Digital transformation of machine technology for onion harvesting using the theory of artificial neural networks by A. V. Sibiriev, A. S. Dorokhov, A. G. Aksenov

“…Analysis of the mathematical model of the working process of onion harvesting machine showed that the increase in the quality indicators of onion harvesting can be ensured by the optimal ratio of internal unregulated parameters of separate executive devices. …”
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A New Approach to Electrical Fault Detection in Urban Structures Using Dynamic Programming and Optimized Support Vector Machines by Reynaldo Villarreal, Sindy Chamorro-Solano, Yolanda Vega-Sampayo, Carlos Alejandro Espejo, Steffen Cantillo, Luis Gaviria, Jheifer Paez, Carlos Ochoa, Silvia Moreno, Claudet Polo, Roberto Pestana-Nobles, Camilo Montoya

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Intelligent Fault Detection and Self-Healing Mechanisms in Wireless Sensor Networks Using Machine Learning and Flying Fox Optimization by Almamoon Alauthman, Abeer Al-Hyari

“…This paper presents an intelligent framework based on Light Gradient Boosting Machine integration for fault detection and a Flying Fox Optimization Algorithm in dynamic self-healing. …”
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Optimal 5G Network Sub-Slicing Orchestration in a Fully Virtualised Smart Company Using Machine Learning by Abimbola Efunogbon, Enjie Liu, Renxie Qiu, Taiwo Efunogbon

“…This paper introduces Optimal 5G Network Sub-Slicing Orchestration (ONSSO), a novel machine learning framework for dynamic and autonomous 5G network slice orchestration. …”
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Numerical Methods for Topological Optimization of Wooden Structural Elements by Daniela Țăpuși, Andrei-Dan Sabău, Adrian-Alexandru Savu, Ruxandra-Irina Erbașu, Ioana Teodorescu

“…In turn, this can be further used to train machine learning models that can embed the topologically optimized geometry and structural behavior information. …”
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Optimizing State of Charge Estimation in Lithium–Ion Batteries via Wavelet Denoising and Regression-Based Machine Learning Approaches by Mohammed Isam Al-Hiyali, Ramani Kannan, Hussein Shutari

“…This study introduces a new approach that uses wavelet denoising with a machine learning regression model to enhance SOC prediction accuracy. …”
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Method for EEG signal recognition based on multi-domain feature fusion and optimization of multi-kernel extreme learning machine by Shan Guan, Tingrui Dong, Long-kun Cong

“…Abstract In response to the current issues of one-sided effective feature extraction and low classification accuracy in multi-class motor imagery recognition, this study proposes an Electroencephalogram (EEG) signal recognition method based on multi-domain feature fusion and optimized multi-kernel extreme learning machine. Firstly, the EEG signals are preprocessed using the Improved Comprehensive Ensemble Empirical Mode Decomposition (ICEEMD) algorithm combined with the Pearson correlation coefficient to eliminate noise and interference. …”
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Assessment of soil classification based on cone penetration test data for Kaifeng area using optimized support vector machine by Hanliang Bian, Zhongxun Sun, Jiahan Bian, Zhaowei Qu, Jianwei Zhang, Xiangchun Xu

“…To enhance classification performance, 25 optimization algorithms were applied, and the models were validated against an independent dataset of 208 CPT records. …”
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OPTIMIZATION OF CALIPER BRACKET DESIGN AS AN EFFORT TO IMPROVE FUEL EFFICIENCY by Auliana Diah Wilujeng, Misbakhul Fatah, Muhammad Ridwan

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Spatial prediction and visualization of PM2.5 susceptibility using machine learning optimization in a virtual reality environment by Seyed Vahid Razavi-Termeh, Jalal Safari Bazargani, Abolghasem Sadeghi-Niaraki, X. Angela Yao, Soo-Mi Choi

“…It improves the spatially predicted accuracy of PM2.5 using Support Vector Regression (SVR) optimized with Particle Swarm Optimization (PSO). Moreover, the visualization is depicted through the VR-based application in an immersive way to comprehend PM2.5 risk maps. …”
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Optimizing predictive features using machine learning for early miscarriage risk following single vitrified-warmed blastocyst transfer by Lidan Liu, Bo Liu, Huimei Wu, Qiuying Gan, Qianyi Huang, Mujun Li

