To reduce engine pollutant emissions,an emission modeling and optimization scheme based on a hybrid artificial intelligence scheme is proposed in this study to reduce pollutant emissions of methanol/diesel dual-fuel e...To reduce engine pollutant emissions,an emission modeling and optimization scheme based on a hybrid artificial intelligence scheme is proposed in this study to reduce pollutant emissions of methanol/diesel dual-fuel engines under low load.Firstly,a data cleaning method based on isolated forest and correlation analysis is designed to improve the stability of the system.Secondly,a hybrid emission prediction model based on improved Transformer(ITransformer)and Bidirectional Gated Recurrent Unit(BiGRU)is built to obtain an accurate mathematical model between control parameters and emissions.Finally,based on the obtained mathematical model,the 3rd Non-dominated Sorting Genetic Algorithm(NGSA-Ⅲ)is used to adjust and optimize the control parameters.Using engine bench test data to evaluate the proposed hybrid emission prediction model,the R^(2) of CO,HC,and NO_(x) prediction is 0.9969,0.9973,and 0.9982,respectively,which is higher than the accuracy of the seven existing modeling methods.Compared with the unoptimized MESR46,the CO,HC,and NO_(x) emissions of the optimized scheme are reduced by at least 45.17%,15.30%,and 17.32%respectively,which can significantly reduce the CO,HC,and NO_(x) emissions,and comparison and analysis with the most advanced optimization technologies show a competitive optimization effect.展开更多
In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in inte...In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in intelligent manufacturing job shop environment was studied. The dual-resource integrated scheduling model of AGV and machine was established by comprehensively considering constraints of machines, workpieces and AGVs. The bidirectional single path fixed guidance system based on topological map was determined, and the AGV transportation task model was defined. The improved A* path optimization algorithm was used to determine the optimal path, and the path conflict elimination mechanism was described. The improved NSGA-Ⅱ algorithm was used to determine the machining workpiece sequence, and the competition mechanism was introduced to allocate AGV transportation tasks. The proposed model and method were verified by a workshop production example, the results showed that the dual resource integrated scheduling strategy of AGV and machine is effective.展开更多
Air route network is the carrier of air traffic flow,and traffic assignment is a method to verify the rationality of air route network structure.Therefore,air route network generation based on traffic assignment has b...Air route network is the carrier of air traffic flow,and traffic assignment is a method to verify the rationality of air route network structure.Therefore,air route network generation based on traffic assignment has been becoming the research focus of airspace programming technology.Based on link prediction technology and optimization theory,a bi-level programming model is established in the paper.The model includes an upper level of air route network generation model and a lower level of traffic assignment model.The air route network structure generation incorporates network topology generation algorithm based on link prediction technology and optimal path search algorithm based on preference,and the traffic assignment adopts NSGA-Ⅲalgorithm.Based on the Python platform NetworkX complex network analysis library,a network of 57 airports,383 nodes,and 635 segments within China Airspace Beijing and Shanghai Flight Information Regions and 187975 sorties of traffic are used to simulate the bilevel model.Compared with the existing air route network,the proposed air route network can decrease the cost by 50.624%,lower the flight conflict coefficient by 33.564%,and reduce dynamic non-linear coefficient by 7.830%.展开更多
基金supported by the National Natural Science Foundation of China(52066003)the Guangxi Key R&D Program(2022GXNSFFA035029).
文摘To reduce engine pollutant emissions,an emission modeling and optimization scheme based on a hybrid artificial intelligence scheme is proposed in this study to reduce pollutant emissions of methanol/diesel dual-fuel engines under low load.Firstly,a data cleaning method based on isolated forest and correlation analysis is designed to improve the stability of the system.Secondly,a hybrid emission prediction model based on improved Transformer(ITransformer)and Bidirectional Gated Recurrent Unit(BiGRU)is built to obtain an accurate mathematical model between control parameters and emissions.Finally,based on the obtained mathematical model,the 3rd Non-dominated Sorting Genetic Algorithm(NGSA-Ⅲ)is used to adjust and optimize the control parameters.Using engine bench test data to evaluate the proposed hybrid emission prediction model,the R^(2) of CO,HC,and NO_(x) prediction is 0.9969,0.9973,and 0.9982,respectively,which is higher than the accuracy of the seven existing modeling methods.Compared with the unoptimized MESR46,the CO,HC,and NO_(x) emissions of the optimized scheme are reduced by at least 45.17%,15.30%,and 17.32%respectively,which can significantly reduce the CO,HC,and NO_(x) emissions,and comparison and analysis with the most advanced optimization technologies show a competitive optimization effect.
基金Project(BK20201162)supported by the General Program of Natural Science Foundation of Jiangsu Province,ChinaProject(JC2019126)supported by the Science and Technology Plan Fundamental Scientific Research Funding Project of Nantong,China+1 种基金Project(CE20205045)supported by the Changzhou Science and Technology Support Plan(Social Development),ChinaProject(51875171)supported by the National Nature Science Foundation of China。
文摘In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in intelligent manufacturing job shop environment was studied. The dual-resource integrated scheduling model of AGV and machine was established by comprehensively considering constraints of machines, workpieces and AGVs. The bidirectional single path fixed guidance system based on topological map was determined, and the AGV transportation task model was defined. The improved A* path optimization algorithm was used to determine the optimal path, and the path conflict elimination mechanism was described. The improved NSGA-Ⅱ algorithm was used to determine the machining workpiece sequence, and the competition mechanism was introduced to allocate AGV transportation tasks. The proposed model and method were verified by a workshop production example, the results showed that the dual resource integrated scheduling strategy of AGV and machine is effective.
文摘Air route network is the carrier of air traffic flow,and traffic assignment is a method to verify the rationality of air route network structure.Therefore,air route network generation based on traffic assignment has been becoming the research focus of airspace programming technology.Based on link prediction technology and optimization theory,a bi-level programming model is established in the paper.The model includes an upper level of air route network generation model and a lower level of traffic assignment model.The air route network structure generation incorporates network topology generation algorithm based on link prediction technology and optimal path search algorithm based on preference,and the traffic assignment adopts NSGA-Ⅲalgorithm.Based on the Python platform NetworkX complex network analysis library,a network of 57 airports,383 nodes,and 635 segments within China Airspace Beijing and Shanghai Flight Information Regions and 187975 sorties of traffic are used to simulate the bilevel model.Compared with the existing air route network,the proposed air route network can decrease the cost by 50.624%,lower the flight conflict coefficient by 33.564%,and reduce dynamic non-linear coefficient by 7.830%.
