PlantLncBoost: key features for plant lncRNA identification and significant improvement in accuracy and generalization

Authors: Tian, Xue-Chan, Nie, Shuai, Domingues, Douglas, Rossi Paschoal, Alexandre, Jiang, Li-Bo, Mao, Jian-Feng, 1977

Source: New Phytologist. 247(3):1538-1549

Subject Terms: feature selection, Fourier transform, gradient boosting algorithms, long noncoding RNAs (lncRNAs), model selection, ORF coverage

File Description: electronic

Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-240920
https://doi.org/10.1111/nph.70211

Advanced Machine Learning Techniques Revolutionize Credit Card Fraud Detection

Authors: A, Balamanikandan, D, Jayakumar, M, Dhanalakshmi, G, Sudharsan, Prabha, Ankala Satya, V, Venkata Karthika

Source: 2025 International Conference on Networks & Advances in Computational Technologies (NetACT) Networks & Advances in Computational Technologies (NetACT), 2025 International Conference on. :1-6 Aug, 2025

Relation: 2025 International Conference on Networks & Advances in Computational Technologies (NetACT)

Early Detection of Student Dropout Risk via Hybrid Deep Learning and Gradient Boosting Algorithms

Authors: Rajput, Vaibhav, Singh, Aryan, Gupta, Subhash Chand

Source: 2025 International Conference on Engineering, Technology & Management (ICETM) Engineering, Technology & Management (ICETM), 2025 International Conference on. :1-6 May, 2025

Relation: 2025 International Conference on Engineering, Technology & Management (ICETM)

Classification and Prediction of Wafer Yield Using Gradient Boosting Algorithms: A Focus on Lithography Inline Parameters

Authors: Islam, Mohammed Nizamul, Islam, Md Tarekul, Dhali, Maruf A

Source: 2025 IEEE 4th International Conference on Computing and Machine Intelligence (ICMI) Computing and Machine Intelligence (ICMI), 2025 IEEE 4th International Conference on. :1-6 Apr, 2025

Relation: 2025 IEEE 4th International Conference on Computing and Machine Intelligence (ICMI)

Enhancing Liver Cirrhosis Prognosis: A Machine Learning and Explainable AI Approach

Authors: Jeyabalan, Jeyalakshmi, Karthikeyan

Source: 2024 Third International Conference on Artificial Intelligence, Computational Electronics and Communication System (AICECS) Artificial Intelligence, Computational Electronics and Communication System (AICECS), 2024 Third International Conference on. :1-5 Dec, 2024

Relation: 2024 Third International Conference on Artificial Intelligence, Computational Electronics and Communication System (AICECS)

Meta Learning Strategies for Comparative and Efficient Adaptation to Financial Datasets

Authors: Noor, K., Fatima, U.

Source: IEEE Access Access, IEEE. 13:24158-24170 2025

Revolutionizing Credit Risk: A Deep Dive into Gradient-Boosting Techniques in AI-Driven Finance

Authors: Tareaf, Raad Bin, AbuJarour, Mohammed, Zinn, Fabian

Source: 2024 International Conference on Information Networking (ICOIN) Information Networking (ICOIN), 2024 International Conference on. :322-327 Jan, 2024

Relation: 2024 International Conference on Information Networking (ICOIN)

Analysis and development of risk prediction models for chronic opioid use after surgery: a cohort study using the nationwide database

Authors: Jonghae Kim, Hyun-Lim Yang, Eugene Kim, Hyung-Chul Lee, Hyun-Kyu Yoon, Yun Jin Kim, Kyu-Nam Kim, Ji-Yoon Kim, Jeong Min Sung, Tagkeun Lee

Source: Korean Journal of Anesthesiology, Vol 78, Iss 5, Pp 429-442 (2025)

Subject Terms: dependence, opioid, gradient boosting algorithms, machine learning, postoperative period, prediction methods, machine, surgical procedures, operative, Anesthesiology, RD78.3-87.3

File Description: electronic resource

Relation: http://ekja.org/upload/pdf/kja-24831.pdf; https://doaj.org/toc/2005-6419; https://doaj.org/toc/2005-7563

Access URL: https://doaj.org/article/52378890d3e74f4f9ba94ad2ab5a4bc7

A Comparison of Machine Learning Algorithms for Customer Churn Prediction

Authors: Pulkundwar, Parth, Rudani, Krishna, Rane, Omkar, Shah, Chintan, Virnodkar, Shyamal

Source: 2023 6th International Conference on Advances in Science and Technology (ICAST) Advances in Science and Technology (ICAST), 2023 6th International Conference on. :437-442 Dec, 2023

Relation: 2023 6th International Conference on Advances in Science and Technology (ICAST)

AI-Automated System for Ingredient Planner using Machine Learning Algorithms

Authors: Arvindaraj, G., Manikandan, B., Rokesh, R., Abinaya, M.

