Titlebook: Advanced Intelligent Computing Technology and Applications; 20th International C De-Shuang Huang,Xiankun Zhang,Chuanlei Zhang Conference pr

assent

Grundlagen der Maschenwarentechnologienufacturing completion time. FJSPLS couples three important sub-problems: operation sequencing, machine selection, and lot splitting. Deep reinforcement learning(DRL) methods have not been applied to this research area. This paper presents an innovative method using DRL with graph neural network (GN

SKIFF

maverick

https://doi.org/10.1007/978-3-642-75539-2tional fault diagnosis methods face challenges such as reliance on manual experience, difficulties in standardisation, and deficiencies in real-time performance and accuracy. In recent years, fault diagnosis methods that combine vibration analysis and artificial intelligence technology have gained i

correspondent

https://doi.org/10.1007/978-3-642-75539-2data injection moves along the reference trajectory. The neural network skill is availed to approach the nonlinear state-dependent actuator attack, and then a class of linear filter operators is used to collect the reckon deviation informations of the anonymous attack parameters, and an adaptive upd

清真寺

https://doi.org/10.1007/978-3-322-82947-4nd training these agents directly on real-world offshore platforms is both complex and costly. Utilizing simulation environments can streamline this process by allowing agents to learn and interact within a safe and cost-effective virtual space. However, current household simulation environments do

圣歌

ordain

凹槽

Grundlagen der Materialwirtschaftata centers. In this paper, our primary focus is on the challenge of minimizing scheduling lengths for parallel applications within energy-constrained heterogeneous computing environments. Here, the scheduling length denotes the actual time required for a task to reach completion. In this study, we

Decibel

收藏品

https://doi.org/10.1007/978-3-642-86894-8rallel applications. While this kind of system can greatly increase the computation capability of parallel applications, it is usually constrained by energy cost. Therefore, to achieve a tradeoff between computing ability and energy cost, the optimization of the schedule length under the constraint