It is important and difficult to control the temperature of mass concrete structure during high arch dam construction.A new method with decision support system is presented for temperature control and crack prevention...It is important and difficult to control the temperature of mass concrete structure during high arch dam construction.A new method with decision support system is presented for temperature control and crack prevention.It is a database system with functions of data storage,information inquiry,data analysis,early warning and resource sharing.Monitoring information during construction can be digitized via this system,and the intelligent analysis and dynamic control of concrete temperature can be conducted.This method has been applied in the construction of the Dagangshan Arch Dam in China and has proven to be very convenient.Based on the decision support of this system and the dynamic adjustment of construction measures,the concrete temperature of this project is well-controlled.展开更多
A data-driven method for arrival pattern recognition and prediction is proposed to provide air traffic controllers(ATCOs)with decision support. For arrival pattern recognition,a clustering-based method is proposed to ...A data-driven method for arrival pattern recognition and prediction is proposed to provide air traffic controllers(ATCOs)with decision support. For arrival pattern recognition,a clustering-based method is proposed to cluster arrival patterns by control intentions. For arrival pattern prediction,two predictors are trained to estimate the most possible command issued by the ATCOs in a particular traffic situation. Training the arrival pattern predictor could be regarded as building an ATCOs simulator. The simulator can assign an appropriate arrival pattern for each arrival aircraft,just like real ATCOs do. Therefore,the simulator is considered to be able to provide effective advice for part of the work of ATCOs. Finally,a case study is carried out and demonstrates that the convolutional neural network(CNN)-based predictor performs better than the radom forest(RF)-based one.展开更多
基金Supported by the National Natural Science Foundation of China(No.50909078)the National Basic Research Program of China("973"Program,No.2013CB035900)
文摘It is important and difficult to control the temperature of mass concrete structure during high arch dam construction.A new method with decision support system is presented for temperature control and crack prevention.It is a database system with functions of data storage,information inquiry,data analysis,early warning and resource sharing.Monitoring information during construction can be digitized via this system,and the intelligent analysis and dynamic control of concrete temperature can be conducted.This method has been applied in the construction of the Dagangshan Arch Dam in China and has proven to be very convenient.Based on the decision support of this system and the dynamic adjustment of construction measures,the concrete temperature of this project is well-controlled.
基金supported by the National Natural Science Foundation of China (Nos. U1933117,61773202,52072174)。
文摘A data-driven method for arrival pattern recognition and prediction is proposed to provide air traffic controllers(ATCOs)with decision support. For arrival pattern recognition,a clustering-based method is proposed to cluster arrival patterns by control intentions. For arrival pattern prediction,two predictors are trained to estimate the most possible command issued by the ATCOs in a particular traffic situation. Training the arrival pattern predictor could be regarded as building an ATCOs simulator. The simulator can assign an appropriate arrival pattern for each arrival aircraft,just like real ATCOs do. Therefore,the simulator is considered to be able to provide effective advice for part of the work of ATCOs. Finally,a case study is carried out and demonstrates that the convolutional neural network(CNN)-based predictor performs better than the radom forest(RF)-based one.
