Multi-Depot Pickup and Delivery Problem with Resource Sharing by Yong Wang, Lingyu Ran, Xiangyang Guan, Yajie Zou

“…Third, benchmark tests are conducted to verify the performance and effectiveness of the proposed two-stage hybrid algorithm, and numerical results prove that the proposed methodology outperforms the standard NSGA-II and multi-objective particle swarm optimization algorithm. …”
Get full text

Crude Oil Price Prediction Based on a Dynamic Correcting Support Vector Regression Machine by Li Shu-rong, Ge Yu-lei

“…We also propose the hybrid RNA genetic algorithm (HRGA) with the position displacement idea of bare bones particle swarm optimization (PSO) changing the mutation operator. …”
Get full text

A Sleep Scheduling Mechanism with PSO Collaborative Evolution for Wireless Sensor Networks by Luobing Dong, He Tao, William Doherty, Marten Young

“…This paper proposes a particle swarm optimization sleep scheduling mechanism for use in wireless sensor networks based on sleep scheduling algorithm. …”
Get full text

Classification of English Translation Teaching Models based on Multiple Intelligence Theory by Xiaoli Li

“…In order to improve the discrimination accuracy of the extreme learning machine algorithm, this paper applies the particle swarm optimization extreme learning machine algorithm to the research on the classification of English translation teaching samples and proposes an intelligent English classification teaching model based on the actual situation of English translation teaching. …”
Get full text

基于萤火虫神经网络的轴承性能退化程度评估 by 刘永前, 徐强, 田德, 龙泉

Get full text

Mix design and performance prediction of EPS lightweight structural concrete based on orthogonal experimentation by Qianhui Zhang

“…A novel dataset was established and utilized in performance prediction using XGBoost, optimized with Seagull Optimization Algorithm (SOA), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO). …”
Get full text

A SIR Model with Incomplete Data for the Analysis of Influenza A Spread in Ningbo by Bingqing Wang, Yanyao Hu, Zhongdi Cen, Jian Huang, Tianfeng He, Aimin Xu

“…Based on the incompleteness of the data, the parameter estimation problem of the SIR model is transformed into an optimization problem. The Particle Swarm Optimization algorithm is used to solve the optimization problem. …”
Get full text

An Improved Kernel Based Extreme Learning Machine for Robot Execution Failures by Bin Li, Xuewen Rong, Yibin Li

“…For improving the prediction accuracy of robot execution failures, this paper proposes a novel KELM learning algorithm using the particle swarm optimization approach to optimize the parameters of kernel functions of neural networks, which is called the AKELM learning algorithm. …”
Get full text

A study on monthly sales forecasting of new energy vehicles in urban areas using the WOA-BiGRU model. by Xiangtu Li

“…Its prediction results are compared with those of the particle swarm optimization (PSO) algorithm. The research findings are as follows: The growth of NEV sales has reversed the declining trend of overall automobile sales in China; Cities with higher NEV sales are predominantly concentrated in four major economic hubs--the Pearl River Delta, Yangtze River Delta, Beijing-Tianjin-Hebei region, and Chengdu-Chongqing. …”
Get full text

Analyzing Student Graduation and Dropout Patterns Using Artificial Intelligence and Survival Strategies by Behrouz Alefy, Vahid Babazadeh

“…The study applies state-of-the-art machine learning techniques to establish dominant patterns and offer forecasts using a wide range of student records. Weevil Damage Optimization Algorithm, Black Widow Optimization Algorithm, and Phasor Particle Swarm Optimization form the core of 3 optimization approaches. …”
Get full text

Multi-user fine-grained task offloading scheduling strategy under cloud-edge-end collaboration by XIE Mande, HUANG Zhufang, SUN Hao

“…Then, a multi-user subtask scheduling scheme was proposed and an improved simulated annealing particle swarm algorithm was designed to minimize the total system cost to achieve the optimal offloading decision. …”
Get full text

