Disturbance Observer-Based Optimal Active Suspension Control for Vehicle-Trailer Systems by Yonghwan Jeong

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A hybrid Bayesian network-based deep learning approach combining climatic and reliability factors to forecast electric vehicle charging capacity by David Chunhu Li

“…This architecture uses extensive transaction data and climate analysis to build a detailed model of EV charging pile reliability. Additionally, two algorithms are designed to assess the usage and reliability of charging stations. …”
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Clean energy supply chain optimization: Steady-state natural gas transportation by Zhongfu Liu, Shuiying Xu, Shihao Zhao, Yuewen Li, Meiling Zhou, Shuosen Li, Fei Meng

“…To address these issues, a mixed-integer nonlinear optimization model is developed, and by linearizing the nonlinear equations, a sequential linear programming algorithm is proposed, iteratively updating the hydraulic parameters. …”
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Improving meningitis surveillance and diagnosis with machine learning: Insights from São Paulo. by Audêncio Victor, Diego Augusto Medeiros Santos, Eduardo Koerich Nery, Danilo Pereira Mori, Pamella Cristina de Carvalho Lucas, Denise Cammarota, Guillermo Leonardo Florez Montero, Fabiano Novaes Barcellos Filho, Ana Lúcia Frugis Yu, Telma Regina Marques Pinto Carvalhanas

“…These techniques can be integrated into public health protocols to improve meningitis outbreak responses and optimize patient treatment.…”
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Point Data Registration With the Multi-Object, Cardinalized Optimal Linear Assignment Metric by Pablo A. Barrios, Vicente Guzman, Martin D. Adams, Claudio A. Perez

“…The Iterative Closest Point (ICP) algorithm and its variants were initially used to solve such problems and since then, various global methods have been proposed to improve registration when data outliers exist. …”
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Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu, Zhenhua Wei

“…It reduces trial-and-error efforts and supports mix design optimization. Currently, machine learning is more adept at handling complicated datasets than experimental and traditional statistical models. …”
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Optimal relay selection for full duplex SWIPT-NOMA systems with maximal throughput by Taoshen LI, Anni SHI, Zhe WANG, Lu HE

“…To improve the performance of 5G communication system, a full duplex Internet of things (IoT) relay system model was built by introducing the non-orthogonal multi-access (NOMA) technology.For the relay system of simultaneous wireless information and power transfer (SWIPT), it was considered that the relay node can harvest the energy of the source node, the self-interference signal of the loop channel and the free energy access point (EAP), and NOMA technology was used to forward the source node signal and its own signal to different destination nodes.Based on the model, a power distribution collaboration SWIPT relay selection strategy was proposed to optimize system throughput.Firstly, the problem model was established based on the constraints of communication quality of service and transmission power of source nodes.And then, the original nonlinear 0-1 programming problem was converted into a pair of coupling optimization problem by mathematical transformation, and the optimal relay selection of outer optimization problem was solved based on the optimal solution of the internal optimization problem.Finally, an optimal relay selection algorithm was used to maximize system throughput.Simulation results show that the proposed model and strategy are superior to the traditional maximum-minimum relay selection schemes in terms of throughput gain, and the consideration of EAP can significantly improve the interrupt performance.…”
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Optimal relay selection for full duplex SWIPT-NOMA systems with maximal throughput by Taoshen LI, Anni SHI, Zhe WANG, Lu HE

“…To improve the performance of 5G communication system, a full duplex Internet of things (IoT) relay system model was built by introducing the non-orthogonal multi-access (NOMA) technology.For the relay system of simultaneous wireless information and power transfer (SWIPT), it was considered that the relay node can harvest the energy of the source node, the self-interference signal of the loop channel and the free energy access point (EAP), and NOMA technology was used to forward the source node signal and its own signal to different destination nodes.Based on the model, a power distribution collaboration SWIPT relay selection strategy was proposed to optimize system throughput.Firstly, the problem model was established based on the constraints of communication quality of service and transmission power of source nodes.And then, the original nonlinear 0-1 programming problem was converted into a pair of coupling optimization problem by mathematical transformation, and the optimal relay selection of outer optimization problem was solved based on the optimal solution of the internal optimization problem.Finally, an optimal relay selection algorithm was used to maximize system throughput.Simulation results show that the proposed model and strategy are superior to the traditional maximum-minimum relay selection schemes in terms of throughput gain, and the consideration of EAP can significantly improve the interrupt performance.…”
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Low-carbon economic dispatch based on improved ISODATA scenario reduction for wind power in IES by Yuangen HUANG, Xingyu LIU, Tianran LI, Zhenya JI, Wei XU

