Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model by JIANG Tao, XU Cong, JIA Shaohui, WANG Shen, ZHANG Yajian

“…Then, based on the differential evolution-particle swarm optimization algorithm, the established low-carbon planning model of the integrated energy system was solved to avoid the algorithm from falling into local optimality during the optimization process. …”
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Optimized Hyper Beamforming of Linear Antenna Arrays Using Collective Animal Behaviour by Gopi Ram, Durbadal Mandal, Rajib Kar, Sakti Prasad Ghoshal

“…As compared to conventional hyper beamforming of linear antenna array, real coded genetic algorithm (RGA), particle swarm optimization (PSO), and differential evolution (DE) applied to the hyper beam of the same array can achieve reduction in sidelobe level (SLL) and same or less first null beam width (FNBW), keeping the same value of hyperbeam exponent. …”
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Multiple Target Localization with Bistatic Radar Using Heuristic Computational Intelligence Techniques by Fawad Zaman, Ijaz Mansoor Qureshi, Ata Ur Rehman, Shujaat Ali Khan Tanoli

“…In this connection, first the global search optimizers, that is,are developed separately Particle Swarm Optimization (PSO) and Differential Evolution (DE) are developed separately, and, to enhance the performances further, both of them are hybridized with a local search optimizer called Active Set Algorithm (ASA). …”
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Traffic Model and On-Ramp Metering Strategy under Foggy Weather Conditions Using T-S Fuzzy Systems by Changle Sun, Hongyan Gao

“…The correction factors are determined based on the parameters of the consequent part in the T-S model, which are optimized using the particle swarm optimization algorithm. The sum of the mean absolute percentage error of the mainstream traffic density and speed is used to evaluate the proposed traffic model. …”
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An Improved CEEMDAN Time-Domain Energy Entropy Method for the Failure Mode Identification of the Rolling Bearing by Fengfeng Bie, Yi Miao, Fengxia Lyu, Jian Peng, Yue Guo

“…Finally, the feature vector sets are input into the PSO-SVM (particle swarm optimization-support vector machine) based model for training and pattern recognition. …”
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Determining Appropriate Strategy for Managing the Energy Production System in the Presence of Renewable Energy Sources and Improved Intelligence Method by Amir Sohel, Md Faisal Bin Ashab

“…The presented method is carried out for IEEE 24 busbar network and the combined particle swarm optimization and gravitation search algorithm optimization process, which includes two method for optimization process.…”
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Energy Management in the Microgrid and Its Optimal Planning for Supplying Wireless Charging Electric Vehicle by Salma Sraidi, Mohamed Maaroufi

“…The optimization problem is solved on the basis of the particle swarm optimization (PSO) algorithm. We could note that the stability of the microgrid in the off-grid mode is better, when the load is close to the output power of the distributed power supply. …”
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Radio frequency energy harvesting-combined collaborative energy-saving computation offloading mechanism by Bei TANG, Qian WANG, Siguang CHEN

“…In order to fit the differentiated energy demands in vertical markets and ensure that internet of things (IoT) devices can hold an efficient and sustainable operation mode, a radio frequency energy harvesting-combined collaborative energy-saving computation offloading mechanism was studied.Specifically, a system energy consumption minimization problem was formulated under the joint optimization consideration of computation offloading decision, uplink bandwidth resource allocation, downlink bandwidth resource allocation and base station power splitting.Meanwhile, by combining the concept of penalty function, a new evaluation index was introduced, and then an adaptive particle swarm optimization-based collaborative energy saving computation offloading (APSO-CESCO) algorithm was proposed to solve the problem.The proposed algorithm constructed dynamic inertia weight and linearly adjusted penalty factor, which could alternate the spatial distribution density of the particle community in real-time during the iterative search process, and the optimal computation offloading policy with tolerable punishment could be well-generated.Furthermore, to prevent particles from exceeding exploration range, the velocity boundary was introduced which could also reduce the generation probability of invalid solutions and improve the actual exploration effectiveness.Finally, the simulation results show that the proposed algorithm can achieve higher convergence efficiency and solution accuracy, and compared with other common benchmark schemes, the system energy consumption can be reduced by 34.09%, 14.72%, and 6.86%, respectively.…”
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Deformation Prediction of Foundation Pit Based on Exponential Power Product Model of Improved Algorithm by Chuankui Jing, Hao Wang, Hongsong Li

“…Through six standard test functions and three application examples, the optimization ability of the ISDO algorithm is verified, and the optimization results are compared with those of basic supply demand optimization algorithm (SDO), whale optimization algorithm (WOA), grey wolf optimization algorithm (GWO), moth swarm algorithm (MSA), and particle swarm optimization algorithm (PSO). Taking the settlement prediction of three foundation pits as an example, the delay time and embedding dimension of each case are determined by autocorrelation function method and false nearest neighbor method, and input and output vectors are constructed to train and predict each model. …”
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Designing a Multi-Objective Closed-loop Supply Chain Mathematical Model with Supplier Selection Approach and considering Discount by Esmat Saadi, kiamars fathi, Reza Radfar

