Advancements in Machine Learning and Deep Learning Techniques for Crop Yield Prediction: A Comprehensive Review by V. Ramesh and P. Kumaresan

Subjects: “…crop yield prediction, machine learning, deep learning, artificial neural networks, optimization algorithms…”
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AI-driven prediction of drug activity against Toxoplasma gondii: Data augmentation and deep neural networks for limited datasets by Natalia V. Karimova, Ravithree D. Senanayake

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Machine learning-driven benchmarking of China's wastewater treatment plant electricity consumption by Minjian Li, Chongqiao Tang, Junhan Gu, Nianchu Li, Ahemaide Zhou, Kunlin Wu, Zhibo Zhang, Hui Huang, Hongqiang Ren

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Organophosphorus Pesticides Management Strategies: Prohibition and Restriction Multi-Category Multi-Class Models, Environmental Transformation Risks, and Special Attention List by Yingwei Wang, Lu Wang, Yufei Li

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Outbreak prediction of covid-19 in most susceptible countries by D. Yadav, H. Maheshwari, U. Chandra

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Multimodal data integration in early-stage breast cancer by Arnau Llinas-Bertran, Maria Butjosa-Espín, Vittoria Barberi, Jose A. Seoane

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Identification of the immune infiltration and biomarkers in ulcerative colitis based on liquid–liquid phase separation-related genes by Zhixing Hong, Shilin Fang, Haihang Nie, Jingkai Zhou, Yuntian Hong, Lan Liu, Qiu Zhao

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A new dimensionality reduction technique based on the Wavelet Transform for cancer classification by Lisardo Fernández, Mariano Pérez, Juan M. Orduña, José M. Alcaraz

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Estimating regional shared trailer demand in drop-and-pull transport by Mei Feng, Qianwei Peng, Zhixue Zhao

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SD‐SHO: Security‐dominated finite state machine state assignment technique with a satisfactory level of hardware optimization by Nitish Das, Aruna Priya Panchanathan

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An Ensemble Based Machine Learning Classification for Automated Glaucoma Detection by Digvijay J. Pawar, Yuvraj K. Kanse, Suhas S. Patil

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Proximity-based solutions for optimizing autism spectrum disorder treatment: integrating clinical and process data for personalized care by Annarita Vignapiano, Annarita Vignapiano, Francesco Monaco, Francesco Monaco, Stefania Landi, Luca Steardo, Carlo Mancuso, Claudio Pagano, Gianvito Petrillo, Alessandra Marenna, Martina Piacente, Stefano Leo, Carminia Marina Ingenito, Rossella Bonifacio, Benedetta Di Gruttola, Marco Solmi, Marco Solmi, Marco Solmi, Marco Solmi, Maria Pontillo, Giorgio Di Lorenzo, Giorgio Di Lorenzo, Alessio Fasano, Alessio Fasano, Alessio Fasano, Giulio Corrivetti, Giulio Corrivetti

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Metagenomic exploration and computational prediction of novel enzymes for polyethylene terephthalate degradation by Donya Afshar Jahanshahi, Mohammad Reza Rezaei Barzani, Mohammad Bahram, Shohreh Ariaeenejad, Kaveh Kavousi

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Machine learning-assisted design of Ti–V–Nb–Mo refractory high-entropy alloys with higher ductility and specific yield strength by Yan Li, Junjie Gong, Shilong Liang, Wei Wu, Yongxin Wang, Zheng Chen

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Comparison of Different Machine Learning Methodologies for Predicting the Non‐Specific Treatment Response in Placebo Controlled Major Depressive Disorder Clinical Trials by Roberto Gomeni, Françoise Bressolle‐Gomeni

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Understanding and Modeling the Dynamics of Storm‐Time Atmospheric Neutral Density Using Random Forests by K. Murphy, A. J. Halford, V. Liu, J. Klenzing, J. Smith, K. Garcia‐Sage, J. Pettit, I. J. Rae

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Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China by Fan Zhang, Xiaohong Shi, Shengnan Zhao, Ruonan Hao, Biao Sun, Guohua Li, Shihuan Wang, Hao Zhang

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Taba Binary, Multinomial, and Ordinal Regression Models: New Machine Learning Methods for Classification by Mohammad Tabatabai, Derek Wilus, Chau-Kuang Chen, Karan P. Singh, Tim L. Wallace

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Exploring Machine Learning Classification of Movement Phases in Hemiparetic Stroke Patients: A Controlled EEG-tDCS Study by Rishishankar E. Suresh, M S Zobaer, Matthew J. Triano, Brian F. Saway, Parneet Grewal, Nathan C. Rowland

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Predicting the reduction in heatstroke and heart disease-related mortality under urban modification scenarios using machine learning by Yukitaka Ohashi, Ko Nakajima, Yuya Takane, Yukihiro Kikegawa, Tomohiko Ihara, Kazutaka Oka

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