“…Then, an integrated energy model is established and it optimized using an improved stepwise carbon trading and power to gas and carbon capture system (P2G-CCS) coupling model. …”
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Stowage Plan Based Slot Optimal Allocation in Rail-Water Container Terminal by Yanjing Li, Xiaoning Zhu, Li Wang, Xi Chen

“…To obtain an efficient and reasonable solution for slot allocation in rail-water container terminals, this paper develops storage optimal allocation model 1 to improve the yard space utilization, which is solved by a heuristic algorithm based on Tabu search. …”
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APG mergence and topological potential optimization based heuristic user association strategy by Zhirui HU, Meihua BI, Fangmin XU, Meilin HE, Changliang ZHENG

“…Methods:The network scalable degree was designed as a measure of scalability,and then a user association strategy to improve network scalable degree was studied by using optimization theory. 1) For modelling the optimization problem, firstly, the network coupling degree, representing the degree of association among nodes, was constructed to establish the mathematical relationship between the network scalable degree and AP group (APG).Thus,the problem of improving the network scalable degree was modeled as the problem of minimizing the network coupling degree.Then,a multi-objective optimization problem of minimum network coupling degree and maximum user rate was established to find the balance between network scalable degree and network service quality. 2) For solving the optimization problem,to avoid the high computational complexity,a heuristic user association strategy based on APG mergence and topological potential optimization was proposed.With the proposed algorithm,the number of APG could be reduced by APG mergence,and the number of APG that AP belongs to could be reduced by AP exiting APG. …”
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Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

“…To strengthen trust evaluation, the framework combines an optimized Levenberg algorithm with the Firefly Algorithm. …”
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Simulation Analysis of RES System Optimization Strategy of Range-extended Electric Vehicle by Xing Zhongyi

“…Based on the working modes of the transmission system of range-extended electric vehicle,the map of internal combustion engine and battery system characters are obtained through calculation,the main components of transmission are set up in Matlab on the basis of dynamics equation,and the model is analyzed,the genetic algorithm is combined into control strategy in order to optimize the start-close area of range extended system.The simulation results show that the optimized strategy can not only improve the fluctuation range of SOC,but also improve the fuel consumption of transmission system.…”
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Design optimization of university ideological and political education system based on deep learning by Shangle Ai, Huanhuan Ding

“…Firstly, this paper introduces the research methods in detail, including deep learning algorithm and model design, as well as the optimization design process of IPE system. …”
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Impact of Network Configuration on Hydraulic Constraints and Cost in the Optimization of Water Distribution Networks by Mojtaba Nedaei

“…Further, a new approach based on the Coral Reef Algorithm (CRA) is developed and implemented to improve the technical and economic viability of the designed WDNs. …”
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Optimal sensor placement of bridge structure based on sensitivity‐effective independence method by Wenhao Chai, Yaxun Yang, Haibo Yu, Fuli Yang, Zhikui Yang

“…Abstract Taking the optimal sensor placement problem in bridge structural health monitoring as the study object and relying on the engineering example of a simply supported steel truss bridge, the improved optimal sensor placement method based on sensitivity‐effective independence method was proposed. …”
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Random Forest-Based Prediction of the Optimal Solid Ink Density in Offset Lithography by Laihu Peng, Hao Fan, Yubao Qi, Jianqiang Li

“…To improve the efficiency of determining the optimal solid ink density, the Random Forest algorithm was applied for the first time to the prediction task of solid ink density in offset printing. …”
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Improved Motion Correction in Dynamic Contrast-Enhanced MRI Using Low Rank With Soft Weighting by Jichang Zhang, Faisal Najeeb, Yulin Wang, Xinpei Wang, Pengfei Xu, Hammad Omer, Jianjun Zheng, Jingfeng Zhang, Sue Francis, Paul Glover, Richard Bowtell, Thomas Meersmann, Chengbo Wang

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An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization by Warda M. Shaban

“…The proposed method is called the Dimensional Archimedes Optimization Algorithm (DAOA). DAOA is based on the Archimedes Optimization Algorithm (AOA) and Dimensional Learning Strategy (DLS). …”
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Schur Complement Optimized Iterative EKF for Visual–Inertial Odometry in Autonomous Vehicles by Guo Ma, Cong Li, Hui Jing, Bing Kuang, Ming Li, Xiang Wang, Guangyu Jia

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