Well logging super-resolution based on fractal interpolation enhanced by BiLSTM-AMPSO by Jian Han, Yu Deng, Bing Zheng, Zhimin Cao

“…In this paper, to improve the vertical resolution of well-logging data, a novel fractal interpolation based well logging super-resolution method was proposed by employing bidirectional long short-term memory (BiLSTM) and adaptive mutation particle swarm optimization (AMPSO). Specifically, mutation factors are introduced into the particle swarm optimization (PSO) algorithm to enhance search accuracy. …”
Get full text

A New Self-Tuning Nonlinear Model Predictive Controller for Autonomous Vehicles by Yasin Abdolahi, Sajad Yousefi, Jafar Tavoosi

“…This paper applies the particle swarm optimization (PSO) algorithm to find the global minimum tracking error by tuning the controller’s parameters and ultimately calculating the front steering angle and directed motor force to the wheels of an autonomous vehicle (AV). …”
Get full text

Visual Classification of Music Style Transfer Based on PSO-BP Rating Prediction Model by Tianjiao Li

“…At the same time, we take advantage of the BP neural network’s ability to handle complex nonlinear problems and construct a rating prediction model between the user and item attribute features, referred to as the PSO-BP rating prediction model, by combining the features of global optimization of particle swarm optimization algorithm, and make further improvements based on the traditional collaborative filtering algorithm.…”
Get full text

Attitude Active Disturbance Rejection Control of the Quadrotor and Its Parameter Tuning by Suiyuan Shen, Jinfa Xu

“…Simultaneously, an adaptive genetic algorithm-particle swarm optimization (AGA-PSO) is used to optimize the controller parameters to solve the problem that the controller parameters are difficult to tune. …”
Get full text

Coevolution of Artificial Agents Using Evolutionary Computation in Bargaining Game by Sangwook Lee

“…We present three kinds of EC based agents (EC-agent) participating in the bargaining game: genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE). …”
Get full text

基于并联机器人的柔性装配工装构型精度综合 by 石宏, 朱宁, 李伟楠, 李楠

“…A flexible fixture configuration for Aero-engine digital assembly is designed.Then aiming at the geometric feature of 3-UPU parallel mechanism,the error model is built considering universal hinge and rod length.Monte Carlo’s methods are adopted to analyze the influence on end executor error of rod length error and the universal vice clearance.Using particle swarm optimization based on interior point penalty function algorithm,accuracy synthesis is carried out according to the maximum pose error of end executor and objective function based on manufacturing cost minimum,the manufacturing tolerance of the parts is reasonable to determine,and a reference is provided for the development of prototype.…”
Get full text

A novel ensemble support vector machine model for land cover classification by Ying Liu, Lihua Huang

“…The key characteristics of this approach are that (1) a novel noise filtering scheme that avoids the noisy examples based on fuzzy clustering and principal component analysis algorithm is proposed to remove both attribute noises and class noises to achieve an optimal clean set and (2) support vector machine classifiers, based on the particle swarm optimization algorithm, are seen to component classifiers. …”
Get full text

Cost-benefit analysis in demand response with penalty and grid management using blockchain by Manikandan Ramasamy, Thenmalar Kaliannan, Saravanakumar Ramasamy

“…Two distinct optimization methods such as the gray wolf optimization algorithm and particle swarm optimization are employed to solve the optimization model. …”
Get full text

Improved energy efficiency using meta-heuristic approach for energy harvesting enabled IoT network by Rekha, Ritu Garg

“…This investigation studies energy efficiency of the network against the various system parameters which are relay location, power-splitting factor, power transmitted, data rate, energy conversion efficiency and noise power and it enables us to find out which parameters need to be optimized. Further, an objective function is formulated to achieve the optimal solution for power transmitted by the source and an adaptive particle swarm optimization (OPA-APSO) algorithm is proposed to attain maximized energy efficiency. …”
Get full text

A Fault Diagnosis Method for Planetary Gearboxes Based on IFMD by Fengfeng Bie, Xueping Ding, Qianqian Li, Yuting Zhang, Xinyue Huang

“…Ultimately, SVM iteratively optimized by the particle swarm optimization (PSO) algorithm, serves as the classification technique. …”
Get full text

STATCOM Controller Tuning to Enhance LVRT Capability of Grid-Connected Wind Power Generating Plants by Irene Ndunge Muisyo, Christopher Maina Muriithi, Stanley Irungu Kamau

