Computer-aided design(CAD)software continues to be a crucial tool in digital twin application and manufacturing,facilitating the design of various products.We present a novel CAD generation method,an agent that constr...Computer-aided design(CAD)software continues to be a crucial tool in digital twin application and manufacturing,facilitating the design of various products.We present a novel CAD generation method,an agent that constructs the CAD sequences containing the sketch-and-extrude modelling operations efficiently and with high quality.Starting from the sketch and extrusion operation sequences,we utilise the transformer encoder to encode them into different disentangled codebooks to represent their distribution properties while considering their correlations.Then,a combination of auto-regressive and non-autoregressive samplers is trained to sample the code for CAD sequence con-struction.Extensive experiments demonstrate that our model generates diverse and high-quality CAD models.We also show some cases of real digital twin applications and indicate that our generated model can be used as the data source for the digital twin platform,exhibiting designers'potential.展开更多
The electricity industry has witnessed increasing challenges in power system operation and rapid developments of artificial intelligence technologies in the last decades.In this context,studying the approach of securi...The electricity industry has witnessed increasing challenges in power system operation and rapid developments of artificial intelligence technologies in the last decades.In this context,studying the approach of security-constrained unit commitment(SCUC)deci-sionmaking with high adaptability and precision is of great importance.This paper proposes an improved da-tadriven deep learning(DL)approach,following the sample coding and Sequence to Sequence(Seq2Seq)technique.First,an encoding and decoding strategy is utilized for high-dimensional sample matrix dimension compression.A DL SCUC decision model based on a Seq2Seq network with gated recurrent units as neurons is then constructed,and the mapping between load and unit on/off scheme is established through massive data from historical scheduling.Numerical simulation results based on the IEEE 118-bus test system demonstrate the correctness and effectiveness of the proposed approach.展开更多
基金National Key Research and Development Program of China,Grant/Award Number:2022YFF0904303Beijing Science and Technology Planning Project,Grant/Award Number:Z221100006322003National Natural Science Foundation of China,Grant/Award Number:61932003。
文摘Computer-aided design(CAD)software continues to be a crucial tool in digital twin application and manufacturing,facilitating the design of various products.We present a novel CAD generation method,an agent that constructs the CAD sequences containing the sketch-and-extrude modelling operations efficiently and with high quality.Starting from the sketch and extrusion operation sequences,we utilise the transformer encoder to encode them into different disentangled codebooks to represent their distribution properties while considering their correlations.Then,a combination of auto-regressive and non-autoregressive samplers is trained to sample the code for CAD sequence con-struction.Extensive experiments demonstrate that our model generates diverse and high-quality CAD models.We also show some cases of real digital twin applications and indicate that our generated model can be used as the data source for the digital twin platform,exhibiting designers'potential.
基金supported by the National Natural Sci-ence Foundation of China(No.62233006).
文摘The electricity industry has witnessed increasing challenges in power system operation and rapid developments of artificial intelligence technologies in the last decades.In this context,studying the approach of security-constrained unit commitment(SCUC)deci-sionmaking with high adaptability and precision is of great importance.This paper proposes an improved da-tadriven deep learning(DL)approach,following the sample coding and Sequence to Sequence(Seq2Seq)technique.First,an encoding and decoding strategy is utilized for high-dimensional sample matrix dimension compression.A DL SCUC decision model based on a Seq2Seq network with gated recurrent units as neurons is then constructed,and the mapping between load and unit on/off scheme is established through massive data from historical scheduling.Numerical simulation results based on the IEEE 118-bus test system demonstrate the correctness and effectiveness of the proposed approach.
