Reciprocating compressors are widely used in the petroleum industry, and a small fault in reciprocating compressors may cause serious issues in operation. Monitoring and detecting potential faults help compressors to continue normal operation. This…
Considered the wireless sensor network clustering structure, a new big data collecting method based on compressive sensing is proposed. The collection process is as follows: in the cluster, the sink node sets the corresponding seed vector based on…
Time Series Forecasting (TSF) is essential to key domains, and the Transformer neural network has advanced the state-of-the-art on global, multi-horizon TSF benchmarks. The quadratic time and memory complexity of the Vanilla Transformer (VT) hinders…
Pipeline transportation is the most economic and reasonable transport means of petroleum and natural gas. Influenced by complex corrosion environment, it is challenging to detect anomalies accurately with precise boundaries. Inspired by the idea of…
A signal reconstruction method for memory-type transient electromagnetic detection systems based on empirical mode decomposition (EMD) was proposed in this study to tackle with the large volume of data saved by the electromagnetic flaw detector in…
Sparse triangular solves (SpTRSVs) are widely used in linear algebra domains, and several GPU-based SpTRSV algorithms have been developed. Synchronization-free SpTRSVs, due to their short preprocessing time and high performance, are currently the…
Matrix factorization on sparse matrices has been proven to be an effective approach for data mining and machine learning. However, the prior parallel implementations for matrix factorization fail to capture the internal social property embedded in…