## 4 Discussion  
Today, mail or mail distribution continues to develop as an important business area in both private and official sectors. These distribution sectors develop many application methods to increase customer satisfaction and business quality. In postal or package delivery, fast delivery in terms of customer satisfaction and minimum distribution cost in the industry is desirable. In calculating the forecast data, ML algorithms, which are very powerful forecast calculators developed using the statistical database, were used. By choosing RF, GB, \(k\)NN, and NN algorithms from ML algorithms, the mail or mail delivery time and the average energy cost of a package were estimated. By using 6269 data in these algorithms, 80% of this data was used in the training phase, and 20% of all data was used in the testing phase. These algorithms estimated 1253 data and compared them with accurate data. The estimation data in terms of time and energy cost of e-scooter implementation of these algorithms are compared and shared in Figure 8. The estimation data of the time data of the e-scooter vehicles of the RF, GB, NN, and KNN algorithms show relative values. In terms of energy cost, the estimation data of ML algorithms show a linear trend, although they are partially close to each other. The prediction data of these algorithms were validated according to the performance criteria. Therefore, the GB algorithm exhibits the best performance among the ML algorithms run for both output parameters. It has been emphasized in other studies that the use of e-scooters in the package and mail distribution process is more advantageous in terms of time and cost compared to other distribution tools. [PERSON] et al. calculated that the e-scooter vehicles used by the PTT unit cost 0.51 TL (including energy, personnel wages, maintenance, etc.). Likewise, this study emphasized that the energy cost required for package or mail distribution with an e-scooter is meagre compared to other distribution vehicles (combivan, truck, motorcycle, minivan, etc.) [45]. In this study, the energy cost of the e-scooter vehicle used to distribute a package or mail was calculated as 0.125 TL on average. According to the test data, the energy cost of the e-scooter vehicle was calculated as 0.121 TL, 0.120 TL, 0.124 TL, and 0.134 TL for the RF, GB, \(k\)NN, and NN algorithms, respectively. Among these algorithms, the GB algorithm provides the lowest energy cost. Although the energy cost of the e-scooter varies depending on many factors such as environmental, geographical, and driver, it is understood that it is advantageous compared to other distribution vehicles. It has been observed that the e-scooter application in package or mail distribution has many advantages in terms of time. The use of e-scooters is advantageous, especially for  
Figure 8: The comparison between actual and estimation data of ML algorithms: (**a**) delivery time; (**b**) delivery energy cost variable. regions with dense populations and settlements, considering many factors such as parking, traffic, and free movement in side streets. However, use of e-scooter should be short in terms of distance, and the responsibilities of the drivers for a particular area should be determined. It has been determined that the short-distance e-scooter application is 20.21% more advantageous than other vehicles (combivan, truck, motorcycle, minivan, etc.) in package or mail distribution. According to the test data, the average package or delivery times with the e-scooter vehicle were calculated as 26.28, 25.80, 26.16, and 25.91 for the RF, GB, \(k\)NN, and NN algorithms, respectively. For all study data, the average delivery time with the e-scooter was 25.98 min. The GB algorithm provided the closest value to this time. According to the GB algorithm, the delivery time obtained by considering different input parameters is 25.80 min on average. This period is valid for an average of 2.3 packages. The time required to deliver a package or mail with the e-scooter is approximately 11.21 min.