Scalable and energy-efficient task allocation in industry 4.0: Leveraging distributed auction and IBPSO. by Qingwen Li, Tang Wai Fan, Lam Sui Kei, Zhaobin Li

“…It also introduces an improved variant of the improved Binary Particle Swarm Optimization (IBPSO) algorithm to manage complicated tasks that require multi-robot collaboration. …”
Get full text

Global maximum power point tracking method for photovoltaic systems using Takagi-Sugeno fuzzy models and ANFIS approach by N. Hadjidj, M. Benbrahim, D. Ounnas, L. H. Mouss

“…In addition, a comparative analysis of the proposed GMPPT controller against conventional algorithms, such as Incremental Conductance, Perturb & Observe and Particle Swarm Optimization, shows that it offers a fast dynamic response in finding the maximum power with significantly less oscillation around the maximum power point. …”
Get full text

Reflection Reduction on DDR3 High-Speed Bus by Improved PSO by Huiyong Li, Hongxu Jiang, Bo Li, Miyi Duan

“…Additionally, an improved particle swarm optimization algorithm with adaptive perturbation is presented to solve the impedance mismatch problem (IPSO-IMp) based on the above model. …”
Get full text

Supply chain finance credit risk assessment using support vector machine–based ensemble improved with noise elimination by Ying Liu, Lihua Huang

“…The main characteristics of this approach include 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 noise and class noise to achieve an optimal clean set, and (2) support vector machine classifiers, based on the improved particle swarm optimization algorithm, are seen as component classifiers. …”
Get full text

Anomaly Detection in Wireless Sensor Networks Using Immune-Based Bioinspired Mechanism by Ramsha Rizwan, Farrukh Aslam Khan, Haider Abbas, Sajjad Hussain Chauhdary

“…Several solutions have been proposed using Artificial Immune System (AIS), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) algorithm, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and so forth. …”
Get full text

Hardware-in-loop implementation of an adaptive MPPT controlled PV-assisted EV charging system with vehicle-to-grid integration by Surabhi Singh, Hari Om Bansal

“…This paper developed and compared perturb and observe (P&O), Particle swarm optimization (PSO), and hybrid PSO + Adaptive neuro-fuzzy inference system (ANFIS) based algorithm for MPPT. …”
Get full text

A PSO Driven Intelligent Model Updating and Parameter Identification Scheme for Cable-Damper System by Danhui Dan, Yanyang Chen, Bin Xu

“…This paper suggests a cable model updating calculation scheme driven by the particle swarm optimization (PSO) algorithm. By establishing a finite element model considering the static geometric nonlinearity and stress-stiffening effect firstly, an automatically finite element method model updating powered by PSO algorithm is proposed, with the aims to identify the cable force and relevant parameters of cable-damper system precisely. …”
Get full text

Data-Driven Superheating Control of Organic Rankine Cycle Processes by Jianhua Zhang, Xiao Tian, Zhengmao Zhu, Mifeng Ren

“…Due to non-Gaussian stochastic disturbances imposed on heat sources, the quantized minimum error entropy (QMEE) is adopted to construct the performance index of superheating control systems. Furthermore, particle swarm optimization (PSO) algorithm is applied to obtain optimal control law by minimizing the performance index. …”
Get full text

Network slicing deployment method based on isolation level by Qirun PAN, Kaizhi HUANG, Wei YOU

“…In order to balance the performance isolation requirements and security isolation requirements of network slicing,a network slice deployment method based on isolation level was proposed.The method first determined the isolation level of the network slice instance from the aspects of performance isolation and security isolation.When deploying the virtual nodes in the appropriate location,not only ensured that all network slice instances could reach their respective performance levels and security levels,but also isolated them.The gradation difference started to limit the coexistence condition of the virtual node.Then the integer linear programming method was used to model the problem,and the deployment cost was minimized as the objective function.Finally,the particle swarm optimization algorithm based on genetic algorithm was used to find the final deployment result.The simulation results show that the method has lower deployment cost and higher benefit-to-cost ratio,and can guarantee both performance and security.…”
Get full text