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Aerial refueling scheduling of multi-receiver and multi-tanker under spatial-temporal constraints for forest firefighting

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Chinese Journal of Aeronautics 2024年第5期37卷 71-91,I0001页

作者： Jing HUANG Jiaqi XING Jinrui REN Quan QUAN Youmin ZHANG Department of Information and Control Engineering Xi’an University of TechnologyXi’an 710048China Jiujiang Measuring Test Technology Research Institute Jiujiang 332000China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Automation Xi’an University of Posts&TelecommunicationsShaanxiXi’an 710121China Department of Mechanical Industrial and Aerospace EngineeringConcordia UniversityMontreal H3G 1M8Canada

Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest *** the constrained load capacities of these aircraft,aerial refueling becomes crucial to extend their operational time and *** order to address the complexities of firefighting missions involving multi-receiver and multi-tanker deployed from various airports,first,a fuel consumption calculation model for aerial refueling scheduling is established based on the receiver ***,two distinct methods,including an integrated one and a decomposed one,are designed to address the challenges of establishing refueling airspace and allocating tasks for *** methods aim to optimize total fuel consumption of the receivers and tankers within the aerial refueling scheduling *** optimization problem is established as nonlinear optimization models along with *** integrated method seamlessly combines refueling rendezvous point scheduling and tanker task allocation into unified *** has a complete solution space and excels in optimizing total fuel *** decomposed method,through the separation of rendezvous point scheduling and task allocation,achieves a reduced computational ***,this comes at the cost of sacrificing optimality by excluding specific feasible ***,numerical simulations are carried out to verify the feasibility and effectiveness of the proposed *** simulations yield insights crucial for the practical engineering application of both the integrated and decomposed methods in real-world *** comprehensive approach aims to enhance the efficiency of forest firefighting operations,mitigating the risks posed by forest fires to human life and property.

关键词： Aerial refueling Scheduling Planning Spatial-temporal constraint Firefighting

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Modeling a fuzzy expert system for predicting customers’ behavioral intention for restaurant business through parallel prediction of perceived values and satisfactions

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International Journal of Information Technology (Singapore) 2025年第2期17卷 1007-1014页

作者： Akhtaruzzaman, M. Shahryer, Fahim Halder, Sachitra Tanvin, Jamal Uddin Department of Computer Science and Engineering Military Institute of Science and Technology (MIST) Mirpur Cantonment Dhaka 1216 Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh

This paper focuses on the modeling of a recommendation process for the restaurant industry. It is a challenge job for a restaurant owner to ascertain the intentions of customers to evaluate their services, further improve their profit margin. So, the objective of this study is to design a fuzzy-based prediction model of customers’ intentions for a fine dining experience. To facilitate a comparative analysis and to identify the optimal approach, various membership functions (MF) and de-fuzzification methods are employed along with the analysis of the correlational behavior among various input subsets. Results have shown that CoA method with triangular MF are well enough to implement the model. The fuzzy-correlation analysis presents various levels of membership strengths for a same recommendation score in some cases. Moreover, the evaluation of the proposed model based on a custom dataset shows prominent results with as 0.938. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Customer intension Customer satisfaction FIS Perceived value Recommendation

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Investigations into the flow dynamics of mixed biomass particles in a fluidized bed through Hilbert-Huang transformation and data-driven modelling

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Particuology 2024年第12期95卷 115-123页

作者： Bojian Qi Yong Yan Wenbiao Zhang School of Computer and Artificial Intelligence Beijing Technology and Business UniversityBeijing100048China International Research Center for Carbon Neutralization Hangzhou Beihang International Innovation InstituteBeihang UniversityHangzhou311115China School of Control and Computer Engineering North China Electric Power UniversityBeijing102206China

Flow dynamics of binary particles are investigated to realize the monitoring and optimization of fluidized *** is a challenge to accurately classify the mass fraction of mixed biomass,considering the limitations of existing *** data collected from an electrostatic sensor array is *** correlation,empirical mode decomposition(EMD),Hilbert-Huang transform(HHT)are applied to process the *** a higher mass fraction of the wood sawdust,the segregation behavior occurs,and the high energy region of HHT spectrum ***,two data-driven models are trained based on a hybrid wavelet scattering transform and bidirectional long short-term memory(ST-BiLSTM)network and a EMD and BiLSTM(EMD-BiLSTM)network to identify the mass fractions of the mixed biomass,with accuracies of 92%and 99%.The electrostatic sensing combined with the EMD-BiLSTM model is effective to classify the mass fraction of the mixed biomass.