Source: 2023 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2023 7th International Conference on. :511-515 Oct, 2023

Relation: 2023 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

Machine Learning Techniques for The Detection of Imposters in Credit Card Fraudulence

Authors: Jeyanathan, Josephine Selle, Kavyasree, Nayani, Pranathi, Thalla, Gowthami, Male, Monalisa, Rapuri

Source: 2023 World Conference on Communication & Computing (WCONF) Communication & Computing (WCONF), 2023 World Conference on. :1-5 Jul, 2023

Relation: 2023 World Conference on Communication & Computing (WCONF)

Fraud Detection in Online Payments using Machine Learning Techniques

Authors: Siddaiah, U., Anjaneyulu, P., Haritha, Y., Ramesh, M

Source: 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS) Intelligent Computing and Control Systems (ICICCS), 2023 7th International Conference on. :268-273 May, 2023

Relation: 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS)

Optimization of Prediction Results Based on Ensemble Methods of Machine Learning

Authors: Nazarov, Fayzullo Makhmadiyarovich, Yarmatov, Sherzodjon

Source: 2023 International Russian Smart Industry Conference (SmartIndustryCon) Russian Smart Industry Conference (SmartIndustryCon), 2023 International. :181-185 Mar, 2023

Relation: 2023 International Russian Smart Industry Conference (SmartIndustryCon)

Using Gradient Boosting Algorithms in Predicting Student Academic Performance

Authors: Mashagba, Esraa, Al-Saqqar, Faisal, Al-Shatnawi, Atallah

Source: 2023 International Conference on Business Analytics for Technology and Security (ICBATS) Business Analytics for Technology and Security (ICBATS), 2023 International Conference on. :1-7 Mar, 2023

Relation: 2023 International Conference on Business Analytics for Technology and Security (ICBATS)

Design of an Intrusion Detection Model for IoT-Enabled Smart Home

Authors: Rani, D., Gill, N.S., Gulia, P., Arena, F., Pau, G.

Source: IEEE Access Access, IEEE. 11:52509-52526 2023

Competitive Analysis of the Top Gradient Boosting Machine Learning Algorithms

Authors: R, Shyam, Ayachit, Sai Sanjay, Patil, Vinayak, Singh, Anubhav

Source: 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN) Computing, Communication Control and Networking (ICACCCN), 2020 2nd International Conference on. :191-196 Dec, 2020

Relation: 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)

Predicting H1N1 and Seasonal Flu : Vaccine Cases using Ensemble Learning approach

Authors: Ayachit, Sai Sanjay, Kumar, Tanmay, Deshpande, Shriya, Sharma, Nayan, Chaurasia, Kuldeep, Dixit, Mayank

Source: 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN) Computing, Communication Control and Networking (ICACCCN), 2020 2nd International Conference on. :172-176 Dec, 2020

Relation: 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)

Construction and Application of Carbon Emissions Estimation Model for China Based on Gradient Boosting Algorithm

Authors: Dongjie Guan, Yitong Shi, Lilei Zhou, Xusen Zhu, Demei Zhao, Guochuan Peng, Xiujuan He

Source: Remote Sensing, Vol 17, Iss 14, p 2383 (2025)

Subject Terms: carbon emission forecasting, county level, gradient boosting algorithms, spatiotemporal patterns, SHAP interpretation, Science

File Description: electronic resource

Relation: https://www.mdpi.com/2072-4292/17/14/2383; https://doaj.org/toc/2072-4292

Access URL: https://doaj.org/article/4acc578eb0134741bd02b2a727f372df

Artificial Intelligence Techniques for Solar Irradiance and PV Modeling and Forecasting

Contributors: Harrou, Fouzi, Sun, Ying, Taghezouit, Bilal, Dairi, Abdelkader

Subject Terms: two-diode model, parameter estimation, gray wolf optimizer, photovoltaic (PV), incremental conductance (InC), dragonfly (DA), maximum power point tracking (MPPT), perturb and observe (P&O), adaptive cuckoo search optimization (ACS), particle swarm optimization (PSO), local maxima (LM), complex partial shading (CPS), partial shading (PS), photovoltaic power forecast, solar energy, Temporal Fusion Transformer, deep learning, artificial intelligence, deep reinforcement learning, double deep Q network, photovoltaic mathematical model, photovoltaic systems, ensemble bagged trees, anomaly detection, shading, electrical faults, statistical control charts, shading ratio estimation, photovoltaics, total-sky imaging, cloud estimation, artificial intelligence (AI), photovoltaic (PV) systems, dust cleaning, renewable energy, optimization, cost minimization, BIPV, PV power forecasting, machine learning, gradient boosting algorithms, maximum power point tracker (MPPT), photovoltaic, partial shading conditions (PSCs), dandelion optimizer, monitoring system, fault diagnosis, internet of things, shallow neural networks, recurrent neural networks, predictive hybrid model, photovoltaic energy, photovoltaic energy prediction, Technology: general issues

File Description: application/octet-stream

Access URL: https://directory.doabooks.org/handle/20.500.12854/137728
https://mdpi.com/books/pdfview/book/8957

Machine Learning-Based Lightning Localization Algorithm Using Lightning-Induced Voltages on Transmission Lines

Authors: Karami, H., Mostajabi, A., Azadifar, M., Rubinstein, M., Zhuang, C., Rachidi, F.

Source: IEEE Transactions on Electromagnetic Compatibility IEEE Trans. Electromagn. Compat. Electromagnetic Compatibility, IEEE Transactions on. 62(6):2512-2519 Dec, 2020