Two-Dimensional ISAR Fusion Imaging of Block Structure Targets by Xiaoxiu Zhu, Limin Liu, Baofeng Guo, Wenhua Hu, Lin Shi, Juntao Ma

“…The algorithm further accelerates the iterative convergence speed and improves the imaging efficiency by combining the weighted back-adding residual and condition number optimization of the basis matrix. …”
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Kinematic Calibration of Industrial Robots Based on Distance Information Using a Hybrid Identification Method by Guanbin Gao, Yuan Li, Fei Liu, Shichang Han

“…The singular value decomposition (SVD) is used to eliminate the redundant parameters of the error model. To solve the problem that traditional optimization algorithms are easily affected by data noise in high dimension identification, a novel extended Kalman filter (EKF) and regularized particle filter (RPF) hybrid identification method is presented. …”
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ENHANCEMENT OF SENSOR PANEL TACTILE TOUCH INTERFACE by Oleksandr Karpin, Zinovii Liubun, Vasyl Mandziy, Oleh Tereshchuk, Nestor Hotsiy

“…Future work can focus on improving the algorithm's accuracy and robustness, as well as exploring its application in different domains.…”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…A multiple linear regression model was developed to estimate instantaneous fuel consumption (in L/100 km) using the gear predicted by the KNN algorithm and other relevant variables. …”
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A Deep Learning Method for Photovoltaic Power Generation Forecasting Based on a Time-Series Dense Encoder by Xingfa Zi, Feiyi Liu, Mingyang Liu, Yang Wang

“…Deep learning has become a widely used approach in photovoltaic (PV) power generation forecasting due to its strong self-learning and parameter optimization capabilities. In this study, we apply a deep learning algorithm, known as the time-series dense encoder (TiDE), which is an MLP-based encoder–decoder model, to forecast PV power generation. …”
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Rice Growth Parameter Estimation Based on Remote Satellite and Unmanned Aerial Vehicle Image Fusion by Jiaqi Duan, Hong Wang, Yuhang Yang, Mingwang Cheng, Dan Li

“…The vegetation indices and textural features most correlated with rice LAI and SPAD were selected using Pearson correlation analysis, and based on vegetation indices, textural features, and their combinations, regression models were established. The results indicate the following: (1) The fusion of satellite and UAV images, combined with spectral information and textural features, can significantly improve the estimation accuracy of LAI and SPAD compared to using only spectral information or textural features. (2) Sparrow search algorithm-optimized extreme gradient boosting (SSA-XGBoost) regression achieved the highest accuracy, with R² and RMSE of 0.904 and 0.183 in LAI estimation and 0.857 and 0.882 in SPAD estimation, respectively. …”
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The Development Strategy of the Multimedia Fusion Mode of Big Data Technology in Japanese Translation Teaching by Wanwan Qian

“…Starting from each aspect, optimize the automatic calibration algorithm of Japanese translation, find the best semantic relevance feature in each sentence, and realize automatic optimization, thereby improving the automatic calibration of Japanese translation machines and the registration of subject words.…”
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Flight Endurance Increasing Technology of New Energy UAV Based on a Strut-Braced Wing by Li Liu, Wencan Bai, Dun Yang

“…Surrogate model technology and multiobjective genetic algorithm are used to optimize the SBW configuration. …”
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Research Progress of Finite Element Technology in Wood Processing by Maosen Wang, Lin Yang

“…It highlights challenges such as model accuracy and algorithm optimization, suggesting that continuous improvements in FEA models and algorithms can further enhance processing efficiency and product quality. …”
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Support Vector Machine Berbasis Feature Selection Untuk Sentiment Analysis Kepuasan Pelanggan Terhadap Pelayanan Warung dan Restoran Kuliner Kota Tegal by Oman Somantri, Dyah Apriliani

“…Sentiment analysis is used to provide a solution related to this problem by applying the Support Vector Machine (SVM) algorithm model. The purpose of this research is to optimize the generated model by applying feature selection using Informatioan Gain (IG) and Chi Square algorithm on the best model produced by SVM on the classification of customer satisfaction level based on culinary restaurants at Tegal City so that there is an increasing accuracy from the model. …”
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Electric Vehicle Charging Load Forecasting Based on K-Means++-GRU-KSVR by Renxue Shang, Yongjun Ma

