It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information technology.According to the current growing trend of the internet o...It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information technology.According to the current growing trend of the internet of things(IOT)in the manufacturing industry,aiming at the capacitor manufacturing plant,a multi-level architecture oriented to IOT-based manufacturing environment is established for a flexible flow-shop scheduling system.Next,according to multi-source manufacturing information driven in the manufacturing execution process,a scheduling optimization model based on the lot-streaming strategy is proposed under the framework.An improved distribution estimation algorithm is developed to obtain the optimal solution of the problem by balancing local search and global search.Finally,experiments are carried out and the results verify the feasibility and effectiveness of the proposed approach.展开更多
The paper follows possible specification of a control algorithm of a WS （water management system） during floods using the procedures of AI （artificial intelligence）. The issue of minimizing negative impacts of flo...The paper follows possible specification of a control algorithm of a WS （water management system） during floods using the procedures of AI （artificial intelligence）. The issue of minimizing negative impacts of floods represents influencing and controlling a dynamic process of the system where the main regulation elements are water reservoirs. Control of water outflow from reservoirs is implicitly based on the used model （titled BW） based on FR （fuzzy regulation）. Specification of a control algorithm means dealing with the issue of preparing a knowledge base for the process of tuning fuzzy regulators based on an I/O （input/output） matrix obtained by optimization of the target behaviour of WS. Partial results can be compared with the regulation outputs when specialized tuning was used for the fuzzy regulator of the control algorithm. Basic approaches follow from the narrow relation on BW model use to simulate floods, without any connection to real water management system. A generally introduced model allows description of an outflow dynamic system with stochastic inputs using submodels of robust regression in the outflow module. The submodels are constructed on data of historical FS （flood situations）.展开更多
基金supported by the National Natural Science Foundations of China(No. 51875171)
文摘It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information technology.According to the current growing trend of the internet of things(IOT)in the manufacturing industry,aiming at the capacitor manufacturing plant,a multi-level architecture oriented to IOT-based manufacturing environment is established for a flexible flow-shop scheduling system.Next,according to multi-source manufacturing information driven in the manufacturing execution process,a scheduling optimization model based on the lot-streaming strategy is proposed under the framework.An improved distribution estimation algorithm is developed to obtain the optimal solution of the problem by balancing local search and global search.Finally,experiments are carried out and the results verify the feasibility and effectiveness of the proposed approach.
文摘The paper follows possible specification of a control algorithm of a WS （water management system） during floods using the procedures of AI （artificial intelligence）. The issue of minimizing negative impacts of floods represents influencing and controlling a dynamic process of the system where the main regulation elements are water reservoirs. Control of water outflow from reservoirs is implicitly based on the used model （titled BW） based on FR （fuzzy regulation）. Specification of a control algorithm means dealing with the issue of preparing a knowledge base for the process of tuning fuzzy regulators based on an I/O （input/output） matrix obtained by optimization of the target behaviour of WS. Partial results can be compared with the regulation outputs when specialized tuning was used for the fuzzy regulator of the control algorithm. Basic approaches follow from the narrow relation on BW model use to simulate floods, without any connection to real water management system. A generally introduced model allows description of an outflow dynamic system with stochastic inputs using submodels of robust regression in the outflow module. The submodels are constructed on data of historical FS （flood situations）.
