Forecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithms

被引：0
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作者：
Bakır, Hüseyin [1 ]
Ağbulut, Ümit [2 ]
Gürel, Ali Etem [2 ,3 ,4 ]
Yıldız, Gökhan [2 ]
Güvenç, Uğur [5 ]
Soudagar, Manzoore Elahi M. [6 ,7 ]
Hoang, Anh Tuan [8 ]
Deepanraj, Balakrishnan [9 ,10 ]
Saini, Gaurav [7 ]
Afzal, Asif [6 ,11 ,12 ,13 ]
机构：
[1] Department of Electronics and Automation, Vocational School, Dogus University, Istanbul,34775, Turkey
[2] Department of Mechanical Engineering, Engineering Faculty, Düzce University, 81620, Turkey
[3] Department of Electricity and Energy, Vocational School, Düzce University, 81010, Turkey
[4] Düzce University, Clean Energy Resources Application and Research Center, Düzce, Konuralp,81620, Turkey
[5] Department of Electrical and Electronics Engineering, Faculty of Engineering, Düzce University, 81010, Turkey
[6] University Centre for Research & Development, Department of Mechanical Engineering, Chandigarh University, Punjab, Mohali,140413, India
[7] Department of Mechanical Engineering, School of Technology, Glocal University, SH-57, Mirzapur Pole, Saharanpur District, Uttar Pradesh, 247121, India
[8] Institute of Engineering, HUTECH University, Ho Chi Minh City, Viet Nam
[9] College of Engineering, Prince Mohammad Bin Fahd University, Al Khobar,31952, Saudi Arabia
[10] Department of Mechanical Engineering, Jyothi Engineering College, Thrissur,679531, India
[11] School of Advanced Materials, Green Energy and Sensor Systems, Indian Institute of Engineering Science and Technology, West Bengal, India
[12] Department of Mechanical Engineering, P. A. College of Engineering (Affiliated to Visvesvaraya Technological University, Belagavi, Mangaluru,574153, India
[13] University Centre for Research & Development, Department of Computer Science and Engineering, Chandigarh University, Punjab, Mohali,140413, India
来源：
Journal of Cleaner Production | 2022年 / 360卷
关键词：
Biology - Forecasting - Trajectories - Electric power generation - Gas emissions - Greenhouse gases - Learning algorithms - Carbon dioxide - Optimization;
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