Mixed Time/Event-Triggered Model Predictive Tracking Control for Networked Mobile Robots by Huixin Liu, Yonghua Lai, Hongsong Lian, Guobin Wang, Dongsheng Zheng

“…The MPC algorithm is developed based on the auxiliary optimization problem (OP), which is constrained by linear matrix inequalities. …”
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Sensorless Control of Ultra-High-Speed PMSM via Improved PR and Adaptive Position Observer by Xiyue Bai, Weiguang Huang, Chuang Gao, Yingna Wu

“…To improve the precision of the position and speed estimation in ultra-high-speed (UHS) permanent magnet synchronous motors (PMSM) without position sensors, multiple refinements to the traditional extended electromotive force (EEMF) estimation algorithm are proposed in this paper. …”
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FedDBO: A Novel Federated Learning Approach for Communication Cost and Data Heterogeneity Using Dung Beetle Optimizer by Dongyan Wang, Limin Chen, Xiaotong Lu, Yidi Wang, Yue Shen, Jingjing Xu

“…This paper proposes a federated learning approach based on the dung beetle optimizer, named FedDBO. In this method, the model parameters uploaded from clients to the server are transformed into model scores. …”
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A Bi-level Stochastic-Robust Optimal Bidding Model of Wind-Storage System in Spot Markets Considering Internal and External Uncertainties by Haowen Xu, Minglei Bao, Xun Yao, Xiaocong Sun, Yi Ding, Zhenglin Yang

“…The proposed model is structured as a bi-level optimization problem to reflect the interaction between WSS bidding and day-ahead market clearing. …”
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Two-Stage Dispatch of CCHP Microgrid Based on NNC and DMC by Suhao CHEN, Yue WU, Wei ZENG, Xiaohui YANG, Xiaopeng WANG, Yunfei WU

“…In the online optimization stage, a finite-time domain optimization model based on dynamic matrix control algorithm is established to track and optimize the offline optimization results with feedback correction to reduce the influence of uncertainty factors. …”
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Balanced operation strategies of district heating systems based on dynamic hydraulic-thermal modeling by Xiaojie Lin, Ning Zhang, Zheng Luo, Encheng Feng, Wei Zhong

“…For the primary side network in the various operation conditions, the dynamic hydraulic-thermal model is established. The heating supply imbalance of the primary side return temperatures among different heating substations is defined and optimized based on the dynamic hydraulic-thermal model and the particle swarm optimization algorithm. …”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Subsequently, both classical and quantum-inspired models are trained and optimized. The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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Intelligent decision-making and regulation method of gas extraction “borehole-pipe network” system by Kai WANG, Dongxu WANG, Aitao ZHOU, Junwen ZHANG, Fangzhou SONG, Chang’ang DU, Yushuang HAO, Xihui FAN, Wei ZHAO

“…Based on the improved particle swarm optimization algorithm, the intelligent optimization decision-making and regulation model of pipeline network is constructed. …”
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A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization by Songping He, Xiangxi Li, Fangyu Peng, Jiazhi Liao, Xia Lu, Hui Guo, Xin Tan, Yanyan Chen

“…Among the machine learning methods used for modelling, the prediction results of the tree model are improved to a certain degree after the error-correcting output code optimization. …”
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Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction by Ruijie Zhu, Fengtian Yang, Xiaocheng Zhou, Jiao Tian, Yongxian Zhang, Miao He, Jingchao Li, Jinyuan Dong, Ying Li

“…Additionally, including sampling time in the data sets significantly improves the model's predictive performance. However, it is important to note that the model's predictive performance varies across different hot spring and indicators type, highlighting the importance of identifying optimal indicators for specific scenarios. …”
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Optimized fiducial marker placement using B‐spline surface modeling and graph theory for Cyberknife stereotactic body radiotherapy for superficial tumors by Jing Huang, Xianlong Xiong, Cheng Chen, Yuhan Li, Ruijie Wang, Zhitao Dai

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The open-closed mod-minimizer algorithm by Ragnar Groot Koerkamp, Daniel Liu, Giulio Ermanno Pibiri

“…Abstract Sampling algorithms that deterministically select a subset of $$k$$ k -mers are an important building block in bioinformatics applications. …”
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Game algorithm based on link quality: Wireless sensor network routing game algorithm based on link quality by Zhanjun Hao, Jiaojiao Hou, Jianwu Dang, Xiaochao Dang, Nanjiang Qu

“…In the simulation experiment, the influence of the change of link quality parameters on the performance of the algorithm is analyzed, and the proposed algorithm is compared with non-linear weight particle swarm optimization (NWPSO) algorithm and Low Energy Adaptive Clustering Hierarchy-Improvement (LEACH-IMPT) algorithm in three aspects: the number of surviving nodes, network lifetime, and network energy consumption. …”
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Optimized Dual-Battery System with Intelligent Auto-Switching for Reliable Soil Nutrient Monitoring in Remote IoT Applications by Doan Perdana, Pascal Lorenz, Bagus Aditya

“…To further assess long-term performance under continuous Internet of Things (IoT) operation, a simulation framework was developed in MATLAB/Simulink, incorporating battery degradation models and empirical sensor load profiles. The experimental results reveal distinct performance improvements. …”
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Control parameter identification method for virtual synchronous generator considering electric vehicles based on dynamic particle swarm optimization by Dongqi Wu, Yong Hu

“…By constructing a VSG inverter control model suitable for distributed power sources and EV charging systems, analyzing the interactions between active and reactive power control loops under EV integration scenarios, selecting parameters and observations to be identified, and improving the Particle Swarm Optimization (PSO) algorithm based on actual conditions, the method ensures enhanced system adaptability. …”
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Research on fault diagnosis of amorphous alloy transformers by using vibration signals and a PSO-optimized full-process WPT-SVM model by Daosheng Liu, Wentao Yang, Longsheng Liu, Zhe Zhao

“…Overall, the full-process optimization significantly improves AMT fault diagnosis efficiency compared with single-aspect optimization.…”
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Dimensional Accuracy Analysis of Splined Shafts and Hubs Obtained by Fused-Deposition Modeling 3D Printing Using a Genetic Algorithm and Artificial Neural Network by Alin-Daniel Rizea, Cristina-Florena Banică, Tatiana Georgescu, Alexandru Sover, Daniel-Constantin Anghel

“…Three-dimensional printing, especially FDM, enables fast production of customized components with complex geometries, reducing material waste and costs. Optimized printing parameters improve dimensional accuracy and performance. …”
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Development platform for artificial pancreas algorithms. by Mohamed Raef Smaoui, Remi Rabasa-Lhoret, Ahmad Haidar

“…<h4>Results</h4>The platform facilitates development by solving the ODE model in the cloud on large CPU-optimized machines, providing a 62% improvement in memory, speed and CPU utilization. …”
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Optimization Study of Multidimensional Computational Model for Distribution Network Cable Fault Location and Hidden Danger Warning System in Smart Grid Environment by Xin Li, Jiyou Wang, Minghui Liu

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Comparison of Doubling the Size of Image Algorithms by S. E. Vaganov, S. I. Khashin

“…However, these improvements are insignificant for complex algorithms (17-point interpolation, Lanczos a=3). …”
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