Anomaly based novel multi-source unsupervised transfer learning approach for carbon emission centric GDP prediction

[1]  S. Awaworyi Churchill,et al.  The Environmental Kuznets Curve across Australian states and territories , 2020 .

[2]  Amit K. Shukla,et al.  Isolation Forest Based Multi-Source Unsupervised Transfer Learning for Missing GDP Prediction , 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

[3]  Halil Altıntaş,et al.  Is the environmental Kuznets Curve in Europe related to the per-capita ecological footprint or CO2 emissions? , 2020 .

[4]  Eyup Dogan,et al.  The use of ecological footprint in estimating the Environmental Kuznets Curve hypothesis for BRICST by considering cross-section dependence and heterogeneity. , 2020, The Science of the total environment.

[5]  Samuel Asumadu Sarkodie,et al.  Investigating the Environmental Kuznets Curve hypothesis in Kenya: A multivariate analysis , 2020 .

[6]  Samuel Asumadu Sarkodie,et al.  Testing the role of oil production in the environmental Kuznets curve of oil producing countries: New insights from Method of Moments Quantile Regression. , 2019, The Science of the total environment.

[7]  Pranab K. Muhuri,et al.  A Novel GDP Prediction Technique based on Transfer Learning using CO2 Emission Dataset , 2019, Applied Energy.

[8]  I. A. Mensah,et al.  Analysis on the nexus of economic growth, fossil fuel energy consumption, CO2 emissions and oil price in Africa based on a PMG panel ARDL approach , 2019, Journal of Cleaner Production.

[9]  Bernard Kamsu-Foguem,et al.  Deep neural networks with transfer learning in millet crop images , 2019, Comput. Ind..

[10]  Yogi Sugiawan,et al.  Are carbon dioxide emission reductions compatible with sustainable well-being? , 2019, Applied Energy.

[11]  Stephane de la Rue du Can,et al.  Modeling India’s energy future using a bottom-up approach , 2019, Applied Energy.

[12]  Sandeep Kumar,et al.  Random Fuzzy Variable based Uncertainty Modelling for the Prediction of Human Development Index using CO2 Emission Data , 2018, 2018 IEEE Symposium Series on Computational Intelligence (SSCI).

[13]  Transfer learning approach for classification and noise reduction on noisy web data , 2018, Expert Systems with Applications.

[14]  A. Acheampong.  Economic growth, CO2 emissions and energy consumption: What causes what and where? , 2018, Energy Economics.

[15]  Sandeep Kumar,et al.  Interval Type-2 Fuzzy weighted Extreme Learning Machine for GDP Prediction , 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

[16]  Jun-Hai Zhai,et al.  Ensemble dropout extreme learning machine via fuzzy integral for data classification , 2018, Neurocomputing.

[17]  A. Chiu,et al.  Driving forces of Iran's CO2 emissions from energy consumption: An LMDI decomposition approach , 2017 .

[18]  S. Chaabouni,et al.  The dynamic links between carbon dioxide (CO2) emissions, health spending and GDP growth: A case study for 51 countries , 2017, Environmental research.

[19]  Samuel Asumadu-Sarkodie,et al.  Recent evidence of the relationship between carbon dioxide emissions, energy use, GDP, and population in Ghana: A linear regression approach , 2017 .

[20]  Miloš Milovančević,et al.  Prediction of GDP growth rate based on carbon dioxide (CO2) emissions , 2016 .

[21]  Sandeep Kumar,et al.  Atanassov Intuitionistic Fuzzy Domain Adaptation to contain negative transfer learning , 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[22]  A. Robalino-López,et al.  CO2 emissions convergence among 10 South American countries. A study of Kaya components (1980–2010) , 2016 .

[23]  P. Narayan,et al.  Economic growth and carbon emissions , 2016 .

[24]  Rawshan Ara Begum,et al.  Dynamics of energy use, technological innovation, economic growth and trade openness in Malaysia , 2015 .

[25]  M. Wagner.  The Environmental Kuznets Curve, Cointegration and Nonlinearity , 2015 .

[26]  Rudra P. Pradhan,et al.  Transportation intensity, urbanization, economic growth, and CO2 emissions in the G-20 countries , 2015 .

