Titlebook: Intelligent Networked Things; The 6th Conference o Lin Zhang,Wensheng Yu,Yongkui Liu Conference proceedings 2024 The Editor(s) (if applicab

AGATE

Alpha-Cells

kindred

A Multi-scale Feature Fusion Method for Demand Forecasting in Supply Chain Managementing its inherent heterogeneity and failing to extract valuable features. In response, we introduce a novel approach called Multi-Scale Feature Fusion Approach with Attention Mechanisms (MO-MSA) for supply chain product demand forecasting. MO-MSA leverages the distinctive characteristics of historica

繁荣地区

步履蹒跚

Intelligent Monitoring Method for Gear Grinding Machine Spindle Based on Multi-source Information Fuare widespread anomalies in grinding processes that affect tooth surface accuracy and load-bearing capacity due to unreasonable process parameters, grinding wheel threshing, and other reasons, such as tooth surface burns, off center grinding, and vibration lines. In response to the problems of fault

粘土

Research on Improving ResNet18 for Classifying Complex Images Based on Attention Mechanism cluttered backgrounds and unclear feature is limited. This article focused on the relatively shallow residual network ResNet18, and added attention mechanism to improve the network’s performance in learning and classifying complex images. Compared to others who added attention mechanisms to the mai

puzzle

A Framework for Automated Generation of Transmission Processes Based on Kinetic Knowledge Mappingnd inflexible manufacturing process make it difficult to balance the production efficiency and personalized demand of transmission customization. This paper proposes a transmission process automation generating framework based on the combination of dynamic and static knowledge mapping, firstly, we c

荒唐

Intelligent Optimization Methods for Unmanned Cluster Delivery Support Task Allocationtion issues of unmanned platforms, aiming to improve the military’s material support capability during wartime. Firstly, a VRPTW model based on unmanned platform delivery was constructed, considering the limitations of the unmanned platform’s endurance mileage, rated load capacity, and intermediate

Aspirin

Knowledge-Specific Reinforcement Learning for Job-Shop Scheduling with Dynamic Processing States in een applied to the job-shop scheduling problem in disassembly factories. However, dynamic factors and unbalanced waste type distributions might influence the machine utilization rate. We proposed a reinforcement learning-based disassembly job-shop scheduling method to optimize the dynamic scheduling

DEFER