“…Then, a combination of kernel support vector regression (KSVR) and gated recurrent unit (GRU) models was used to handle nonlinear features and time-dependent data, where particle swarm optimization (PSO) further optimized the model parameters to improve the forecasting accuracy. …”
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Hard Example Mining Method for Visual Perception Based on Multi-sensor Fusion by Jun LIN, Wenbo PAN, Jun YOU, Yanghan XU

“…These hard samples were for training a new object detection model and remote deployment through the cloud-side collaboration mechanism to realize the optimization and iterative update of the model. …”
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Prediction of cutting depth in abrasive water jet machining of Ti-6AL-4V alloy using back propagation neural networks by Yakub Iqbal Mogul, Ibtisam Mogul, Jaimon Dennis Quadros, Ma Mohin, Abdul Aabid, Muneer Baig, Mohammad Abdul Malik

“…The results showed that as the depth of cut was small, i.e., ranging from 3 mm to 5 mm, the algorithm was unable to predict the optimized parameters, however, the prediction improved as the depth of cut increased. …”
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Real time counting method for coal mine drill pipes based on deep learning by Fukai ZHANG, Yiran SUN, Xufeng WU, Aijun LI, Peiyang LI, Dengke WANG, Guan YUAN, Shan ZHAO, Haiyan ZHANG

“…It consists of two parts: the drill recognition model Drill-YOLOv8 optimized based on AM-NT and the drill pipe counting inference algorithm Pipe Count based on two-level judgment regions. …”
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Research on wind temperature prediction of tunneling working site based on PSO−SVR by Yanhe LI, Zhijun WAN, Zhenzi YU, Hong GOU, Wanli ZHAO, Jiale ZHOU, Peng SHI, Zheng ZHEN, Yuan ZHANG

“…So PSO optimization model parameters play an important role in improving SVR fitting degree, generalization and prediction accuracy. …”
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Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods by Anton S. Chepurnenko, Tatiana N. Kondratieva, Ebrahim Al-Wali

“…Intelligent models are based on the CatBoost algorithm and implemented in the Jupyter Notebook environment in Python. …”
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Flexible Combinatorial-Bids-Based Auction for Cooperative Target Assignment of Unmanned Aerial Vehicles by Tianning Wang, Zhu Wang, Wei Li, Chao Liu

“…A comparison of the results demonstrates that the FCBA can provide comparable optimal results to a genetic algorithm but has better computational efficiency, and the reconnaissance effectiveness can be improved by considering cooperative observation.…”
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Research on temperature and humidity compensation method of vehicle gas sensor based on SCA-PSO support vector regression by Lv Yingming, Yuan Wenping

“…For a nitrogen oxide gas sensor, based on its detection principle, temperature and humidity will have a greater impact on the chemical reaction in the detection process, so a corresponding temperature and humidity compensation method is required to improve the measurement accuracy of the sensor. In this paper, a vehicle-mounted vehicle exhaust gas detection device is designed and a sensor temperature and humidity compensation method based on Support Vector Regression (SVR), Sine Cosine Algorithm(SCA) and Particle Swarm Optimization (PSO) is proposed. …”
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Prediction of Chemical Corrosion Rate and Remaining Life of Buried Oil and Gas Pipelines in Changqing Gas Field by Xianbing Li, Rui Liu, Dong Ma, Yang Bai, Yukai Shi, Badm Anhouck

“…In this paper, the corrosion rate prediction of buried oil and gas pipelines is studied in Changqing gas field. By improving the inertial weights and learning factors of the traditional particle swarm algorithm, the parameters of the generalized regression neural network are optimized and selected, and the corrosion rate prediction model of buried pipelines is finally constructed. …”
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Advancing Rice Grain Impurity Segmentation with an Enhanced SegFormer and Multi-Scale Feature Integration by Xiulin Qiu, Hongzhi Yao, Qinghua Liu, Hongrui Liu, Haozhi Zhang, Mengdi Zhao

“…To address the current challenges, a lightweight semantic segmentation algorithm for impurities based on an improved SegFormer network is proposed. …”
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