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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Soft Measurement of Wastewater Treatment System Based on PSOGA-WNN by LIU Yuhui, MAI Wenjie, LI Xiaoyong, ZHAO Yinzhong, HE Xinzhong, HUANG Mingzhi

“…To accurately predict the SS_eff (effluent SS) content and COD_eff (effluent COD) concentration in water quality parameters and further improve the water quality early warning mechanism,this paper proposes the PSOGA-WNN soft measurement model of paper wastewater effluent quality to obtain the main water quality technical parameters,COD_inf (influent COD),Q (influent flow),pH (influent pH),SS_inf (influent SS),T (influent temperature),DO (influent dissolved oxygen),COD_eff,and SS_eff, for predicting the quality of wastewater from the wastewater treatment plant.Among them,the prediction results of PSOGA-WNN are compared with the neural networks of PSO-WNN,GA-WNN,and PSOGA-BP.The results show that the PSOGA-WNN neural network has the highest prediction accuracy,which indicates that the PSOGA hybrid parameter optimization algorithm based on the genetic algorithm and particle swarm algorithm has obvious superiority in optimizing the prediction accuracy of the model.The WNN neural network has certain advantages over BP neural network in terms of fitting degree as well as error accuracy and is an effective means of simulation prediction.…”
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Integrated Energy Management of Smart Grids in Smart Cities Based on PSO Scheduling Models by Xiaolong Yang, Yanxia Xu, Chao Ma, Tao Yao, Lei Xu

“…Based on systematizing the system architecture of smart cities, we first analyze the facilitating and constraining roles of smart grids and smart cities with each other and make a quantitative analysis of the coordination and supporting roles between them; in the smart grid environment, we propose a framework of energy management system based on particle swarm optimization (PSO) dispatching model. …”
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Combined State-of-Charge Estimation Method for Lithium-Ion Batteries Using Long Short-Term Memory Network and Unscented Kalman Filter by Long Pu, Chun Wang

“…Firstly, the particle swarm optimization (PSO) algorithm was utilized to accurately identify the parameters of the battery model. …”
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Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents by Lida Barba, Nibaldo Rodríguez, Cecilia Montt

“…The coefficients of the first ANN are estimated through the particle swarm optimization (PSO) learning algorithm, while the coefficients of the second ANN are estimated with the resilient backpropagation (RPROP) learning algorithm. …”
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Automatic collaborative water surface coverage and cleaning strategy of UAV and USVs by Tianping Deng, Xiaohui Xu, Zeyan Ding, Xiao Xiao, Ming Zhu, Kai Peng

“…Second, we design a task scheduling and assignment algorithm for USVs to balance the garbage loads based on the particle swarm optimization algorithm. …”
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Rolling Force Prediction of Hot Rolling Based on GA-MELM by Jingyi Liu, Xinxin Liu, Ba Tuan Le

“…In this paper, a rolling force prediction method based on genetic algorithm (GA), particle swarm optimization algorithm (PSO), and multiple hidden layer extreme learning machine (MELM) is proposed, namely, PSO-GA-MELM algorithm, which takes MELM as the basic model for rolling force prediction. …”
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Gearbox Fault Diagnosis based on LMD Approximate Entropy and PSO-ELM by Zhang Yuxue, Pan Hongxia

“…Finally,the input weights of ELM and the threshold value of the hidden layer neurons are optimized by the particle swarm optimization algorithm,the model of PSO-ELM is established,and the approximate entropy values are input into the ELM and PSO-ELM models to recognize and classify the fault types of the gearbox of different conditions. …”
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An Information Granulated Based SVM Approach for Anomaly Detection of Main Transformers in Nuclear Power Plants by Wenmin Yu, Ren Yu, Cheng Li

“…A condition prediction method based on the online support vector machine (SVM) regression model is proposed, with the input data being preprocessed using the information granulation method, and the parameters of the model are optimized using the particle swarm optimization (PSO) algorithm. …”
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Performance analysis of secrecy rate for SWIPT in massive antenna by Hui BAO, Minmin ZHANG, Yaqing YAO, Hui WANG

