An Algorithm of Train Operation Environment Recognition Based onEmbedded GPU Platform by XIONG Minjun, LI Chen, ZHANG Huiyuan, PENG Liantie, SU Zhen

“…The instance segmentation network MaskRCNN based on deep learning is improved and trained, and the model is accelerated based on TensorRT. …”
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An efficient approach for mathematical modeling and parameter estimation of PEM fuel based on Young’s double-slit experiment algorithm by Basma S. Alqadi, Deema Mohammed Alsekait, Mohamed F. Issa, Essam H. Houssein, Fatma H. Ismail, Mokhtar Said, Nour Mostafa, Fahmi Elsayed

“…Abstract This paper introduces a novel optimization algorithm, Young’s double-slit experiment algorithm (YSDE), for accurately estimating the unknown parameters of Proton Exchange Membrane Fuel Cell (PEMFC) models. …”
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Basic principals of the tiltrotors flight control system architecture and algorithms by M. I. Myasnikov, I. R. Ilyin

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Development of an interpretable QSPR model to predict the octanol-water partition coefficient based on three artificial intelligence algorithms by Ao Yang, Shirui Sun, Lu Qi, Zong Yang Kong, Jaka Sunarso, Weifeng Shen

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A Bayesian-Optimized Surrogate Model Integrating Deep Learning Algorithms for Correcting PurpleAir Sensor Measurements by Masrur Ahmed, Jing Kong, Ningbo Jiang, Hiep Nguyen Duc, Praveen Puppala, Merched Azzi, Matthew Riley, Xavier Barthelemy

“…This study introduces BaySurcls, a Bayesianoptimised surrogate model integrating deep learning (DL) algorithms to improve the PurpleAir sensor PM2.5 (PAS2.5) measurement accuracy. …”
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Community-based COVID-19 active case finding and rapid response in the Democratic Republic of the Congo: Improving case detection and response. by John Otokoye Otshudiema, Gervais Léon Tengomo Folefack, Justus M Nsio, Cathy H Kakema, Luigino Minikulu, Aimé Bafuana, Joel B Kosianza, Antoine K Mfumu, Edith Nkwembe, Yannick Munyeku-Bazitama, Sheila Makiala-Mandanda, Noé Guinko, Gisèle Mbuyi, Jean-Marie K Tshilumbu, Guy N Saidi, Moreau-Serge Umba-di-Masiala, Amos K Ebondo, Jean-Jacques Mutonj, Serge Kalombo, Jad Kabeya, Taty K Mawanda, Faustin N Bile, Gaby K Kasereka, Placide Mbala-Kingebeni, Steve Ahuka-Mundeke, Humphrey Cyprian Karamagi, Karl Njuwa Fai, Amédée Prosper Djiguimde

“…This pilot study was modeled on the DRC's National COVID-19 Response Plan and the COVID-19 Ag-RDT screening algorithm defined by the World Health Organization (WHO), with case findings implemented in 259 health areas, 39 health zones, and 9 provinces. …”
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Presenting a Prediction Model for CEO Compensation Sensitivity using Meta-heuristic Algorithms (Genetics and Particle Swarm) by Saeed Khaljastani, Habib Piri, Reza Sotoudeh

“…Given these points, the aim of this research is to provide a model for predicting the sensitivity of CEO compensation using meta-heuristic algorithms, specifically genetic algorithms and particle swarm optimization. …”
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A Multi-Algorithm Machine Learning Model for Predicting the Risk of Preterm Birth in Patients with Early-Onset Preeclampsia by Xu Y, Zu Y, Zhang Y, Liang Z, Xu X, Yan J

“…The ensemble prediction model demonstrates the best predictive performance, helping obstetricians identify high-risk patients and perform early intervention to improve perinatal outcomes.Keywords: machine learning, preterm birth, early-onset preeclampsia, clinical prediction model…”
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Algorithm of passive “Beidou”/INS closed-loop integrated using two level filter by GAO Fa-qin, TAN Zhan-zhong

“…One scheme of integrated navigation Kalman filter positioning algorithm was put forward to apply to “Beidou” and INS（intertial navigation system）.Using the pseudo-range’s velocity of changing as observations,on the basis of the high stable clock,a closed loop Kalman filtering model that can revise the attitude error of INS was put out,its biggest optimism was that it could change between the close-loop method and open-loop method steadily.Finally,by computer simulation,it explain that our scheme improve the positioning precision effectively when the satellites in sight are less then two ones,and it also show that our scheme can revise the attitude error of INS effectively and estimate the user’s velocity in high precision.…”
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Improving resectable gastric cancer prognosis prediction: A machine learning analysis combining clinical features and body composition radiomics by Gianni S.S. Liveraro, Maria E.S. Takahashi, Fabiana Lascala, Luiz R. Lopes, Nelson A. Andreollo, Maria C.S. Mendes, Jun Takahashi, José B.C. Carvalheira

