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A Comparative Study of Advanced Machine Learning and Deep Learning Models for Municipal Solid Waste Forecasting: A Case Study of Surat, India

DOI : 10.5614/j.eng.technol.sci.2026.58.5.1
Abhijit R. Rathod (1), Vinodkumar M. Patel (2)
(1) Gujarat Technological University, GTU Campus, Nr. Visat Three Road, Visat-Gandhinagar Road, Chandkheda, Ahmedabad-382424, Gujarat, , India ,
(2) Shantilal Shah Engineering College, New Sidsar Campus, Vartej, Sidsar, Bhavnagar - 364060, Gujarat, India
613-629
Abstract : 103
PDF : 11
DOI: https://doi.org/10.5614/j.eng.technol.sci.2026.58.5.1

Adaptive Ensemble Learning for Enhancing Building Energy Consumption Prediction: Insights from COVID-19 Pandemic Energy Consumption Dynamics

DOI : 10.5614/j.eng.technol.sci.2025.57.2.2
Putu Handre Kertha Utama (1), Edi Leksono (2), Irsyad Nashirul Haq (3), Rachmadi Indrapraja (4), Rezky Mahesa Nanda (5), Koko Friansa (6), Reza Fauzi Iskandar (7), Justin Pradipta (8)
(1) Engineering Physics, Institut Teknologi Bandung, Indonesia ,
(2) Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, Indonesia ,
(3) Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, Indonesia ,
(4) Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, Indonesia ,
(5) Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, Indonesia ,
(6) Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, Indonesia ,
(7) Engineering Physics, School of Industrial Engineering, Telkom University, Jalan Telekomunikasi No.1, Bandung 40257, Indonesia ,
(8) Engineering Physics, Faculty of Industrial Technology, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, Indonesia
161-174
Abstract : 1680
PDF : 584
DOI: https://doi.org/10.5614/j.eng.technol.sci.2025.57.2.2

Classifying Coal Mine Pillar Stability Areas with Multiclass SVM on Ensemble Learning Models

DOI : 10.5614/j.eng.technol.sci.2024.56.1.8
Gatot Fatwanto Hertono (1), Ridho Kresna Wattimena (2), Gabriella Aileen Mendrofa (3), Bevina Desjwiandra Handari (4)
(1) Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Kampus Baru UI, Depok 16424, Indonesia , Indonesia ,
(2) Mining Engineering Study Program, Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung, Jalan Ganesa No. 10 Bandung 40132, Indonesia, Indonesia ,
(3) Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Kampus Baru UI, Depok 16424, Indonesia , Indonesia ,
(4) Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Kampus Baru UI, Depok 16424, Indonesia , Indonesia
95-109
Abstract : 878
PDF : 246
DOI: https://doi.org/10.5614/j.eng.technol.sci.2024.56.1.8
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