“…In the multi-drop broadcast system,the existing research is to optimize the single-user security rate in the complete channel state information.In fact,it’s impossible that there exists only one user in the system.The base station often receives incomplete channel state information.Aiming at this problem,a robust beamforming scheme was proposed.In the multi-user case,considering the influence of channel estimation error on the system security rate,the particle swarm optimization algorithm was used to optimize the emission beamforming vector,artificial noise covariance and power split ratio to ensure that the user collects a certain energy while maximizing the safe transmission rate.The simulation results show that the proposed scheme is slightly lower than the security rate in the ideal case,but it is meaningful to the actual system,taking into account the existence of eavesdropping users and the estimation error.…”
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Rate of penetration prediction in drilling operations: a comparative study of AI models and meta-heuristic approaches by Fatemeh Mohammadinia, Ali Ranjbar, Fatemeh Ghazi, Seyyed Taha Hosseini

“…To further enhance model performance, metaheuristic optimization strategies such as the Crow Search Algorithm (CSA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) are integrated. …”
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Rolling Bearing Fault Diagnosis Based on Adaptive Multiparameter-Adjusting Bistable Stochastic Resonance by Z. H. Lai, S. B. Wang, G. Q. Zhang, C. L. Zhang, J. W. Zhang

“…In order to further enhance the detection performance of adaptive SR methods and extend their application in rolling bearing fault diagnosis, an adaptive multiparameter-adjusting SR (AMPASR) method for bistable systems based on particle swarm optimization (PSO) algorithm is proposed in this paper. …”
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An Improved Parameter-Adaptive Variational Mode Decomposition Method and Its Application in Fault Diagnosis of Rolling Bearings by Cuixing Li, Yongqiang Liu, Yingying Liao

“…The new objective function fully considers the equivalent filtering characteristics of VMD, and squared envelope kurtosis has good antinoise performance. In the optimization method, this paper uses an improved particle swarm optimization (PSO) algorithm. …”
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Multi-UAV Cooperative Air Combat Target Assignment Method Based on VNS-IBPSO in Complex Dynamic Environment by Yiyuan Li, Weiyi Chen, Shukan Liu, Guang Yang, Fan He

“…This method improves upon the limitations of the BPSO algorithm, such as limited local search capability and premature convergence, by combining variable neighborhood search and an improved binary particle swarm optimization algorithm. …”
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Predicting the Traffic Crashes of Taxi Drivers by Applying the Non-Linear Learning of ANFIS-PSO with M5 Model Tree by E. Abbasi, M. Hadji Hosseinlou

“…A novel technique is been developed by applying nonlinear-learning of composition model of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Particle Swarm Optimization (PSO) with M5 model tree. …”
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Mitigating of Sub-synchronous Resonance in a Series-Compensated Hybrid System with Steam and Wind Turbine Using FACTS Controllers by Hossein Hosseini, Behruz Tousi

“…Furthermore, the results obtained from imperialist competitive algorithm (ICA) are compared with PID controller optimized by Particle Swarm Optimization (PSO) algorithm.…”
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Survival risk prediction of gastric cardia cancer-based on a dynamic modular neural network by Chao Lu, Yang Li, Xing Wei

“…Therefore, this paper proposes a data-driven method for the survival risk of cardiac cancer based on an adaptive particle swarm optimization algorithm (APSO) and a dynamic modular neural network (DMNN). …”
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Research on Trajectory Tracking Control Method for Crawler Robot Based on Improved PSO Sliding Mode Disturbance Rejection Control by Zhiyong Yang, Qing Lang, Yuhong Xiong, Shengze Yang, Changjin Zhang, Lielei Deng, Daode Zhang

“…To overcome the tendency of the standard particle swarm optimization (PSO) algorithm to fall into local optima during controller parameter tuning, a nonlinear dynamic adjustment strategy was adopted. …”
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Bike-Sharing Static Rebalancing by Considering the Collection of Bicycles in Need of Repair by Sheng Zhang, Guanhua Xiang, Zhongxiang Huang

“…The proposed formulation takes into account the problem introduced by the need to collect bicycles in need of repair. A hybrid Discrete Particle Swarm Optimization (DPSO) algorithm was proposed to solve the model, which incorporates a reduced variable neighborhood search (RVNS) functionality together with DPSO to improve the global optimization performance. …”
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Research on Input Scheme Selection of a Novel Parallel Mechanism by Yajun Chen, Yongbin Li, Dong Yang, Tiejun Li

“…Then, the end effector of the parallel mechanism moves along two different trajectories. Using the particle swarm optimization algorithm, the inverse kinematics solution of each trajectory is obtained, and the velocity and acceleration of each actuator under different trajectories are obtained. …”
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