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Enhanced genetic algorithm for indoor low-illumination stereo matching energy function optimization by Zhang Hongjin, Wei Hui

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Numerical Assessment of Automotive Mufflers Using FEM, Neural Networks, and a Genetic Algorithm by Ying-Chun CHANG, Min-Chie CHIU, Meng-Ru WU

“…With this, the muffler’s optimization can proceed by linking the objective function to an optimizer, a Genetic Algorithm (GA). Consequently, the discharged muffler which is optimally shaped will improve the automotive exhaust noise.…”
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Optimizing a Hybrid Controller for Automotive Active Suspension System by Using Genetic Algorithms With Two High Level Parameters by Vu Van Tan, Do Trong Tu, Nguyen Van Vinh, Pham Tat Thang, Andras Mihaly, Peter Gaspar

“…Specifically, the ride comfort has improved from 60% to 80%, while the road holding has improved from 10% to 15%. …”
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Improving ecosystem respiration estimates for CO2 flux partitioning by discriminating water and temperature controls on above- and below-ground sources by Shuai Wang, Shujing Qin, Lei Cheng, Kaijie Zou, Chenhao Fu, Pan Liu, Lu Zhang

“…Empirical models for estimating ecosystem respiration (ER) are widely used in CO2 flux partitioning algorithms that partition net ecosystem CO2 exchange (NEE) into gross primary productivity (GPP) and ER due to advantages of simple structures. …”
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Hybrid Machine Learning Model for Predicting Shear Strength of Rock Joints by Daxing Lei, Yaoping Zhang, Zhigang Lu, Hang Lin, Yifan Chen

“…To address these challenges, this study proposes a hybrid ML model that integrates a multilayer perceptron (MLP) with the slime mold algorithm (SMA), termed the SMA-MLP model. …”
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‌Rockburst intensity grading prediction based on the LOF-ENN-KNN model‌ by Haoran Ge, Jiyong Zhang, Congbo Ma, Kai Hui, Yicong Li, Ziniu Wu

“…Through the comparison and exploration of different sampling methods and different combinations of LOF algorithm, single resampling technology (SMOTE, ADASYN) or simple technology superposition (LOF-SMOTE, LOF-ADASYN) is easy to introduce over-fitting or negative coupling effect, while LOF-ENN-KNN significantly improves the robustness and generalization ability of the model through modular design. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…Finally, the integrated prediction combining fluctuation and random terms under condition 5 yielded R2 of 0.87 and 0.93 for the overall prediction at Ankang and Baihe stations, respectively, demonstrating excellent model performance. [Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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A Probabilistic Linguistic Large-Group Emergency Decision-Making Method Based on the Louvain Algorithm and Group Pressure Model by Zhiying Wang, Hanjie Liu, Ruohan Ma

“…To tackle preference conflicts and uncertainty in large-group emergency decision-making (LGEDM), this study proposes a probabilistic linguistic LGEDM method integrating the Louvain algorithm and group pressure model. First, expert weights are determined based on a social trust network, and the Louvain algorithm is employed for expert clustering, reducing the complexity of large-scale decision information. …”
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YOLO-LSM: A Lightweight UAV Target Detection Algorithm Based on Shallow and Multiscale Information Learning by Chenxing Wu, Changlong Cai, Feng Xiao, Jiahao Wang, Yulin Guo, Longhui Ma

“…Focaler inner IoU is incorporated to improve bounding box matching and localization, thereby accelerating model convergence. …”
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Novel CP model and CP-assisted meta-heuristic algorithm for flexible job shop scheduling with preventive maintenance by Lixin Zhao, Leilei Meng, Weiyao Cheng, Yaping Ren, Biao Zhang, Hongyan Sang

“…Finally, the experimental evaluation on benchmark instances validates the capability of the CP model and CVNSQ-CP. Specifically, compared with existing mathematical models, the proposed CP model proves 3 new optimal solutions and improves 11 current best-known solutions for FJSP-FPM, and it improves 13 current best-known solutions for FJSP-PPM. …”
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