The Improved Antlion Optimizer and Artificial Neural Network for Chinese Influenza Prediction by Hongping Hu, Yangyang Li, Yanping Bai, Juping Zhang, Maoxing Liu

“…The antlion optimizer (ALO) is a new swarm-based metaheuristic algorithm for optimization, which mimics the hunting mechanism of antlions in nature. …”
Get full text

A Pareto-Based Clustering Approach for Solving a Bi-Objective Mobile Hub Location Problem with Congestion by Maryam Dehghan Chenary, Arman Ferdowsi, Richard F. Hartl

“…The results have been compared with Multiple-Objecti-ve Particle Swarm Optimization (MOPSO) and Non-Domi-nated Sorting Genetic Algorithm (NSGA-II) using several performance evaluation metrics. …”
Get full text

Research on Quality Anomaly Recognition Method Based on Optimized Probabilistic Neural Network by Li-li Li, Kun Chen, Jian-min Gao, Hui Li

“…Finally, the above method was validated by a simulation experiment and proved to be the most effective method compared with traditional BP neural network, single PNN, PCA-PNN without parameters optimized, and SVM optimized by particle swarm optimization algorithm.…”
Get full text

An Online Data-Driven Method for Accurate Detection of Thermal Updrafts Using SINDy by Yufeng Lu, Chenglou Liu, Haichao Hong, Yunwei Huang, Tingwei Ji, Fangfang Xie

“…By comparing results obtained using the particle filter algorithm, this method is shown to accurately estimate the parameters with negligible errors under observability conditions. …”
Get full text

Research on On-line Distribution Control Method of Driving Torque of Dual Hub Motor by WU Shi, CHE Cuiru, GUAN Yibo

“…In FTP-75 condition，the QPSO-LSTM algorithm with the addition of heterogeneous sequences reduces the single-cycle energy consumption by 2. 98% and 4. 64% ，respectively，compared with the quantum genetic algorithm and the particle swarm algorithm in the FTP-75 operating condition，and by 3. 06% and 4. 81% ，respectively，in the CLTC-P operating condition.…”
Get full text

Construction of teaching quality evaluation model of online dance teaching course based on improved PSO-BPNN by Jin Ben, Li Hanwen

“…For these shortcomings, it is optimized by the improved particle swarm. This study uses inertia weight and crossover operator strategy to optimize particle swarm optimization algorithm, achieving the collaborative work of back-propagation neural network and particle swarm optimization. …”
Get full text

Neuro-evolutionary models for imbalanced classification problems by Israa Al-Badarneh, Maria Habib, Ibrahim Aljarah, Hossam Faris

“…The utilized algorithms are the Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and the Salp Swarm Algorithm (SSA). …”
Get full text

Analysis of Reliability Indices in Next Generation Microgrids Under Uncertainties of Load and Renewable Power Production by nima nikmehr, Sajad Najafi Ravadanegh

“…In proposed structure, the MGs are in interconnected mode and there is power exchanging between MGs. The particle swarm optimization (PSO) algorithm is applied to optimal power dispatch and the obtained results are compared by Monte Carlo simulation (MCS) method.…”
Get full text

Efficient Multi-Target Localization Using Dynamic UAV Clusters by Wei Gong, Shuhan Lou, Liyuan Deng, Peng Yi, Yiguang Hong

“…To solve the NP-hard clustering problem, we develop the MDQPSO-ASA algorithm, which combines multi-swarm discrete quantum-inspired particle swarm optimization with adaptive simulated annealing, incorporating a repair mechanism to satisfy spatial and cardinality constraints. …”
Get full text

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.…”
Get full text

Gaussian Process Regression with Soft Equality Constraints by Didem Kochan, Xiu Yang

“…The GP model is trained using the quantum-inspired Hamiltonian Monte Carlo (QHMC) algorithm, which efficiently samples from a wide range of distributions by allowing a particle’s mass matrix to vary according to a probability distribution. …”
Get full text

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

“…The performance of the algorithm is verified through simulation experiments, and the results show that the proposed algorithm significantly reduces electricity consumption costs by 32.54% compared to algorithms that only optimize the scheduling of loads or some components of the home energy management system.…”
Get full text

Real-time active cell balancing using QPSO-controlled switched capacitor and transformer methods by S. Ida Evangeline, B. Subashini

“…To address these limitations, this paper proposes a novel hybrid active balancing approach that integrates switched capacitor and transformer-based techniques, dynamically controlled by a quantum particle swarm optimization algorithm. The hybrid system combines the speed of switched capacitor balancing for localized voltage differences with the long-range capabilities of transformer-based balancing, enabling efficient energy redistribution across large battery packs. …”
Get full text

Chaotic chimp-mountain gazelle optimized FOPID control for frequency regulation in islanded airport microgrids with heterogeneous energy systems by Odelu P., Chandan Kumar Shiva, Sachidananda Sen, Vedik Basetti, Chandra Sekhar Reddy

“…Simulation results demonstrates that the CCMGO optimized fractional order proportional-integral-derivative controller exhibits better performances compared to the conventional genetic algorithm and particle swarm optimization based controllers, as well as contemporary metaheuristic algorithms like grey wolf optimizer and whale optimization algorithm. …”
Get full text

Design and Parameter Optimization of Trajectory Correction Control Strategy for Air Duct Structure Projectile by Silin Cui, Xing Liu, Shoushan Jiang, Wei Wu

“…A design method of trajectory correction control strategy based on particle swarm optimization-cuckoo search (PSO-CS) hybrid algorithm is proposed to obtain the optimal control parameters that can make the projectile flight stable and correct accurately. …”
Get full text

Gradient-based optimization for parameter identification of lithium-ion battery model for electric vehicles by Motab Turki Almousa, Mohamed R. Gomaa, Mostafa Ghasemi, Mohamed Louzazni

“…The findings were contrasted to those from various algorithms, such as whale optimization algorithm, multi-verse optimizer, sine cosine algorithm, arithmetic optimization algorithm, particle swarm optimization, red kite optimization algorithm, tree-seed algorithm, and white shark optimizer. …”
Get full text

Aerodynamic Parameter Identification of Projectile Based on Improved Extreme Learning Machine and Ensemble Learning Theory by Tianyi Wang, Wenjun Yi, Youran Xia

“…To obtain the aerodynamic parameters of the projectile accurately, an aerodynamic parameter identification model based on ensemble learning theory and ELM optimized by improved particle swarm optimization is proposed. The improved particle swarm optimization algorithm (IPSO) with an adaptive update strategy is used to optimize the weight and threshold of ELM. …”
Get full text

Load Frequency Control of an Isolated Power System in Presence of Controllable Energy Storage Devices by Mallareddy Mounica, Chinta Prasad, D. J. V Prasad, M. Aruna Bharathi

“…In each case the effect of different storage units are studied for random load changes. Here particle swarm optimization algorithm (PSO) and improved particle swarm optimization technique (IPSO) are used to tune the parameters of storage units to provide proper control strategy for the system. …”
Get full text

Analysis of the generalization ability of neural networks based on the NN-MPS-interpolation model by Bo-Tao Wang, Zhe Sun, Li-Yuan Dou

“…This paper combines the Moving Particle Semi-implicit (MPS) method with neural networks to construct a data-driven model, which is then applied to solve the Poisson equation, aiming to reduce computational resource consumption. …”
Get full text

A simple and efficient attack on the Merkle-Hellman knapsack cryptosystem. by Jingguo Bi, Lei Su, Haipeng Peng, Lin Wang

“…In this paper, we present an improved algorithm to analyze the basic Merkle-Hellman public key cryptosystem. …”
Get full text