Predicting the Matching Possibility of Online Dating Youths Using Novel Machine Learning Algorithm by Karthikeyan Palanisamy, Muthumani Muralidharan

“…This research project aims to gain insights into forecasting the course of relationships created during initial meetings using cutting-edge Machine Learning (ML) approaches. Light Gradient Boosting Classification (LGBC) serves as a foundational framework, and an innovative approach is introduced by combining it with the Henry Gass Solubility Optimization Algorithm (HGSOA), Flying Fox Optimization (FFO), and Mayflies Optimization (MO), resulting in a hybrid model. …”
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Optimization method of electric vehicle energy system based on machine learning by Huanmei Ren

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Improved Butterfly Optimizer-Configured Extreme Learning Machine for Fault Diagnosis by Helong Yu, Kang Yuan, Wenshu Li, Nannan Zhao, Weibin Chen, Changcheng Huang, Huiling Chen, Mingjing Wang

“…The model is mainly based on an improved butterfly optimizer algorithm- (BOA-) optimized kernel extreme learning machine (KELM) model. …”
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Optimized Machine Learning for the Early Detection of Polycystic Ovary Syndrome in Women by Bharti Panjwani, Jyoti Yadav, Vijay Mohan, Neha Agarwal, Saurabh Agarwal

“…The hyperparameters of the EL model were optimized through the nature-inspired walrus optimization (WaO), cuckoo search optimization (CSO), and random search optimization (RSO) algorithms, leading to the WaOEL, CSOEL, and RSOEL models, respectively. …”
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Machine Learning with Tunicate Swarm Optimization for Improved Disc Herniation Prediction by Theofilos Gofas, Argyros Maris

“…Additionally, Tunicate Swarm Optimization (TSO) is integrated to enhance the accuracy of all three models—NBC, ETC, and LRC. …”
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Optimizing Data Classification in Support Vector Machines Using Metaheuristic Algorithms by Qonita Ilmi Awalin, Ika Hesti Agustin, Alfian Futuhul Hadi, Dafik Dafik, R. Sunder

“…This finding suggests that PSO-based hyperparameter optimization yields a superior model for data classification…”
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Optimizing Renewable Energy Integration Using IoT and Machine Learning Algorithms by Orken Mamyrbayev, Ainur Akhmediyarova, Dina Oralbekova, Janna Alimkulova, Zhibek Alibiyeva

“…Due to their inherent variability, incorporating renewable energy sources into current power grids poses major challenges. This study aims to optimize renewable energy integration using Internet of Things (IoT) technology and machine learning (ML) algorithms. …”
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Purchasing Prediction Using Machine Learning Algorithms for Optimizing Inventory Management by Reza Hamdi Prayetno, Rani Destika Purba, Kyrene Wirawan, Kelvin Sweet, Evta Indra

“…The model successfully captured seasonal patterns and trends in sales data, proving its ability to forecast stock requirements. …”
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FPCB STIFFENER ADHESIVE MACHINE DYNAMIC PERFORMANCE OPTIMIZATION AND ACCURACY ANALYSIS by MEI LingLiang, LIN XiaoXia, MEI XueSong

“…Aiming at the problem of the FPCB（ flexible printed circuit board） stiffener adhesive machine performance optimization,applying the finite element method,a FEA model of the FPCB stiffener adhesive machine has been set up. …”
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Recent Advances in Optimization Methods for Machine Learning: A Systematic Review by Xiaodong Liu, Huaizhou Qi, Suisui Jia, Yongjing Guo, Yang Liu

“…This systematic review explores modern optimization methods for machine learning, distinguishing between gradient-based techniques using derivative information and population-based approaches employing stochastic search. …”
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An optimize canny algorithm with traditional machine learning for edge detection enhancement by Russel Lafta, Zainab Sultani

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Optimization of microwave components using machine learning and rapid sensitivity analysis by Slawomir Koziel, Anna Pietrenko-Dabrowska

“…The global optimization phase is complemented by local tuning. Verification experiments demonstrate the remarkable efficacy of the presented approach and its advantages over the benchmark methods that include machine learning in full-dimensionality space and population-based metaheuristics.…”
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Hyperparameter Optimization of ANN, SVM, and KNN Models for Classification of Hazelnuts Images Based on Shell Cracks and Feature Selection Method by H. Bagherpour, F. Fatehi, A. Shojaeian, R. Bagherpour

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Optimizing water management and climate-resilient agriculture in rice-fallow regions of the Dwarakeswar river basin using ML models by Chiranjit Singha, Satiprasad Sahoo, Ajit Govind

“…This study analyzed soil moisture and GWL behavior in rice fallows along the Dwarakeswar River, India, using Sentinel-2, Landsat 8 OLI (2019–2022), and TerraClimate (1958–2022) datasets. Machine learning models—Random Forest (RF), Extreme Gradient Boosting (XGB), and Multivariate Adaptive Regression Splines (MARS)—were applied to predict boro rice-fallows, soil moisture, and GWL. …”
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Uneven air gap optimization of synchronous machine with permanent rotor magnets by V. V. Kharlamov, Yu. V. Moskalev, A. Yu. Milutin, A. P. Popov

“…As a result of modeling the magnetic field of an electric machine with a calculated optimal uneven air gap, a distribution curve of the normal component of magnetic induction along the inner circumference of the stator is obtained, the average deviation of which from the sinusoidal curve is 4,8 %.…”
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Enhancing Predictive Accuracy of Landslide Susceptibility via Machine Learning Optimization by Chuanwei Zhang, Dingshuai Liu, Paraskevas Tsangaratos, Ioanna Ilia, Sijin Ma, Wei Chen

“…A correlation analysis was conducted to examine the relationship between the conditioning factors and landslide occurrence, and the certainty factor method was applied to assess their influence. Beyond model comparison, the central focus of this research is the optimization of machine learning parameters to enhance prediction reliability and spatial accuracy. …”
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Diagnosis by SAM Linked to Machine Vision Systems in Olive Pitting Machines by Luis Villanueva Gandul, Antonio Madueño-Luna, José Miguel Madueño-Luna, Miguel Calixto López-Gordillo, Manuel Jesús González-Ortega

“…In this study, we explore the use of the Segment Anything Model (SAM), a pre-trained neural network developed by META AI in 2023, as an alternative for industrial segmentation tasks in the table olive (<i>Olea europaea</i> L.) processing industry. …”
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Optimization of Selective Laser Sintering Processing Parameters Based on ISMA-ELM Hybrid Model by LI Jian, NIE Qian, JIANG Chenglei, GUO Yanling, WANG Yangwei

“…Finally, the optimal processing parameters predicted by the ISMA-ELM model are used to guide the machining, and the dimensional accuracy of the obtained molded parts is improved by 29. 62% compared to the ELM model and 18. 02% compared to the SMA-ELM, which shows that the model can provide optimal process parameters for SLS molding processing and guide the machining effectively.…”
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Optimizing Curriculum for Students: A Machine Learning Approach to Time Management Analysis by Jianmin Dong

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Accelerating antibody discovery and optimization with high-throughput experimentation and machine learning by Ryo Matsunaga, Kouhei Tsumoto

“…We illustrate how machine learning models, including protein language models, are used not only to enhance affinity but also to optimize other crucial therapeutic properties, such as specificity, stability, viscosity, and manufacturability. …”
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