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Toward Smart Condition Monitoring of Rotatory Machines: An Optimized Probabilistic Signal Reconstruction Methodology for Fault Prediction With Multisource Uncertainties by Xiaomo Jiang, Weijian Tang, Haixin Zhao, Xueyu Cheng

“…The bandwidth parameter in the auto-associative kernel regression approach was optimized to represent the health status of the rotatory machine. …”
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Optimizing Academic Certificate Management With Blockchain and Machine Learning: A Novel Approach Using Optimistic Rollups and Fraud Detection by Khoa Tan-Vo, Khanh Pham, Phu Huynh, Mong-Thy Nguyen Thi, Thu-Thuy Ta, Thu Nguyen, Tu-Anh Nguyen-Hoang, Ngoc-Thanh Dinh, Hong-Tri Nguyen

“…The experimental outcomes validate the effectiveness of Optimistic Rollups in certificate revocation, showing a notable approximately 61.92% reduction in both transaction costs and latency. Moreover, the machine learning model displays impressive performance, achieving high accuracy in detecting fraudulent users, with an average F1-score of 99.42% and an AUC score nearing perfection. …”
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Experimental assessment and data-driven hybrid machine learning quantification with parametric optimization of compressive strength of ceramic waste concrete by Mihir Mishra, Md. Habibur Rahman Sobuz, Md. Kawsarul Islam Kabbo, M Jameel, Turki S. Alahmari, Naim Ahmad, Md. Munir Hayet Khan

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Machine learning-optimized dual-band wearable antenna for real-time remote patient monitoring in biomedical IoT systems by Umar Musa, Amor Smida, Muhammad S. Yahya, Mohamed I. Waly, Jun Jiat Tiang, Nazih Khaddaj Mallat, Surajo Muhammad, Abubakar Salisu

“…Abstract This work presents a machine learning (ML)-optimized dual-band wearable antenna designed specifically for biomedical applications in healthcare monitoring. …”
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Research on the evolution and optimization of ecological networks in arid areas based on machine learning and multi-source remote sensing data by Ruyi Pan, Jie Zhang, Wentao Xue, Qianqian Xia, Jiangxiang Liu, Junjie Yan, Hongbo Ling, Xufan Jin

“…In arid and semi-arid regions, where vegetation degradation and water stress are prevalent, improving the connectivity of ecological units is crucial for achieving optimal ecological network design. This study proposes a new methodological framework that integrates Morphological Spatial Pattern Analysis, circuit theory, and machine learning models to explore the spatiotemporal evolution and optimization of ecological networks in Xinjiang from 1990 to 2020. …”
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Blasting vibration velocity prediction of open pit mines based on GRA-EPSO-SVM model by Pengfei ZHANG, Yong YUAN, Yunhua HE, Shaojun DAI, Jiazhen LI, Xuehai CHI, Wei LI, Xue SUN, Jiao ZHANG, Runcai BAI, Honglu FEI

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Optimizing Ingredient Substitution Using Large Language Models to Enhance Phytochemical Content in Recipes by Luís Rita, Joshua Southern, Ivan Laponogov, Kyle Higgins, Kirill Veselkov

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Integrating Bioengineering and Machine Learning: A Multi-Algorithm Approach to Enhance Agricultural Sustainability and Resource Efficiency by Senthil G.A., Prabha R., Asha R.M., Suganthi S.U., Sridevi S.

“…The novel research incorporates high-level machine learning algorithms for optimizing agricultural performance regarding sustainability and resource efficiencies. …”
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Enhancing Compressive Strength Prediction in Recycled Aggregate Concrete through Robust Hybrid Machine Learning Approaches by Samuel Keown, Dylan O’Dwyer

“…To address this issue, robust hybrid machine learning (ML) approaches are employed, particularly emphasizing the Least Square Support Vector Regression (LSSVR) model. …”
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