Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement by Jie Fang, Wenwu Li, Dunchu Chen

“…It replaces the traditional energy storage model with this model and then solves the EV and SOP collaborative planning model using a second-order conical planning algorithm with the objective function of minimizing the annual integrated cost. …”
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Cloud edge end network resource allocation for thermostatically controlled load aggregation regulation by Yi LIU, Xin WU

“…Thermostatically controlled load is a flexible load that controls temperature regulation, such as air conditioning and electric water heaters.As a crucial demand side resource, flexible aggregation and regulation of load clusters can fully mobilize clean energy consumption capacity and ensure the balance between supply and demand of the power grid.Due to the common occurrence of thermostatically controlled loads in commercial office buildings and residential areas, a relatively stable control and transmission method can be adopted.Therefore, an efficient hierarchical transmission network is introduced to achieve data transmission and information interaction between loads and the power grid, and to flexibly, real-time, and accurately utilize the adjustable potential of load clusters.Firstly, an information interaction architecture of load IoT which structured “central cloud-edge cloud-regional load controller-thermostatically controlled load”was proposed.Then, for the “end edge”part, considering the requirements of different aggregation control tasks, an improved clustering algorithm was used to classify the tasks and reduce transmission overhead.For the “end-side” part, an improved clustering algorithm was used to optimize the transmission distance.For the edge-cloud collaboration part, a subchannel resource allocation algorithm was designed based on stable matching and water injection algorithms.The binary particle swarm optimization algorithm was used to solve the task upload decision problem.Finally, the effectiveness of the proposed model and algorithm is verified through simulation, and comparative experiments are also conducted.…”
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Prediction of Transformer Residual Flux Based on J-A Hysteresis Theory by Qi Long, Xu Yang, Keru Jiang, Changhong Zhang, Mingchun Hou, Yu Xin, Dehua Xiong, Xiongying Duan

“…It has low dependence on the initial conditions and greatly avoids the influence of DC offset and noise on measurement results. Firstly, an improved particle-swarm optimization algorithm is proposed in this paper to address the problem of slow convergence speed and susceptibility to local optima in current particle-swarm optimization algorithms for extracting J-A model parameters. …”
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Dynamic energy consumption monitoring and scheduling for green buildings: A comprehensive approach by Hua Zheng, Pengming Wang

“…Meanwhile, the particle swarm optimization (PSO) algorithm is used to solve the multi-objective scheduling problem to achieve the global objectives of energy conservation, cost reduction, and comfort optimization. …”
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Deep Reinforcement Learning for UAV Intelligent Mission Planning by Longfei Yue, Rennong Yang, Ying Zhang, Lixin Yu, Zhuangzhuang Wang

“…Then, the SEAD intelligent planning model based on the proximal policy optimization (PPO) algorithm is established and a general intelligent planning architecture is proposed. …”
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Finding the Shortest Path with Vertex Constraint over Large Graphs by Yajun Yang, Zhongfei Li, Xin Wang, Qinghua Hu

“…In this paper, we first propose a novel exact heuristic algorithm in best-first search way and then give two optimizing techniques to improve efficiency. …”
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Intelligent design of Fe–Cr–Ni–Al/Ti multi-principal element alloys based on machine learning by Kang Xu, Zhengming Sun, Jian Tu, Wenwang Wu, Huihui Yang

“…Multi-principal element alloys (MPEAs), distinguished by their complex compositions and exceptional mechanical properties, pose significant challenges for conventional predictive approaches in mechanical property optimization. This study proposes an innovative intelligent optimization algorithm (OA) to refine feature selection in machine learning (ML) models, targeting the prediction of ultimate tensile strength (UTS) and fracture elongation (FE) in MPEAs. …”
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A Machine Learning Approach to Analyze Manpower Sleep Disorder by Reza Amiri

“…Moreover, a combination of machine learning and metaheuristic algorithms such as eXtreme Gradient Boosting and particle swarm optimization are used to make an accurate predictive model. …”
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Research on collaborative scheduling strategies of multi-agent agricultural machinery groups by Ziyi Wang, Fan Zhang, Shiji Ma, Hailong Wang, Shunyao Zhang, Xiaozhong Gao

