Name
Title | ||
|---|---|---|
Parallel processing algorithm for railway signal fault diagnosis data based on cloud computing. |
Abstract | ||
|---|---|---|
To explore the data processing of high-speed railway fault signal diagnosis based on MapReduce algorithm, the partitioning strategy of data flow was improved, and Bias classification algorithm was used to model and classify data. In MapReduce parallelization process, the data partition matrix Tk was stored in line segmentation, the computing load was distributed in every node of cluster, and the time consumption of mobile data matrix and the consumption of partitioned matrix were calculated. Results show that the algorithm proposed could reduce the amount of computation in the execution process, greatly reduce the memory space consumption, and improve the counting speed in railway signal system. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.future.2018.05.038 | Future Generation Computer Systems |
Keywords | Field | DocType |
High speed railway,Cloud computing,Fault diagnosis,MapReduce | Data processing,Railway signal,Matrix (mathematics),Segmentation,Computer science,Algorithm,Real-time computing,Block matrix,Computation,Cloud computing,Data flow diagram | Journal |
Volume | ISSN | Citations |
88 | 0167-739X | 26 |
PageRank | References | Authors |
1.08 | 17 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Cao | 1 | 73 | 10.39 |
| Peng Li | 2 | 32 | 3.24 |
| Yuzhuo Zhang | 3 | 36 | 2.36 |