Design and Modellingof a Pneumatic Vice Machine by Talemwa, Prosper

“…The design focuses on optimizing the pneumatic actuator mechanism to ensure consistent performance under varying load conditions. …”
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Multi-scale computational fluid dynamics and machine learning integration for hydrodynamic optimization of floating photovoltaic systems by Fadhil Khadoum Alhousni, Samuel Chukwujindu Nwokolo, Edson L. Meyer, Theyab R. Alsenani, Humaid Abdullah Alhinai, Chinedu Christian Ahia, Paul C. Okonkwo, Yaareb Elias Ahmed

“…Abstract This paper presents a new and multidisciplinary systematic analysis of floating photovoltaic (FPV) systems that integrates recent advances in computational modelling and intelligent optimization to address persistent issues with performance, hydrodynamics, and adaptability. …”
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Optimization of fabric’s tensile strength and bagging deformation using surface response and finite element in stenter machine by Tavangar Fatemeh, Abghari Ramin, Mirjalili Mohammad, Amiri Hamidreza

“…Optimization of fabric’s mechanical properties, such as strength and bagging deformation of worsted fabrics, is considered one of the most important cases in relation to the use of stenter machine. …”
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Machine learning enhanced metal 3D printing: high throughput optimization and material transfer extensibility by Yuanjie Zhang, Cheng Lin, Yuan Tian, Jianbao Gao, Bo Song, Hao Zhang, Min Wang, Kechen Song, Binghui Deng, Dezhen Xue, Yonggang Yao, Yusheng Shi, Kun Kelvin Fu

“…The high throughput methodologies are mostly on obtaining the printed samples and their structural and physical properties, while ML is used for data analysis by model building for prediction (optimization), and understanding. …”
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Optimized Fake News Classification: Leveraging Ensembles Learning and Parameter Tuning in Machine and Deep Learning Methods by Abubaker A. Alguttar, Osama A. Shaaban, Remzi Yildirim

“…This study offers insights into model selection and optimization.…”
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Optimizing Solid Rocket Missile Trajectories: A Hybrid Approach Using an Evolutionary Algorithm and Machine Learning by Carlo Ferro, Matteo Cafaro, Paolo Maggiore

“…This paper introduces a novel approach for modeling and optimizing the trajectory and behavior of small solid rocket missiles. …”
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Particle Swarm Optimization Support Vector Machine-Based Grounding Fault Detection Method in Distribution Network by Zhongqin Xiong, Shichang Huang, Shen Ren, Yutong Lin, Zewen Li, Dongyu Li, Fangming Deng

“…In this paper, a particle swarm optimization (PSO) support vector machine (SVM)-based grounding fault detection method is proposed for distribution networks. …”
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Laser powder bed fusion process optimization of CoCrMo alloy assisted by machine-learning by Haoqing Li, Bao Song, Yizhen Wang, Jingrui Zhang, Weihong Zhao, Xiaoying Fang

“…Gaussian process regression (GPR) model of machine learning method was employed to identify the optimal process window for high-performance CoCrMo alloy in laser powder bed fusion (LPBF), considering density (≥99%) and surface roughness (≤7 μm) as key parameters. …”
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Genetic algorithm–optimized support vector machine for real-time activity recognition in health smart home by Yan Hu, Bingce Wang, Yuyan Sun, Jing An, Zhiliang Wang

“…In addition, the genetic algorithm is used to automatically select optimal hyperparameters for the support vector machine model, thereby reducing the recognition inaccuracy caused by manual tuning of hyperparameters. …”
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The Design and Optimization of Additively Manufactured Windings Utilizing Data Driven Algorithms for Minimal Loss in Electric Machines by John McKay, Jill Miscandlon, Tatyana Konkova

“…The optimisation process consists of sensitivity analysis utilising an efficient hybrid 2D FEA-Analytical model, meta-modelling and genetic algorithm to search the design space for optimal winding designs. …”
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Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning by Shaojie Li, Zaixing Dong, Jianfeng Jin, Hucheng Pan, Zongqing Hu, Rui Hou, Gaowu Qin

“…The SVR model combined with multi‐objective genetic algorithm are successfully used to optimize mechanical properties of four extruded alloys from Mg‐Ca, Mg‐Ca‐Zn, Mg‐Ca‐Mn‐Sn, and Mg‐Ca‐Al‐Zn‐Mn series alloys, respectively, and the corresponding experimental results are in good agreement with the designed ones. …”
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Optimizing machine learning algorithms for diabetes data: A metaheuristic approach to balancing and tuning classifiers parameters by Hauwau Abdulrahman Aliyu, Ibrahim Olawale Muritala, Habeeb Bello-Salau, Salisu Mohammed, Adeiza James Onumanyi, Ore-Ofe Ajayi

“…Diabetes mellitus poses a global health concern, prompting the development of machine learning algorithms designed to construct a model for the accurate classification of patients, enabling precise diagnoses and early-stage treatment. …”
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Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli, Rani Kumari, Adnan Akhunzada, Korhan Cengiz, Santosh Kumar Sharma, Rakesh Ranjan Kumar, Dinesh Kumar Sah

“…Lastly, a newly improved learning algorithm encompasses a modified pelican optimization algorithm (MOD-POA) and an extreme learning machine (ELM) for classification tasks. …”
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Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques by Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif

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Construction and validation of prognostic model for ICU mortality in cardiac arrest patients: an interpretable machine learning modeling approach by Yong Li, Ying Liu, Qing Zhang, Hongwei Zhu, Chengli Wen, Xian Jiang

“…We developed interpretable machine learning models for early prediction of ICU mortality risk in patients diagnosed with CA. …”
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Optimized Flare Performance Analysis Through Multi-Modal Machine Learning and Temporal Standard Deviation Enhancements by Said Boumaraf, Pengfei Li, Muaz Al Radi, Fares Oussama Abdelhafez, Abderaouf Behouch, Khalid Yousef Al Awadhi, Hamad Karki, Sajid Javed, Jorge Dias, Naoufel Werghi

“…A CatBoost regression model is then trained on this dataset to estimate the final CE. …”
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Real‐Time Self‐Optimization of Quantum Dot Laser Emissions During Machine Learning‐Assisted Epitaxy by Chao Shen, Wenkang Zhan, Shujie Pan, Hongyue Hao, Ning Zhuo, Kaiyao Xin, Hui Cong, Chi Xu, Bo Xu, Tien Khee Ng, Siming Chen, Chunlai Xue, Zhanguo Wang, Chao Zhao

“…Abstract Traditional methods for optimizing light source emissions rely on a time‐consuming trial‐and‐error approach. …”
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An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…Currently, more and more intrusion detection systems based on machine learning and deep learning are being applied to SDN, but most have drawbacks such as complex models and low detection accuracy. …”
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Antenna Optimization Design Based on Deep Gaussian Process Model by Xin-Yu Zhang, Yu-Bo Tian, Xie Zheng

“…When using Gaussian process (GP) machine learning as a surrogate model combined with the global optimization method for rapid optimization design of electromagnetic problems, a large number of covariance calculations are required, resulting in a calculation volume which is cube of the number of samples and low efficiency. …”
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Impact Assessment of Coupling Mode of Hydrological Model and Machine Learning Model on Runoff Simulation: A Case of Washington by Junqi Zhang, Jing Li, Huiyizhe Zhao, Wen Wang, Na Lv, Bowen Zhang, Yue Liu, Xinyu Yang, Mengjing Guo, Yuhao Dong

“…Combining machine learning models with traditional hydrological models is an essential approach to enhancing the runoff modeling capabilities of hydrological models. …”
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