A Firefly Algorithm and Elite Ant System-Trained Elman Neural Network for MPPT Algorithm of PV Array by Yan Zhang, Ya-jun Wang, Han Li, Jia-Bao Chang, Jia-qi Yu

“…Furthermore, MATLAB/Simulink is adopted to acquire the datasets of irradiance, temperature, and maximum voltage and validate the reliability and superiority of the proposed algorithm under complex atmospheric conditions. The tracking characteristic, response speed, and efficiency of the proposed MPPT algorithm are contrasted with the particle swarm optimization (PSO), ant colony optimization (ACO), ACO-artificial neural network (ACO-ANN), and PSO-RBF neural network (PSO-RBNFNN) algorithm via simulation. …”
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Comprehensive Fault Location on Transmission Lines Considering Variation in Line Parameters and Saturation in Current Transformers by Duy C. Huynh, Loc D. Ho

“…To achieve accurate parameter and current estimation at both terminals of the transmission line, advanced artificial bee colony (ABC) algorithms such as Chaos ABC algorithm and Chaos particle swarm optimization (PSO)-ABC algorithm are employed. …”
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Voltage and frequency regulation in wind penetrated deregulated power system using an electric vehicle and IPFC assisted model predictive controller by Vineet Kumar, Vineet Kumar, Ark Dev

“…The proposed controller is benchmarked against conventional PID, fractional-order PIλDF, and MPC schemes optimized via Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA). …”
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Game algorithm based on link quality: Wireless sensor network routing game algorithm based on link quality by Zhanjun Hao, Jiaojiao Hou, Jianwu Dang, Xiaochao Dang, Nanjiang Qu

“…In the simulation experiment, the influence of the change of link quality parameters on the performance of the algorithm is analyzed, and the proposed algorithm is compared with non-linear weight particle swarm optimization (NWPSO) algorithm and Low Energy Adaptive Clustering Hierarchy-Improvement (LEACH-IMPT) algorithm in three aspects: the number of surviving nodes, network lifetime, and network energy consumption. …”
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Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO by Adel Taieb, Moêz Soltani, Abdelkader Chaari

“…This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO) Fuzzy Optimal Model Predictive Control (FOMPC) using the Adaptive Particle Swarm Optimization (APSO) algorithm. …”
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Enhancing power system stability by coordinating a wind turbine voltage regulator and lead-lag power system stabilizer using GOOSE optimization by Nader M. A. Ibrahim, Attia A. El-Fergany, Bassam A. Hemade

“…The GOA performance compared with the Osprey Optimization Algorithm (OOA) and Particle Swarm Optimizer (PSO). …”
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Swarm intelligence based classification rule induction (CRI) framework for qualitative and quantitative approach: An application of bankruptcy prediction and credit risk analysis by J. Uthayakumar, T. Vengattaraman, P. Dhavachelvan

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Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

“…Different MOAs, including a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), Cuckoo Search (CS), Bat Algorithm (BA), Shark Smell Optimization (SSO), Whale Optimization Algorithm (WOA), Harris Hawk''s Optimization (HHO), and hybrid of WOA and CS (WOA_CS), were developed for Muskingum calibration. …”
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Optimal Mobile Robot Navigation in Unknown Environments using Different Optimization Techniques by Sarah H. Abdulridha, Dheyaa J. Kadhim

“…After that, three intelligent optimization algorithms are proposed to enhance the performance of the EKF-SLAM trajectory for the mobile robot, these algorithms are: particle swarm optimization (PSO), chaotic particle swarm optimization (CPSO) and genetic optimization (GA). …”
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Smart Energy Strategy for AC Microgrids to Enhance Economic Performance in Grid-Connected and Standalone Operations: A Gray Wolf Optimizer Approach by Sebastian Lobos-Cornejo, Luis Fernando Grisales-Noreña, Fabio Andrade, Oscar Danilo Montoya, Daniel Sanin-Villa

“…To assess performance, 100 independent runs per method were conducted, comparing GWO against particle swarm optimization (PSO) and genetic algorithms (GAs). …”
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Enhanced grey wolf optimization for maximum power point tracking in photovoltaic systems with hybrid battery-supercapacitor storage by Chirine Benzazah, Najoua Mrabet, Ahmed ElAkkary, Fathallah Rerhrhaye

