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Onuwa Okwuashi, Christopher E. Ndehedehe, Dupe Nihinlola Olayinka, Aniekan Eyoh & Hosanna Attai. (2021) Deep support vector machine for PolSAR image classification. International Journal of Remote Sensing 42:17, pages 6498-6536.
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Zhipeng Niu, Xiaowei Hu, Mahmudur Fatmi, Shouming Qi, Siqing Wang, Haihua Yang & Shi An. (2023) Parking occupancy prediction under COVID-19 anti-pandemic policies: A model based on a policy-aware temporal convolutional network. Transportation Research Part A: Policy and Practice 176, pages 103832.
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Abrar Yaqoob, Rabia Musheer Aziz & Navneet Kumar verma. (2023) Applications and Techniques of Machine Learning in Cancer Classification: A Systematic Review. Human-Centric Intelligent Systems 3:4, pages 588-615.
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Huanfa Chen & Yan Cheng. (2023) Travel Mode Choice Prediction Using Imbalanced Machine Learning. IEEE Transactions on Intelligent Transportation Systems 24:4, pages 3795-3808.
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Hamed Naseri, Edward Owen Douglas Waygood, Bobin Wang & Zachary Patterson. (2022) Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters. International Journal of Environmental Research and Public Health 19:24, pages 16844.
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Mohammadreza Akbarzadeh, Sina Shaffiee Haghshenas, Seyed Mohammad Esmaeil Jalali, Shokrollah Zare & Reza Mikaeil. (2022) Developing the Rule of Thumb for Evaluating Penetration Rate of TBM, Using Binary Classification. Geotechnical and Geological Engineering 40:9, pages 4685-4703.
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Patricio Salas, Rodrigo De la Fuente, Sebastian Astroza & Juan Antonio Carrasco. (2022) A systematic comparative evaluation of machine learning classifiers and discrete choice models for travel mode choice in the presence of response heterogeneity. Expert Systems with Applications 193, pages 116253.
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Weijia (Vivian) Li & Kara M. Kockelman. (2021) How does machine learning compare to conventional econometrics for transport data sets? A test of ML versus MLE. Growth and Change 53:1, pages 342-376.
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Sruthi Ashraf, Arezoo Samimi Abianeh, Farinoush Sharifi, Vivek Gupta, Isha Shyam Narsaria & Mark Burris. (2021) Predicting the Use of Managed Lanes Using Machine Learning. Journal of Big Data Analytics in Transportation 3:3, pages 213-227.
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K. Parthiban, Digvijay Pandey & Binay Kumar Pandey. (2021) Impact of SARS-CoV-2 in Online Education, Predicting and Contrasting Mental Stress of Young Students: A Machine Learning Approach. Augmented Human Research 6:1.
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Wangli Zhu & Meixia Shi. (2021) Research on the Development Path of a Cross-European e-Commerce Logistics Mode under the Background of “Internet Plus”. Wireless Communications and Mobile Computing 2021, pages 1-7.
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Eui-Jin Kim, Youngseo Kim, Sunghoon Jang & Dong-Kyu Kim. (2021) Tourists’ preference on the combination of travel modes under Mobility-as-a-Service environment. Transportation Research Part A: Policy and Practice 150, pages 236-255.
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Kailai Wang & Xize Wang. (2021) Generational differences in automobility: Comparing America's Millennials and Gen Xers using gradient boosting decision trees. Cities 114, pages 103204.
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Tim Hillel, Michel Bierlaire, Mohammed Z.E.B. Elshafie & Ying Jin. (2021) A systematic review of machine learning classification methodologies for modelling passenger mode choice. Journal of Choice Modelling 38, pages 100221.
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Xinyi Tang, Dianhai Wang, Yilin Sun, Mengwei Chen & E. Owen D. Waygood. (2020) Choice behavior of tourism destination and travel mode: A case study of local residents in Hangzhou, China. Journal of Transport Geography 89, pages 102895.
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Zhengchao Zhang, Congyuan Ji, Yineng Wang & Yanni Yang. (2020) A Customized Deep Neural Network Approach to Investigate Travel Mode Choice with Interpretable Utility Information. Journal of Advanced Transportation 2020, pages 1-11.
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Onuwa Okwuashi & Christopher E. Ndehedehe. (2020) Deep support vector machine for hyperspectral image classification. Pattern Recognition 103, pages 107298.
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Abdulkerim Karabiber & Omer Faruk Alcin. (2019) Short Term PV Power Estimation by means of Extreme Learning Machine and Support Vector Machine. Short Term PV Power Estimation by means of Extreme Learning Machine and Support Vector Machine.