“…The STATCOM under investigation is tuned using the Water Cycle Algorithm (WCA), Particle Swarm Optimization (PSO), and a hybrid algorithm of both WCA and PSO. …”
Get full text

Adaptive routing and wavelength assignment method based on SDN by Zhongnan ZHAO, Jian WANG, Hongwei GUO

“…Routing and wavelength assignment is an important resource allocation method of all-optical network.Aiming at the problem of traditional method combined with the new architecture,an adaptive multi-objective routing and wavelength assignment method based on SDN was proposed,which could realize the allocation of link resources of all-optical network through self-regulation.Based on the SDN service function chain model,service scheduling time and link service quality were taken as the scheduling objective,routing and wavelength assignment problem was constructed as the 0-1 integer programming problem,meanwhile,binary hybrid topology particle swarm optimization algorithm was used to optimize the network resources for optimal scheduling.The simulation results show that the proposed method is superior to the traditional classical algorithms in the test of recovery time,blocking rate and resource utilization.…”
Get full text

基于QPSO-SVM的轴承故障诊断方法 by 杨光春, 蹇清平

“…Due to the importance of rolling bearing as one of the most widely used in rotating machines,bearing failures have adverse effects on the safe operation of the equipment,in order to diagnosing the fault of rolling bearing effectively,a fault diagnosis model of support vector machine（SVM）optimized by quantum particle swarm optimization（QPSO）algorithm is proposed.First,fault vibration signals are decomposed into several intrinsic mode functions（IMFs）using empirical mode decomposition（EMD）method,then the instantaneous amplitudes of the IMFs that have the fault characteristics are extracted and regarded as the features vector,finally the SVM model optimized by QPSO is used for the failure mode identification.The experimental results indicate that the proposed bearing fault diagnosis method has good capability for adaptive features extraction as well as high fault diagnostic accuracy.…”
Get full text

Fault Diagnosis of Bearing Based on Cauchy Kernel Relevance Vector Machine Classifier with SIWPSO by Sheng-wei Fei, Yong He

“…In this paper, Cauchy kernel relevance vector machine with stochastic inertia weight particle swarm optimization algorithm (SIWPSO-CauchyRVM) is proposed to fault diagnosis for bearing. …”
Get full text

ARIMA-Based Forecasting of Wastewater Flow Across Short to Long Time Horizons by Jiawen Ye, Xulai Meng, Haiying Wang, Qingdao Zhou, Siwei An, Tong An, Pooria Ghorbani Bam, Diego Rosso

“…Ten repetitions with the same dataset assess stability, and ARIMA–LSTM–Transformer, with better performance, were selected. Then, the Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO) algorithm, and Sparrow Search Algorithm (SSA) were used for optimization, with the WOA excelling in accuracy and stability. …”
Get full text

Estimating shear strength of dredged soils for marine engineering: experimental investigation and machine learning modeling by Zheng Yao, Kaiwei Xu, Zejin Wang, Haodong Sun, Peng Cui, Peng Cui

“…For performance verification, four alternative predictive models were established, including LDA–ANN, support vector machines (SVM), Particle Swarm Optimization (PSO), and a GA-tuned BA–ANN. …”
Get full text

A Two-Phase Pattern Generation and Production Planning Procedure for the Stochastic Skiving Process by Tolga Kudret Karaca, Funda Samanlioglu, Ayca Altay

“…In addition, we also compare the performance of the dragonfly algorithm (DA) to the particle swarm optimization (PSO) for pattern generation. …”
Get full text

SIC-Free Based Indoor Two-User NOMA-VLCP System by Jianli Jin, Qianlong Shang, Jianping Wang, Huimin Lu, Danyang Chen, Dongmei Yang

“…The particle swarm optimization (PSO) algorithm is employed to construct a joint optimization function that optimizes the power allocation factor of the two users and the roll-off coefficient of the square-root-raised-cosine(SRRC) filter. …”
Get full text

Maneuver Strategy for Active Spacecraft to Avoid Space Debris and Return to the Original Orbit by Qun Fang, Zhen Zhang, Haodong Meng, Xiaolong Wang, Xiuwei Zhang

“…It has modified the artificial potential field (APF) method and particle swarm optimization algorithm, with an aim to help spacecraft avoid the space debris group and return to the original orbit. …”
Get full text

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.…”
Get full text