Wet aggregate stability modeling based on support vector machine in multiuse soils by Ruizhi Zhai, Jianping Wang, Deshun Yin, Ziheng Shangguan

“…In this work, we use the support vector machine to evaluate wet aggregate stability and compare it with a benchmark model based on artificial neural networks. …”
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A novel ensemble support vector machine model for land cover classification by Ying Liu, Lihua Huang

“…Nowadays, support vector machines are widely applied to land cover classification although this method is sensitive to parameter selection and noise samples. …”
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Developing an Extreme Learning Machine-Based Model for Estimating the Isothermal Compressibility of Biodiesel by Yue Wang, Hamid Heydari

“…Therefore, as a novel and prevailing mathematical method in this field, an extreme learning machine was implemented for isothermal compressibility on the massive dataset. …”
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Analysis and Compensation of Current Measurement Errors in Machine Drive Systems—A Review by Pingyue Song, Tao Wang, Lijian Wu, Hao Li, Xiang Meng, Cheng Li

“…Accurate measurement results, especially current measurement results, are crucial for high-performance machine drive systems. However, current measurement errors (CME) caused by circuit parameter inconsistencies, aging, and temperature variations can significantly affect the control performance of drive systems, thus necessitating compensation. …”
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Electroencephalogram-Based Emotion Classification Using Machine Learning and Deep Learning Techniques by Gst Ayu Vida Mastrika Giri, Made Leo Radhitya

“…The research shows that machine learning and deep learning can classify EEG signals to identify emotions. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Embodied neuromorphic synergy for lighting-robust machine vision to see in extreme bright by Shijie Lin, Guangze Zheng, Ziwei Wang, Ruihua Han, Wanli Xing, Zeqing Zhang, Yifan Peng, Jia Pan

“…This approach enables accurate connections between events and frames in the physics space for swift irradiance prediction, ultimately facilitating rapid control parameter updates. Our experimental results demonstrate the remarkable efficiency, low latency, superior generalization capability, and bio-inspired nature of the NEC in delivering timely and robust neuromorphic synergy for lighting-robust machine vision across a wide range of real-world applications. …”
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BIM-Based Machine Learning Application for Parametric Assessment of Building Energy Performance by Panagiotis Tsikas, Athanasios Chassiakos, Vasileios Papadimitropoulos, Antonios Papamanolis

“…Next, statistical and machine learning techniques are implemented to provide artificial models of energy performance. …”
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Innovative data techniques for centrifugal pump optimization with machine learning and AI model. by Gaurav Sandeep Dave, Amar Pradeep Pandhare, Atul Prabhakar Kulkarni, Dhananjay Vasant Khankal

“…In modern centrifugal pump machines (CPM), a data acquisition system encompassing software- hardware interfacing is essential for parameter recording. …”
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Research on Intelligent Planning Method for Turning Machining Process Based on Knowledge Base by Yante Li, Tingting Zhou

“…First, to address the heterogeneity issues in knowledge aggregation during machining processes, a process knowledge model comprising three sub-models was designed. …”
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Machine learning based prediction of specific heat capacity for half-Heusler compounds by Laxman Chaudhary, Keshab Chaudhary, Ambika Shahi, Kedar Nath Jaiswal, Dipendra Prasad Kalauni, Se-Hun Kim, Madhav Prasad Ghimire

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Real-Time Capable Thermal Model of an Automotive Permanent Magnet Synchronous Machine by Martin Stefan Baumann, Andreas Steinboeck, Wolfgang Kemmetmuller, Andreas Kugi

“…Recent publications typically utilize low-dimensional lumped-parameter thermal networks. This article presents a modeling method for a permanent magnet synchronous machine (PMSM), where the thermal model is derived using the finite-volume method. …”
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Noise-Adaptive SOGI–HOSM Observer for Sensorless Speed Control of Induction Machines by Kobena Badu Enyam, Desmond Hammond, Francis Boafo Effah, Lily Akosua Kyei-Baffour, Benecentia Mafo-Kwofie

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The quality optimization of English–Chinese machine translation based on deep neural networks by Ping Lu, Fangfang Xu

“…Abstract In the context of globalization, improving the quality of English–Chinese machine translation is crucial. This study aims to address key issues in current English–Chinese machine translation, including accuracy, fluency, and adaptability to texts from different domains. …”
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Research Progress on Process Optimization of Metal Materials in Wire Electrical Discharge Machining by Xinfeng Zhao, Binghui Dong, Shengwen Dong, Wuyi Ming

“…Wire electrical discharge machining (WEDM), as a significant branch of non-traditional machining technologies, is widely applied in fields such as mold manufacturing and aerospace due to its high-precision machining capabilities for hard and complex materials. …”
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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

“…On this basis, virtual machining is carried out, and a database containing massive parameter combinations is constructed. …”
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Optimizing UAV sprayer performance using field data and machine learning approaches by Doğan Güneş, Hideo Hasegawa

“…Statistical tests (Levene’s test, Kruskal-Wallis, and Dunn’s test) identified significant differences among experimental groups. Machine learning models (Random Forest and XGBoost) were employed to evaluate parameter importance and predict real droplet size and coverage performance. …”
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Optimizing Concrete Mix Design for Cost and Carbon Reduction Using Machine Learning by Angga T. Yudhistira, Arief S. B. Nugroho, Iman Satyarno, Tantri N. Handayani, Malindu Sandanayake, Rimba Erlangga, Jonathan Lianto, Alfa Rosyid Ernanto

“…This study aims to create an optimal concrete mixture of cost and minimal carbon emissions, but the compressive strength meets the requirements. XGBoost Machine Learning Algorithm is used to make predictions, and PSO is used to obtain the optimal mixture. …”
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Field inversion and machine learning based on the Rubber–Band Spalart–Allmaras Model by Chenyu Wu, Yufei Zhang

“…Machine learning (ML) techniques have emerged as powerful tools for improving the predictive capabilities of Reynolds-averaged Navier–Stokes (RANS) turbulence models in separated flows. …”
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ENSEMBLE RESAMPLING SUPPORT VECTOR MACHINE, MULTINOMIAL REGRESSION TO MULTICLASS IMBALANCED DATA by Laila Qadrini, Hikmah Hikmah, Elviani Tande, Ignasius Presda, Aulia Atika Maghfirah, Nilawati Nilawati, Handayani Handayani

“…The study Centres on the Utilization of Support Vector Machines (SVM) with parameter optimization using repeated cross-validation (k = 10) and the application of multinomial regression. …”
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