutionary multi-objective optimization ... algorithm SADE-AMSS, add three expensive multi-objective evolutionary algorithms DISK, DISKplus, and DRL-SAEA, add a sparse multi-objective ...