“…Subsequently, the network model is trained to improve its solution capabilities using the policy gradient algorithm (REINFORCE). …”
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Vehicle Routing Problem for Collaborative Multidepot Petrol Replenishment under Emergency Conditions by Guangcan Xu, Qiguang Lyu

“…As a method to solve the model, genetic variation of multiobjective particle swarm optimization algorithm is considered. …”
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Software and hardware co-design of lightweight authenticated ciphers ASCON for the internet of things by Jing WANG, Lesheng HE, Zhonghong LI, Luchi LI, Hang YANG

“…ASCON was the most promising algorithm to become an international standard in the 2021 NIST lightweight authenticated encryption call for proposals.The algorithm was designed to achieve the best performance in IoT resource-constrained environments, and there was no hardware IP core implementation based on this algorithm in the open literature.A software-hardware collaborative implementation method of ASCON was proposed, which improved the speed and reduced the memory footprint of ASCON in IoT security authentication applications through hardware means such as S-box optimization, prior calculation and advanced pipeline design.As a comparison, ASCON has been transplanted on the common IoT embedded processor platform.The results showed that the described method was more than 7.9 times faster, while the memory footprint was reduced by at least 90%.The schemes can be used for the design and implementation of IoT security application-specific integrated circuits or SoCs.…”
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考虑润滑状态的摆动活齿传动多目标优化设计 by 邓志平, 张均富

“…The global optimal solution is obtained based on chaotic particle swarm optimization algorithm. …”
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基于modeFRONTIER的离合器碟形弹簧多目标优化设计 by 潘金坤

“…Based on the analysis of the working characters of disc springs in clutch,the mathematical model of multi-objective optimal design of disc springs is established with unified objective function method,which regards the minimization of the disc spring volume and its average variable quantity of working compress force within the scope of friction lining wear as optimal objectives.The optimization calculation is presented by using the software modeFRONTIER.The results indicate that the relevant performance of disc springs is significantly improved after optimal design,with the objective function values reduced by 36% and 6% respectively.The software modeFRONTIER,with its simplicity and efficient algorithm,solves optimization problems and improves design efficiency.…”
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Pickup and delivery planning for the crowdsourced freight delivery routing problem. by Jingxian Zhang

“…To solve this combinatorial optimization problem, we propose an improved partheno genetic algorithm (IPGA) and a simulated annealing algorithm (SA). …”
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Secure healthcare data sharing and attack detection framework using radial basis neural network by Abhishek Kumar, Priya Batta, Pramod Singh Rathore, Sachin Ahuja

“…Specifically, the Intelligent Voyage Optimization algorithm effectively tunes the model hyperparameters and the deployment of hybrid features contributes to the proposed model to detect attack patterns effectively. …”
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Image acquisition technology for unmanned aerial vehicles based on YOLO - Illustrated by the case of wind turbine blade inspection by Zhenjun Dai

“…For this purpose, the study aims to optimize the You Only Look Once (YOLO) processing algorithm for drone images to improve the detection efficiency. …”
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Reinforcement Learning for Computational Guidance of Launch Vehicle Upper Stage by Shiyao Li, Yushen Yan, Hao Qiao, Xin Guan, Xinguo Li

“…This manuscript investigates the use of a reinforcement learning method for the guidance of launch vehicles and a computational guidance algorithm based on a deep neural network (DNN). Computational guidance algorithms can deal with emergencies during flight and improve the success rate of missions, and most of the current computational guidance algorithms are based on optimal control, whose calculation efficiency cannot be guaranteed. …”
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Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs by Kaifeng Geng, Chunming Ye, Zhen hua Dai, Li Liu

“…This paper proposes an improved multiobjective ant lion optimization (IMOALO) algorithm to solve the RHFSP with the objectives of minimizing the makespan and energy consumption cost under Time-of-Use (TOU) electricity tariffs. …”
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Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network by Liming Li, Shubin Zheng, Chenxi Wang, Shuguang Zhao, Xiaodong Chai, Lele Peng, Qianqian Tong, Ji Wang

“…The prediction graph is inputted into CRRNet to improve its edge information and local region to achieve optimization. …”
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Robust Analysis and Parameters Identification of the Nonlinear Multistage Dynamical System in Batch Fermentation of Glycerol by Xu Zhang, Xinying Wang, Enmin Feng, Zhilong Xiu

“…Then we establish a parameter identification model and construct the particle swarm optimization algorithm to solve it. …”
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