关键词： Fluidized beds Biomass Hilbert-Huang transformation Bidirectional long short-term memory network Electrostatic sensors

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A Novel Thermal Analysis Method for Tubular PM Linear Motors Based on Transfer Learning

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7379-7388页

作者： Wu, Tao Dai, Peipei Xue, Gang Guo, Youguang Lei, Gang Zhu, Jianguo Wang, Yifei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Technology Sydney School of Electrical and Data Engineering UltimoNSW2007 Australia The University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

Thermal modeling and analysis are critical for permanent magnet linear synchronous motors (PMLSMs), particularly in multiphysical analysis and motor design optimization. This article proposes a new method for thermal steady state modeling and analysis based on transfer learning (TL), which combines the thermal mechanism model with the data-driven model to achieve high-precision temperature analysis with small number of finite element analysis (FEA) samples. First, an equivalent thermal circuit (ETC) model is established for PMLSMs based on the structural parameters and heat transfer principles. Second, a hybrid model based on TL is developed: the model is pretrained by a large sample set generated from the ETC in the source field (mechanism analytical model), and then, the trained model is transferred to the target field (FEA data-driven model). The parameters of the neural network in the target field are optimized by a few FEA sample sets with higher precision to improve the prediction accuracy of the target model. Experimental results demonstrate that the proposed method significantly boosts the performance of the deep neural network (DNN) model, particularly when training sets are small. The root mean square error (RMSE) of the DNN model decreases by 0.901 in the 5:5 (training/testing) dataset and 1.726 in the 2:8 dataset;and the corresponding R^{2} and maximal absolute error of motor performances are significantly decreased. The smaller the proportion of the training set, the better performance of the hybrid modeling will achieve. Furthermore, a temperature rise experiment conducted on a prototype motor validates the efficacy and precision of the proposed hybrid modeling methodology. © 2015 IEEE.

关键词： Permanent magnets

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Software Detection and Warning Method for Pitch Angle Deviation of Road Traffic Radar 9

Software Detection and Warning Method for Pitch Angle Deviat...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Sun, Haokai Zhang, Zheng Jari Technology Lianyungang Jari Electronics Co. Ltd Lianyungang China Jiangsu Automation Research Institute Control Science and Engineering Lianyungang China

ISBN: (纸本)9798350376548

Introduced a software detection and warning method for the installation angle of road traffic radar in the pitch direction. Establish a mathematical model M1 based on the directional pattern of the transmitting antenna in the elevation direction. According to the RCS definition, the normalized curve shape of the received target echo signal strength is the same as model M1. The normalization coefficient is determined by on-site calibration methods or empirical value methods, and the model M1 is inversely normalized to obtain the model M2. Substitute the statistical analysis result A of the received signal strength result P ' calculated after real-time and cumulative sampling into model M2 to obtain the current elevation angle information of the radar. If the change in radar pitch angle exceeds the threshold, an alarm message will be output. This method does not require the addition of hardware sensors, and only estimates the current elevation angle of the radar through software calculations based on mathematical models and on-site sampled target echo signal strength, which has good engineering application value. © 2024 IEEE.

关键词： Radar warning systems

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Multi-agent Reinforcement Learning Algorithm Based on Role Parameter Sharing 1

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Zhang, Hui Xu, Chi Zhang, Ting-Ting Zhang, Ya School of Automation Southeast University Nanjing210096 China High-Tech Department Jiangsu Automation Research Institute Lianyungang222061 China School of Command and Control Engineering Army Engineering University Jiangsu Nanjing210017 China

ISBN: (数字)9789819733361

ISBN: (纸本)9789819733354

In multi-agent reinforcement learning, scalability is a significant challenge. Applying reinforcement learning algorithms in large-scale multi-agent systems requires consideration of algorithm efficiency. This paper attempts to reduce network parameter quantity and training time from the perspective of parameter sharing. However, parameter sharing may also bring some disadvantages, such as policy similarity, which may limit the formation of cooperative policies and affect the efficiency of the entire system. To address the problems caused by parameter sharing, this paper proposes a multi-agent reinforcement learning algorithm with role parameter sharing (R-PS). By dynamically dividing roles and selecting objects for parameter sharing, R-PS automatically identifies intelligent agents that may generate beneficial parameter sharing and conducts partial parameter sharing within the roles. Meanwhile, intrinsic rewards are introduced to increase the diversity of agent strategies. Experimental results show that R-PS can effectively divide roles, benefit from partial parameter sharing, and form diverse policies through intrinsic rewards. It also reduces training time, produces excellent performance and collaboration. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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Enhancing deformation characteristics prediction of coarse-grained soils with time-series generative adversarial network-based data augmentation and pre-training

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Frontiers of Structural and Civil engineering 2025年第3期19卷 396-410页