“…The presented model generates Pareto solutions using two proposed meta-heuristic algorithms, multi objective particle swarm optimization and non-dominated sorting genetic algorithm and combination of the two. …”
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Artificial Bee Colony and Newton Algorithm for Forward Position Solution of Parallel Mechanism by Ping Li, Siyang Peng, Linxian Che, Li Du, Junkun Hong

“…Furthermore， comparative tests to solve these examples are carried out with HABC-Newton， ABC， DE and particle swarm optimization algorithms， and the numerical experiments indicate that HABC-Newton algorithm has better performance than compared algorithms in terms of the accuracy， robustness and computational efficiency.…”
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Short-Term Passenger Flow Forecasting for Rail Transit considering Chaos Theory and Improved EMD-PSO-LSTM-Combined Optimization by Lixin Zhao, Hui Jin, Xintong Zou, Xiao Liu

“…This paper proposes a prediction method based on chaos theory and an improved empirical-modal-decomposition particle-swarm-optimization long short-term-memory (EMD-PSO-LSTM)-combined optimization process for passenger flow data with high nonlinearity and dynamic space-time dependence, using EMD to process the original passenger flow data and generate several eigenmodal functions (IMFs) and residuals with different characteristic scales. …”
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Road Surface State Recognition Based on SVM Optimization and Image Segmentation Processing by Jiandong Zhao, Hongqiang Wu, Liangliang Chen

“…In order to improve the recognition accuracy and the universality, a grid searching algorithm and PSO (Particle Swarm Optimization) algorithm are used to optimize the kernel function factor and penalty factor of SVM. …”
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A New Decomposition Ensemble Learning Approach with Intelligent Optimization for PM2.5 Concentration Forecasting by Guangyuan Xing, Shaolong Sun, Jue Guo

“…According to the principle of “divide and conquer,” we propose a novel decomposition ensemble learning approach by integrating ensemble empirical mode decomposition (EEMD), artificial neural networks (ANNs), and adaptive particle swarm optimization (APSO) for forecasting PM2.5 concentrations. …”
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A Novel Experimental and Approach of Diagnosis, Partial Shading, and Fault Detection for Domestic Purposes Photovoltaic System Using Data Exchange of Adjacent Panels by H. A. Raeisi, S. M. Sadeghzadeh

“…The MPPT has been executed by employing a boost converter using particle swarm optimization (PSO) technique. The system is composed of two photovoltaic arrays. …”
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Automatic Optimal Design Method for Minimum Total Resistance Hull Based on Enhanced FFD Method by Shuhui Guo, Baoji Zhang, Zheng Tian, Jie Liu, Hailin Tang

“…To this end, an integrated, fully automated optimization program was developed based on Python, incorporating Enhanced Free-Form Deformation (FFD) technology, scripted CFD numerical evaluation, and the Particle Swarm Optimization (PSO) algorithm. This program allowed precise control of hull form, improving efficiency while reducing costs. …”
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Strategic Behavior of Customers and Optimal Control for Batch Service Polling Systems with Priorities by Tao Jiang, Xingzheng Lu, Lu Liu, Jun Lv, Xudong Chai

“…Finally, we formulate the revenue function of the service provider and present the Particle Swarm Optimization algorithm to seek the optimal service prices for the high-priority and low-priority customers to maximize the service provider’s revenue under the two levels of information.…”
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Improving Airport Flight Prediction System Based on Optimized Regression Vector Machine Algorithm by Baraa Yousif Salman, Jaber Parchami

“…In this research, to improve the performance of the SVR algorithm in predicting air delays, the particle swarm optimization (PSO) algorithm has been used to adjust the hyperparameters of the SVR algorithm. …”
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Comparative Analysis of ANFIS and State-ANFIS for Forecasting Cooking Oil Prices Based on Processed Palm Oil Yield (Crude Palm Oil) by Brodjol Sutijo Suprih Ulama, Fausania Hibatullah, Mochammad Reza Habibi, null Makkulau

“…However, ANFIS confronts limitations stemming from backpropagation, prompting the exploration of alternatives like particle swarm optimization (PSO). Hybrid PSO-ANFIS models exhibit enhanced forecasting accuracy, albeit at the expense of increased computational time. …”
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Finite-Time Cluster Synchronization of Fractional-Order Complex-Valued Neural Networks Based on Memristor with Optimized Control Parameters by Qi Chang, Rui Wang, Yongqing Yang

“…We further investigate the optimization of control parameters by formulating an optimization model, which is solved using particle swarm optimization (PSO) to determine the optimal control parameters. …”
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