Data Mining Scheduled Phase Sequence: A Graphic Developing Fast-Food Formation Records - Vijayasree, G; Periasamy, Pon (International Journal of Computer Sciences and Engineering, 2025)
Given the widespread use of modern information technology, a substantial number of time arrangement might be gathered amid ordinary business operations. We use a fast-sustenance restaurant establishment as a case to represent how information mining can be connected to such time series, and help the establishment harvest the advantages of such an effort. Time arrangement information mining at both the store level and corporate level are discussed. Box–Jenkins regular ARIMA models are utilized to investigate and gauge the time series. Instead of a customary manual approach of Box–Jenkins modelling, a programmed time arrangement displaying strategy is utilized to investigate a substantial number of exceedingly occasional time series. In addition, a programmed anomaly discovery and alteration strategy is utilized for both model estimation and forecasting. The change in gauge execution due to anomaly alteration is demonstrated. Alteration of gauges based on stored chronicled gauges of like occasions is moreover discussed. Anomaly discovery moreover leads to information that can be utilized not just for better stock administration and planning, but moreover to recognize potential deals opportunities. To represent the feasibility and straightforwardness of the above programmed strategies for time arrangement information mining, the SCA measurable framework is utilized to per structure the related analysis.