作者： Ying ZHANG Meng JIA Xuedong ZHANG Liping CAO Ziying AN Hongchao WANG Jinyu WANG School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China The State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower ResearchBeijing 100038China

Coarse-grained soils are fundamental to major infrastructures like embankments,roads,and *** their deformation characteristics is essential for ensuring structural *** methods,such as triaxial compression tests and numerical simulations,face challenges like high costs,time consumption,and limited generalizability across different soils and *** address these limitations,this study employs deep learning to predict the volumetric strain of coarse-grained soils as axial strain changes,aiming to obtain the axial strain(ε_(a))-volumetric strain(ε_(v))curve,which helps derive key mechanical parameters like cohesion(c),and elastic modulus(E).However,the limited data from triaxial tests poses challenges for training deep learning *** propose using a Time-series Generative Adversarial Network(TimeGAN)for data ***,we apply feature importance analysis to assess the quality of the numerical augmented data,providing feedback for improving the TimeGAN *** further enhance model performance,we introduce the pre-training strategy to reduce bias between augmented and real *** results demonstrate that our approach effectively predictscurve,with the mean absolute error(MAE)of 0.2219 and the R^(2) of *** analysis aligns with established findings in soil mechanics,underscoring the potential of our method in engineering applications.

关键词： coarse-grained soils deformation characteristics TimeGAN data augmentation pre-training

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Detuned Wireless Charging System with Constant Power Charging Ability and High-Misalignment Tolerance 7

Detuned Wireless Charging System with Constant Power Chargin...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： He, Jiafang Ma, Jun Dong, Shuai Li, Zhenjie Harbin Institute of Technology Zhengzhou Research Institute Harbin Institute of Technology Harbin China Northeast Forestry University College of Computer and Control Engineering Harbin China

ISBN: (纸本)9798350359558

In practical applications, wireless charging systems (WCS) should solve unavoidable misalignment problems and realize stable output over a wide load range. Therefore, a detuned WCS with solid anti-misalignment capacity and constant power (CP) output over a wide load range using the overlapping coil magnetic coupler (OCMC) and Buck converter is proposed in this paper. First, the system structure is designed, and then the relationship between the mutual inductance, load resistance, and output power is investigated. Second, the detailed coupling characteristic of the optimized OCMC is analyzed. Finally, the closed-loop workflow of the WCS is described, and simulation results are given. © 2024 IEEE.

关键词： Inductance

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Parameter Design Method of the Magnetic Coupler for Wireless Charging System Using Metamodel of Optimal Prognosis 7

Parameter Design Method of the Magnetic Coupler for Wireless...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Ma, Jun He, Jiafang Li, Zhenjie Dong, Shuai Harbin Institute of Technology Zhengzhou Research Institute Harbin Institute of Technology Harbin China Northeast Forestry University College of Computer and Control Engineering Harbin China

ISBN: (纸本)9798350359558

This paper addresses the parameter design problem of magnetic couplers and proposes a multi-objective optimization design method based on the Metamodel of Optimal Prognosis (MOP). The method involves mathematically fitting optimization objectives and design parameters using the optimal predictive metamodel, thereby establishing response surfaces for multi-objective optimization. By transforming finite element calculations of the magnetic coupler into numerical computations through fitting, the optimization process is accelerated. The parameters ultimately selected are verified through simulation, thus validating the effectiveness of the proposed optimization method. © 2024 IEEE.

关键词： Multiobjective optimization

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AN IMPROVED APF METHOD FOR SAFETY control OF MOBILE MANIPULATOR IN HUMAN-ROBOT COEXISTENCE ENVIRONMENT

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International Journal of Robotics and automation 2025年第3期40卷 184-193页

作者： Ye, Jinhua Hong, Linxin Wu, Haibin Zheng, Gengfeng School of Mechanical Engineering and Automation Fuzhou University Fuzhou350116 China Fujian Provincial Special Equipment Inspection and Research Institute Fuzhou350003 China Fujian Key Laboratory of Special Intelligent Equipment Safety Measurement and Control Fuzhou350003 China

Technology is nudging robot into automation and intelligence field, making dynamic collision avoidance indispensable in robotics. Aiming at safety control of mobile manipulator in human-robot coexistence environment, a novel artificial potential field based on danger index (DIAPF) approach is proposed. Firstly, hinged on the kinematic and dynamic model of mobile manipulators, a danger index system is established to take precautions against accident during the operation. We further improve the repulsion field and velocity repulsive field to promote dynamic obstacle avoidance in the human-robot coexistence environments. Feasibility and effectiveness of the proposed method are verified in simulation environment. © 2025 Acta Press. All rights reserved.

关键词： Social robots

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