Optimizing the mobile cab rental system app using data mining techniques

Abstract

ABSTRACT newlineTransportation is necessary thing in our life. Everyone is not in the position to use the own car. Even though the person having own car, they are using rental car for long drive so that the rental car system is unavoidable. newlineThe traditional cab rental service is highly manual and here the customer register for the cab by phone or come directly to the office so it took a lot of time and resources and also related each process requires different resources causing the existing report data becomes difficult to manage. With the advent of GPS and increased Internet speeds, the mobile apps of car rental systems have emerged and completely replaced the traditional manual and online rental systems. In mobile app cab rental system, companies like Uber and Ola, the customers and drivers are connected with the pre determined fare and cab is reached within specified time. newlineThe cab rental mobile app is user friendly and satisfying the customers. However because of last minute booking cancellations of late the customer satisfaction service is getting affected. The problem is further aggrieved with the cab cancellations close to the trip start time, thereby causing passengers inconvenience. The problem could be tackled by accurately classifying the data of cab bookings using data mining techniques and design a predictive model there by forecasting the booking cancellations and take necessary steps so as to satisfy the customers. newlineThe problem is further aggrieved with the cab cancellations close to the trip start time, thereby causing passengers inconvenience. The problem could be tackled by accurately classifying the data of cab bookings using data mining techniques. newlineCab rental system using application based various optimization techniques has been analyzed. Comparing to the existing system our proposed modified particle swarm optimization technique showed enhanced accuracy result. newlineVIII newline