Multi-objective Optimization Method for Pocket Milling Driven by Massive Virtual Machining by SHEN Bin, TU Weiyi, NIE Pengfei, WANG Chenghan, AI Di, WU Jun, ZHENG Zujie, GUO Guoqiang

“…The database is used to estimate risks and optimize parameters. The neural network is combined to predict the machining state. …”
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Data-driven network intrusion detection using optimized machine learning algorithms by Dauda Adeite Adenusi, Oladosu Oyebisi Oladimeji, Theopilus Adekunle Oyekola, Korede Solomon Olagunju

“…Comparative analysis with existing approaches, including deep learning methods, shows that our optimized tree-based models achieve comparable or superior performance while maintaining computational efficiency. …”
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Optimizing UAV sprayer performance using field data and machine learning approaches by Doğan Güneş, Hideo Hasegawa

“…This integrated approach demonstrates the potential of combining field data with simulation and machine learning to optimize UAV spraying strategies, offering a framework for broader applications in sustainable agriculture.…”
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Optimized hybrid machine learning framework for early diabetes prediction using electrogastrograms by Paramasivam Alagumariappan, Malathy Sathyamoorthy, Rajesh Kumar Dhanaraj, K. Kamalanand, C. Emmanuel, Sarah Allabun, Manal Othman, Masresha Getahun, Ben Othman Soufiene

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Data-efficient optimization of thermally-activated polymer actuators through machine learning by Yuhao Zhang, Maija Vaara, Azin Alesafar, Duc Bach Nguyen, Pedro Silva, Laura Koskelo, Jussi Ristolainen, Matthias Stosiek, Joakim Löfgren, Jaana Vapaavuori, Patrick Rinke

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Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

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Experimental analysis and optimization of hydrogen pre-cooling liquefaction process with composite catalyst through a hybrid priority cluster modeling approach by Faisal Khan, Osama Khan, Praveen Pachauri, Mohd Parvez, Aiyeshah Alhodaib, Zeinebou Yahya, Haidar Howari, M. Javed Idrisi, Worku Tenna

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Self compacting concrete with recycled aggregate compressive strength prediction based on gradient boosting regression tree with Bayesian optimization hybrid model by Emad A. Abood, Zainab Abdulrdha Thoeny, Noralhuda M. Azize, Hamza Imran, Viroon Kamchoom, Kennedy C. Onyelowe, Krishna Prakash Arunachalam

“…In our research we presented a new hybrid model, GBRT, that was integrated with Bayesian Optimization. …”
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Optimasi Model Extreme Gradient Boosting Dalam Upaya Penentuan Tingkat Risiko Pada Ibu Hamil Berbasis Bayesian Optimization (BOXGB) by Edi Jaya Kusuma, Ririn Nurmandhani, Lenci Aryani, Ika Pantiawati, Guruh Fajar Shidik

“…Secara keseluruhan implementasi Bayesian Optimization mampu memberikan setelan hyper-parameter yang dapat meningkatkan kemampuan model machine learning khususnya dalam memprediksi tingkat risiko kehamilan pada ibu hamil berdasarkan data pengukuran klinis.   …”
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Traffic light optimization (TLO) using reinforcement learning for automated transport systems by Mohammad Mehedi Hassan, Stephen Karungaru, Kenji Terada

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Robust Optimal Sizing of a Stand-Alone Hybrid Renewable Energy System Using Machine Learning-Based Uncertainty Sets by Ali Keyvandarian, Ahmed Saif, Ronald Pelot

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Data driven models for predicting pH of CO2 in aqueous solutions: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Moein Kafi, Hamed Nikravesh, Maryam Aghel, Erfan Mohammadian, Yousef Kazemzadeh, Reza Azin

“…To fill this research gap, this study developed 15 models comprising five machine learning methods: regression trees, support vector regression, Gaussian process regression, bagged trees, and boosted trees, and three optimization algorithms: random search, grid search, and Bayesian optimization. …”
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Prediction of Shear Strength of Steel Fiber-Reinforced Concrete Beams with Stirrups Using Hybrid Machine Learning and Deep Learning Models by B. R. Kavya, A. S. Shrikanth, K. S. Sreekeshava

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Prediction of uniaxial compressive strength of limestone from ball mill grinding characteristics using supervised machine learning techniques by Sahas V. Swamy, Bijay Mihir Kunar, Karra Ram Chandar, Mamdooh Alwetaishi, Shashikumar Krishnan, Sudhakar Reddy

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Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database by Hongyi Chen, Haiyang Song, Hongyu Huang, Xiaojun Fang, Huang Chen, Qingqing Yang, Junyu Zhang, Wenjun Ding, Zheng Gong, Jun Ke

Subjects: “…bayesian optimization…”
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Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection by Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu

“…Model performance was systematically evaluated through discrimination (ROC analysis), calibration (Brier score), and clinical utility analyses (decision curve analysis), with additional validation using random forest and support vector machine algorithms across independent samples. …”
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Leveraging boosting machine learning for drilling rate of penetration (ROP) prediction based on drilling and petrophysical parameters by Raed H. Allawi, Watheq J. Al-Mudhafar, Mohammed A. Abbas, David A. Wood

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Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection by Khalil Abbal, Mohammed El-Amrani, Oussama Aoun, Youssef Benadada

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Evaluation of predictive maintenance efficiency with the comparison of machine learning models in machining production process in brake industry by Can Aydın, Burak Evrentuğ

“…Hyperparameter optimization was also performed, resulting in significant improvements in model performance. …”
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Token-Based Digital Currency Model for Aviation Technical Support as a Service Platforms by Igor Kabashkin, Vladimir Perekrestov, Maksim Pivovar

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