Name
Abstract | ||
|---|---|---|
This paper focuses on macro prediction of corporate equipment maintenance expenditure, adopts ARMA to establish the model for historical data of corporate equipment maintenance expenditure and makes demand analysis and prediction so as to provide a scientific basis for decision makers in equipment maintenance expenditure prediction, and they can control the overall budget for equipment maintenance. Based on analysis and compassion of actual model calculation results, the paper reaches the conclusion that ARMA model enjoys an advantage over traditional predicting models in corporate equipment maintenance prediction. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/SOLI.2012.6273564 | Service Operations and Logistics, and Informatics |
Keywords | DocType | ISBN |
autoregressive moving average processes,maintenance engineering,production equipment,arma model,corporate equipment maintenance expenditure prediction,decision makers,demand analysis,historical data,macroprediction,overall budget,corporate equipment maintenance expenditure,econometric analysis,prediction,random sequence,time frequency analysis,predictive models,noise,data models | Conference | 978-1-4673-2400-7 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minhui Lv | 1 | 0 | 0.68 |
| Hongxia Zhao | 2 | 1 | 1.02 |