Please use this identifier to cite or link to this item:
|Title:||Prediction of the toilet’s health and manpower deployment orchestration||Authors:||Quek, Eric Yuan Zhou||Keywords:||Science::Physics||Issue Date:||2020||Publisher:||Nanyang Technological University||Abstract:||Predictive Analysis is widely used today: From weather forecasts to pandemic modelling to prediction of stock market trends. There are many approaches in Predictive Analysis, and every single set of data uses a variety of different approaches to model and predict future trends. This project aims to employ Predictive Analysis to optimise cleaners’ cleaning schedules in Best Mall by creating a mathematical model. The collected data will be processed and analysed, using various techniques such as correlation matrix and Factor Analysis to create a Cleanliness Index as an indication of cleanliness in the toilets of Best Mall. The models used in this project are the ARIMA model and the TBATS model. Results suggest that cleanliness, being such a complex and intangible variable, may require a more complex model. The ARIMA model, being a simple model, was not a suitable model for the data. But the TBATS model, incorporating most aspects of ARIMA in it, may be superior to ARIMA.||URI:||https://hdl.handle.net/10356/139963||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SPMS Student Reports (FYP/IA/PA/PI)|
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.