“…The proposed method was compared with conventional and metaheuristic optimisation techniques, including Particle Swarm Optimization, Ant Colony Optimization, and the standard Grey Wolf Optimization algorithm. …”
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Medium- and Long-term Runoff Prediction Based on SMA-LSSVM by TIAN Jinghuan, LI Congxin, LI Ang

“…Medium-and long-term runoff prediction is extremely important for flood control,disaster reduction and the utilization efficiency improvement of water resources.To avoid the influence of prediction model parameters on prediction accuracy,this paper proposes a medium-and long-term runoff prediction model based on least squares support vector machine (LSSVM) optimized by the slime mold algorithm (SMA).Firstly,five standard test functions are selected to compare the simulation results of SMA and particle swarm optimization (PSO) algorithms in different dimensions.Secondly,SMA is used to optimize the penalty parameters and kernel parameters of LSSVM,and the comparison models of LSSVM and PSO-LSSVM are constructed.Finally,the models are verified with the monthly runoff of Manwan Hydropower Station Reservoir and Yingluoxia Hydrological Station as prediction examples.The results show that the mean square error of the SMA-LSSVM model is 29.26% and 7.42% lower than those of the LSSVM and PSO-LSSVM models,respectively,in the monthly runoff prediction of the Manwan station,and 32.61% and 6.61% lower,respectively,in the monthly runoff prediction of the Yingluoxia station.The proposed SMA-LSSVM model has better comprehensive prediction performance and also provides a new method for medium- and long-term runoff prediction.…”
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Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attenti... by Santosh Prabhakar Agnihotri, Mandar Padmakar Joshi

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Neural network-based link prediction algorithm by Yonghao PAN, Hongtao YU, Shuxin LIU

“…To improve the difference existed in the link prediction accuracy and adaptability of different topology structure similarity based methods,a neural network-based link prediction algorithm,which fused similarity indices by neural network was proposed.The algorithm uses neural network to study the numerical characteristics of different similarity indices,and uses particle swarm optimization to optimize the neural network,and calculates the fusion index by the optimized neural network model.The experiment on the real network data set shows that the prediction accuracy of the algorithm is obviously higher than that before the fusion,and the accuracy is better than the existing methods.…”
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Reinforcing long lead time drought forecasting with a novel hybrid deep learning model: a case study in Iran by Mahnoosh Moghaddasi, Mansour Moradi, Mahdi Mohammadi Ghaleni, Zaher Mundher Yaseen

“…Key parameters of the DFFNN, including the number of neurons and layers, learning rate, training function, and weight initialization, were optimized using the WSO algorithm. The model’s performance was validated against two established optimizers: Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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Link Prediction in Social Networks Using the HTOA by Foad Asef, Vahid Majidnezhad, Mohammad-Reza Feizi-Derakhshi

“…Comparisons with other optimization techniques, such as the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), reveal that the proposed method outperforms them in selecting key features and achieving faster convergence. …”
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QPSO-Based Adaptive DNA Computing Algorithm by Mehmet Karakose, Ugur Cigdem

“…This new approach aims to perform DNA computing algorithm with adaptive parameters towards the desired goal using quantum-behaved particle swarm optimization (QPSO). …”
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System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario by Wenhao Luo, Yuan Zeng, Ximeng Zheng, Lingyan Zha, Weicheng Cai, Qing Wang, Jingjin Zhang

“…Finally, a network coverage optimization scheme was designed by combining a particle swarm optimization (PSO) algorithm and link quality prediction model, and a reliable cluster routing protocol was designed by combining K-means algorithm. …”
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AMBWO: An Augmented Multi-Strategy Beluga Whale Optimization for Numerical Optimization Problems by Guoping You, Zengtong Lu, Zhipeng Qiu, Hao Cheng

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Optimal Assembly Position and Multi-objective Trajectory Optimization for Dual Robotic Arms Collaboration by Wang Tianrui, Tao Ping

“…In order to solve the limitation and randomness in determining the collaborative assembly position of dual robotic arms by the traditional manual demonstration method, and taking the coordinated assembly of dual robotic arms axle holes as the engineering background, this study uses the particle swarm algorithm to perform multiple searches for the optimal assembly position for the overall global flexibility in the collaborative assembly process and carries out multi-objective trajectory optimization based on the optimal position, with respect to the overall motion flexibility and trajectory planning of the robotic arm. …”
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