چكيده به لاتين
The increasing number of Tehran's population and the consequent production of various types of waste, the type of systems used, is very important for the collection of waste generated. The importance of this is because a little improvement in waste collection and transfer operations can have a significant effect on reducing the time lag generated in the waste transportation system. Therefore, in this research, the use of data mining in waste management management at the stations of collection and transportation of waste in Tehran has been addressed. The purpose of this research, which is field-oriented and applied, is to identify the effective factors and their degree of importance on the predicted delay time during the drainage and reloading process of trailer trailers inside the intermediate waste station using the application of the data mining technique. Using the CRISP-DM methodology, the computations were performed using IBM SPSS Modeler 12 software. The findings show that in the investigation of information on waste transportation, factors such as the time of garbage delivery by mechanized vehicles to intermediate transmissions, seasons, professional records of drivers, their age group, records of violations and accidents, the age of car transportation , The amount of repairs and the degree of driver education. The results of this study indicate that the main factor of the indicators identified in the delay time was the arrival of waste by smaller vehicles to the intermediate waste transmission station. After all the calculations of the model, it was determined that factors such as the seasons of the year affect the generation of these types of delays. Compared to the seasons of the year, the results show a better forecast for spring load than the other seasons. Based on the results, the best loading time is to reduce the delay time inside the transfer station during the spring and at the time of the day.
Key Words: Data Mining- Transportation- Waste Management
