Method of Generalized Evaluation in the Selecting Factors and Levels of Variation in the Multifactorial Study of Sowing Machines by E. M. Zubrilina, I. A. Markvo, A. S. Zhuravlev, V. I. Novikov, E. V. Neroda

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Sustainable phytoprotection: a smart monitoring and recommendation framework using Puma Optimization for potato pathogen detection by Amal H. Alharbi, Faris H. Rizk, Khaled Sh. Gaber, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Pushan Kumar Dutta, Doaa Sami Khafaga

“…This study proposes a novel hybrid framework for potato disease classification that integrates copula-based dependency modeling with a Restricted Boltzmann Machine (RBM), further enhanced through hyperparameter tuning using the biologically inspired Puma Optimization (PO) algorithm. …”
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An Optimized Hybrid PSO-ELM for Parkinson’s Disease Diagnosis by Gunakala Archana, Afzal Hussain Shahid

“…This paper proposes a hybrid model combining Particle Swarm Optimization with Extreme Learning Machine (PSO-ELM) for PD diagnosis. …”
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Uterine Transplant Optimization From a Preclinical Donor Model With Controlled Cardiocirculatory Arrest by Emma Loiseau, MSc, Benoit Mesnard, MSc, Sarah Bruneau, PhD, Carla De Sousa, MD, Stéphanie Bernardet, PhD, Jeremy Hervouet, David Minault, Stephan Levy, MSc, Antoine Le Gal, MD, Ludivine Dion, PhD, Gilles Blancho, MD, PhD, Vincent Lavoue, MD, PhD, Julien Branchereau, MD, PhD

“…We performed a preclinical study on a porcine model of controlled donation after circulatory death (60 min warm ischemia). …”
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Numerical benchmarking of dual decomposition-based optimization algorithms for distributed model predictive control by Vassilios Yfantis, Achim Wagner, Martin Ruskowski

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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Subsequently, both classical and quantum-inspired models are trained and optimized. The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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Data-Driven Computational Methods in Fuel Combustion: A Review of Applications by Jacek Lukasz Wilk-Jakubowski, Lukasz Pawlik, Damian Frej, Grzegorz Wilk-Jakubowski

Subjects: “…machine learning…”
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Digitized material design and performance prediction driven by high-throughput computing by Hanhui Li, Jiao Yang, Jingxu Yao, Jingxu Yao, Chuanxin Sheng

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Unified modeling language code generation from diagram images using multimodal large language models by Averi Bates, Ryan Vavricka, Shane Carleton, Ruosi Shao, Chongle Pan

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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

“…By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method and fuzzy entropy (FE) with the new and highly efficient Runge–Kuta optimizer (RUN), adaptive parameter optimization for the support vector machine (SVM) and radial basis function neural network (RBFNN) algorithms was achieved. …”
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Optimal power flow with synchronous generator capability curves using the branch flow model by Dakota Hamilton, Dionysios Aliprantis

“…A method for incorporating synchronous generator capability curves (GCC) into the constraints of the optimal power flow (OPF) problem is proposed. The steady-state equivalent circuit of the synchronous machine in qd variables is added as a branch in the branch flow model (BFM) of the power system equations. …”
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Comprehensive Outlier Detection in Wireless Sensor Network with Fast Optimization Algorithm of Classification Model by Haiqing Yao, Heng Cao, Jin Li

“…To reduce the complexity of optimization algorithm for QSSVM model in existing techniques, a fast optimization algorithm based on average Euclidean distance has been developed and employed to the comprehensive outlier detection method. …”
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New categorized machine learning models for daily solar irradiation estimation in southern Morocco's, Zagora city by Zineb Bounoua, Laila Ouazzani Chahidi, Abdellah Mechaqrane

“…It also performs well in estimating DHI with Clearness index Based Models (nRMSE=20.44 %). The next effective method is MLP, that is the optimal one in estimating daily GHI with Relative Humidity Based Models (nRMSE=11.41 %) and daily DNI using Clearness index Based Models (nRMSE= 12.43 %). …”
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Applying an optimized low risk model for fast history matching in giant oil reservoir by Mojtaba karimi, Ali Mortazavi, Mohammad Ahmadi

“…Modified support vector machine was employed to create proxy model in which 44 model parameters were incorporated based on design of experimental. …”
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Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence by Manish Sharma Timilsina, Yuvraj Chaudhary, Prikshya Bhattarai, Bibek Uprety, Dilip Khatiwada

“…Secondly, a suitable blended machine learning predictive model (with Random Forest, Gradient Boosting Regressor, and XGBoost) and robust optimization framework are developed to address model accuracy, non-linear interactions, and uncertainties in pyrolysis such as temperature, heating rate, and biomass-to-plastic ratio. …”
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Optimization of Production Scheduling for the Additive Manufacturing of Ship Models Using a Hybrid Method by Kyeongho Kim, Soonjo Kwon, Minjoo Choi

“…This paper introduces a hybrid optimization method that leverages either linear programming (LP) or a genetic algorithm (GA) based on the problem size to enhance the parallel additive manufacturing (AM) process for ship models. …”
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Structure Optimization of Mixed-Speed Train Traffic for Cyclic Timetable: Model and Algorithm Development by Jiamin Zhang, Jiarui Zhang

“…Firstly, by taking it as a job-shop problem with sequence-dependent setup times on one machine, in the type of infinite capacity resource with headway (ICR + H), the problem is transformed to alternative graph (AG) and then recast to the mixed-speed train traffic planning (MSTTP) model. …”
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Computational hybrid analysis of drug diffusion in three-dimensional domain with the aid of mass transfer and machine learning techniques by Mohammed Alqarni, Ali Alqarni

“…Hyperparameter optimization is performed using the Bacterial Foraging Optimization Algorithm (BFO) to fine-tune the models. …”
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Hybrid and optimized neural network models to estimate the elastic modulus of recycled aggregate concrete by Mingke Zheng, Jinzhao Yin, Lei Zhang, Lihua Wu, Hao Liu

“…All in all, the MLPNN model with two numbers of hidden layers with a structure of 17-14-1 optimized with AOA can be proposed as the most appropriate model. …”
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Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

“…Finally, a multi algorithm fusion learning model based on stacking technology is proposed to address the problem of poor generalization ability of single algorithm models in prediction; Furthermore, radial basis function network (RBF) was used as a two-level meta learner to fuse the above models, and particle swarm optimization (PSO) was used to optimize RBF parameters to reduce generalization error. …”
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