Predictive Model of Passengers Trans Metro Bandung Encouraging Smart Transportation
Abstract
Smart city can be accomplished by merging all components to be smart system. One of significant components is transportation. Everybody moves, everybody need to reach other place safely, efficiency, and comfortably. In order to get smart, we have to analyze the best way to improve capability. One of the best ways is to make predictive model that one may conceive strategies attracting passengers. Using Bayesian dan SVM as comparison will produce best fit model for Trans Metro Bandung passenger data. Better strategy is an emergence needed to produce Trans Metro Bandung better performance because the model predicted there will be no significant growth for Trans Metro Bandung passenger
Downloads
References
Faruqi, Umar Al. Survey Paper: Future Service in Industry 5.0. Published in Jurnal Sistem Cerdas 2019 Volume 02 No 01 ISSN : 2622-8254 Hal : 67 - 79
Hovsepyan, Aram,et al. Is Newer Always Better? The Case of Vulnerability Predicion Model. Published in Proceeding ESEM '16 Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement Article No. 26
Peng T, et al.Predictive Modeling of Drug Effects on Elecrocardiograms. Published in Journal Computers in Biology and Medicine 108 (2019) 332 344
Kempf, Michael. The Application of GIS and Satellite Imagery in Archaeological Land-Use Reconstruction: A Predictive Model? Published in Journal of Archaeological Science: Report
Schatz, Edward. When Capital Cities Move: The Political Geographical of Nation and State Building
Liu, Chunxia,et al. An Improved Grey Neural Network Model for Predicting Transportation Disruptions.Published in Journal Expert Systems with Application 45(2016) 331-340
Zhou, Huide, et al. An Approach of Model Predictive Control for Urban Transportation Network. Published in 13th IFAC Symposium on Large ScaleComplex Systems: Theory and ApplicationsJuly 7-10, 2013. Shanghai, China
I.I Sirmatel and N.Geroliminis. Dynamical Modeling and Predictive Control of Bus Transport System: A Hybrid Systems Approach.Published in IFAC PapersOnLine 50-1 (2017) 7499–7504
Zhou, Zhao, et al. A Congestion Eliminating Control Method for Large-Scale Urban Traffic Network. Published in 13th IFAC Symposium on Large ScaleComplex Systems: Theory and ApplicationsJuly 7-10, 2013. Shanghai, China
Khanmohamadi, Masoud, et al. A Security Vulnerability Analysis Model for Dangerous Goods Transportation by Rail – Case Study: Chlorine Transportation in Texas-Illnois. Published in Journal Safety Science 110 (2018) 230-241
Wu, Yizheng, et al. Modeling Health Equity in Active Transportation Planning. Published in Journal Transportation Research Part D 67 (2019) 528-540
Huang, Dengpeng,et al. Modelling of Serrated Chip Formation Processes Using the Stabilized Opimal Transportation Meshfree Method. Published in International Journal of Mechanical Science Volume 155, May 2019, Pages 323-333
Sona Taheri, Musa Mammadov, “Learning The Naive Bayes Classifier With Optimization Model”, Int. J. Appl. Math. Comput. Sci., 2013, Vol. 23, No. 4, 787–795, DOI: 10.2478/amcs-2013-0059
Feng, Yating,et al. Short Term Load Forecasting of Offshore Oil Field Microgrids Based on DA-SVM. Published in 10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, China
Dhamecha, Tejas Indulal,et al. Between-Subclass Piece –wise Linear Solutions in Large Scale Kernel SVM Learning. Published in Journal Pattern Recognition.
Chao, Luo, et al. A Novel Reconsructed Training-Set SVM with Roulette Cooperative Coevolution for Financial Time Series Classification. Published in Journal Experts Systems with Applications 123(2019)283-298
Alfa Shaleh, ‘Implementasi Metode Klasifikasi Naïve Bayes Dalam Memprediksi Besarnya Penggunaan Listrik Rumah Tangga’, Citec Journal Vol.2
Babajide O. Afeni, Thomas I. Aruleba1, Iyanuoluwa A. Oloyede, “Hypertension Prediction System Using Naive Bayes Classifier”, Journal of Advances in Mathematics and Computer Science, Previously known asBritish Journal of Mathematics & Computer Science