SinoXivEngineering design optimization problems characterized by highly nonlinear, tightly constrained, and mixed-variable formulations remain challenging for conventional metaheuristic approaches, particula...
The large-scale deployment of Large Language Models (LLMs) is constrained by significant energy consumption and operational costs, with inference accounting for up to 90% of the total energy footprint...
In modern manufacturing, artificial intelligence and data analytics techniques are frequently used and developed for various industrial applications. The final purpose of the smart-factory problem is ...
Accurate identification of equilibrium points and bifurcation boundaries is fundamental to understanding the nonlinear lateral dynamics of rear-wheel-drive (RWD) vehicles, particularly during aggressi...
Among Time-Sensitive Networking (TSN) mechanisms, the Credit-Based Shaper (CBS) ensures bounded latency, while Frame Replication and Elimination for Reliability (FRER) enhances fault tolerance through...
Healthcare revenue cycle management (RCM) loses billions annually to claim denials, yet existing machine learning approaches treat billing as a prediction problem rather than a decision problemthey pr...
Agrovoltaic systems increasingly rely on Internet of Things (IoT)-enabled heterogeneous wireless sensor networks (HWSNs) for real-time environmental monitoring. However, energy inefficiency and redund...
This study introduces MAG, a lightweight intrusion detection system (IDS) that couples a single-hidden-layer multilayer perceptron (MLP) with the Adam optimizer and a Grey Wolf Optimizer (GWO) for hyp...
Background: The objective of Phase I/II dose-finding design is to determine the Optimal Biological Dose(OBD) that is acceptably safe and demonstrates sufficient anti-tumor activity by maximizing a pre...
This paper proposes a stochastic differential equation (SDE)-based global optimization method on matrix Lie groups, specifically addressing the challenge of local optima trapping in optimization over ...
