Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
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Abstract: Distribution network optimization is represented by non-convex power flow equations, where traditional convex relaxation methods may lead to inaccurate or infeasible solutions. To ...
Network planning has always been a bit reactive. Engineers analyze historical traffic data, build capacity models, and make infrastructure decisions based on what’s happened before. When congestion ...
In the field of multi-objective evolutionary optimization, prior studies have largely concentrated on the scalability of objective functions, with relatively less emphasis on the scalability of ...
Efficient traffic signal control is crucial for reducing congestion and improving vehicle flow in urban areas. This project implements a Genetic Algorithm (GA) to optimize traffic light timings using ...
ABSTRACT: Visual Sensor Networks (VSNs) focus on capturing data, extracting relevant information, and enabling communication. However, the presence of obstacles affects network efficiency, linking ...
College of Railway Locomotive and Rolling Stock, Hebei Vocational College of Rail Transportation, Shijiazhuang, China Introduction: This research focuses on optimizing the motion path of truss ...
In telecommunication applications, target impedance serves as a crucial benchmark for power distribution network (PDN) design. It ensures that the die operates within an acceptable level of rail ...