[27]  João Ricardo Sato,et al.  On the relationships between CO2 emissions, energy consumption and income: The importance of time variation , 2015 .

[28]  Sami Hammami,et al.  The impact of energy consumption and CO2 emissions on economic growth: Fresh evidence from dynamic simultaneous-equations models , 2015 .

[29]  Simon Coupland,et al.  Fuzzy Transfer Learning: Methodology and application , 2015, Inf. Sci..

[30]  Brantley Liddle.  What Are the Carbon Emissions Elasticities for Income and Population? Bridging STIRPAT and EKC via Robust Heterogeneous Panel Estimates , 2015 .

[31]  Witold Pedrycz,et al.  Multistep Fuzzy Bridged Refinement Domain Adaptation Algorithm and Its Application to Bank Failure Prediction , 2015, IEEE Transactions on Fuzzy Systems.

[32]  R. Begum,et al.  CO2 emissions, energy consumption, economic and population growth in Malaysia , 2015 .

[33]  S. Katircioğlu,et al.  Economic growth, CO2 emissions, and energy consumption in the five ASEAN countries , 2015 .

[34]  A. Robalino-López,et al.  Studying the relationship between economic growth, CO2 emissions, and the environmental Kuznets curve in Venezuela (1980–2025) , 2015 .

[35]  Duc Khuong Nguyen,et al.  Causal interactions between CO2 emissions, FDI, and economic growth: Evidence from dynamic simultaneous-equation models , 2014 .

[36]  Mohammad Salahuddin,et al.  Economic growth, energy consumption and CO2 emissions in Gulf Cooperation Council countries , 2014 .

[37]  Danai Koutra,et al.  Graph based anomaly detection and description: a survey , 2014, Data Mining and Knowledge Discovery.

[38]  Angel Mena-Nieto,et al.  System dynamics modelling and the environmental Kuznets curve in Ecuador (1980–2025) , 2014, Energy Policy.

[39]  Jie Lu,et al.  Text categorization by fuzzy domain adaptation , 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[40]  C. Tang,et al.  The dynamic links between CO2 emissions, economic growth and coal consumption in China and India , 2013 .

[41]  Joachim Denzler,et al.  One-class classification with Gaussian processes , 2010, Pattern Recognit..

[42]  Brian C. O'Neill,et al.  Urban and rural energy use and carbon dioxide emissions in Asia , 2012 .

[43]  Cecilio Tamarit,et al.  Is there an environmental Kuznets curve for Spain? Fresh evidence from old data , 2012 .

[44]  Muhammad Shahbaz,et al.  Environmental Kuznets Curve hypothesis in Pakistan: Cointegration and Granger causality , 2012 .

[45]  Fei Tony Liu,et al.  Isolation-Based Anomaly Detection , 2012, TKDD.

[46]  S. Sathya Bama,et al.  Network Intrusion Detection using Clustering: A Data Mining Approach , 2011 .

[47]  Hsiao-Tien Pao,et al.  Multivariate Granger causality between CO2 emissions, energy consumption, FDI (foreign direct investment) and GDP (gross domestic product): Evidence from a panel of BRIC (Brazil, Russian Federation, India, and China) countries , 2011 .

[48]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[49]  D. Stern.  Between estimates of the emissions-income elasticity , 2010 .

[50]  Zhi-Hua Zhou,et al.  Isolation Forest , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[51]  Chee Kheong Siew,et al.  Extreme learning machine: Theory and applications , 2006, Neurocomputing.

[52]  M. Wagner,et al.  The Carbon Kuznets Curve: A Cloudy Picture Emitted by Bad Econometrics? , 2008 .

[53]  Guang-Bin Huang,et al.  Extreme learning machine: a new learning scheme of feedforward neural networks , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[54]  Jinbo Bi,et al.  A geometric approach to support vector regression , 2003, Neurocomputing.

[55]  Dong Xiang,et al.  Information-theoretic measures for anomaly detection , 2001, Proceedings 2001 IEEE Symposium on Security and Privacy. S&P 2001.

[56]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[57]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..