Optimization method of building energy efficiency design based on decomposition multi objective and agent assisted model by Bai Chaoqin, Yang Zhuoyue

“…For the same building type, the average volume measurements of the multi-objective particle swarm optimization algorithm assisted by the decomposed surrogate model are 21153 and 40230, respectively. …”
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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…From the results measured by evaluation metrics, the proposed model ANN with the combination of parameter tuning, feature selection algorithm, SMOTE-ENN, and optimal hyper-parameters demonstrates superior performance compared to traditional methods, achieving an F1 Score of 98.5% and an accuracy of 98.6%. …”
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An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem by Jianxia Zhang, Jianxin Zhang, Feng Zhang, Minglu Chi, Linbin Wan

“…At last, the economic load dispatch problem could be optimized by the proposed improved symbiosis particle swarm optimization algorithm. In addition, two different kinds of practical examples were also adopted for algorithm evaluation. …”
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Simulation of a Bio-Inspired Flocking-Based Aggregation Behaviour in Swarm Robotics by Samira Rasouli, Kerstin Dautenhahn, Chrystopher L. Nehaniv

“…The results of the experiments demonstrated that the proposed algorithm is robust and scalable. Moreover, we compared our proposed algorithm with another implementation of the flocking-based self-organizing aggregation behaviour based on Reynolds’ rules in a swarm of e-puck robots. …”
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Multidimensional Resource Task Scheduling Based on Particle Swarm Optimization in Edge Computing by Zhonglu Zou, Zhuxin Zhai, Xin Yan, Zilin You, Liming Chen

“…The proposed approach enables the simultaneous scheduling of multiple tasks while iteratively adjusting the inertia weight and learning factors in the discrete particle swarm optimization (DPSO) algorithm. Experimental results with different types of applications show that, compared to the baseline scheduling methods, the proposed strategy can flexibly adapt to the varying demands of different task types and effectively reduce the imbalance in the utilization of multi-dimensional cluster resources. …”
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Prediction of cold region dew volume based on an ECOA-BiTCN-BiLSTM hybrid model by Yi Zhang, Pengtao Liu, Yingying Xu, Meng Zhang

“…Comparative experiments were conducted against the BiTCN model, the BiLSTM model, the original BiTCN-BiLSTM model, and other models optimized with advanced swarm intelligence algorithms. The experimental results demonstrate that the proposed model achieved a mean absolute error (MAE) of 0.002424, a root mean square error (RMSE) of 0.003984, and a mean absolute percentage error (MAPE) of 0.123050, with a coefficient of determination R2 of 0.999840. …”
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A hybrid ensemble framework with particle swarm optimization for network anomaly detection by Narinder Verma, Neerendra Kumar, Gourav Kumar, Kuljeet Singh

“…We propose an adaptive particle swarm optimization (PSO)-optimized ensemble learning framework tailored to address these challenges in modern IDS applications. …”
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Swarm-Based Trajectory Generation and Optimization for Stress-Aligned 3D Printing by Xavier Guidetti, Efe C. Balta, and John Lygeros

“…In this study, we present a novel swarm-based approach for generating optimized stress-aligned trajectories for 3D printing applications. …”
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An innovative complex-valued encoding black-winged kite algorithm for global optimization by Chengtao Du, Jinzhong Zhang, Jie Fang

“…Abstract The black-winged kite algorithm (BKA) constructed on the black-winged kites’ migratory and predatory instincts is a revolutionary swarm intelligence method that integrates the Leader tactic with the Cauchy variation procedure to retrieve the expansive appropriate convergence solution. …”
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Exploring the possibilities of MADDPG for UAV swarm control by simulating in Pac-Man environment by Artem Novikov, Sergiy Yakovlev, Ivan Gushchin

“…This paper explores the application of the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) for model training to control UAV swarms in dynamic and adversarial scenarios. Using a modified Pac-Man environment, Pac-Man represents a target UAV, and Ghosts represents the UAV swarm that counteracts it. …”
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Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO by Enlai ZHANG, Yi CHEN, Liang SU, Ruoyu ZHONGLIAN, Xianyi CHEN, Shangfeng JIANG

“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
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AFCPOA-based optimal dispatch of hybrid PV-wind DGs for voltage stability and loss reduction in radial distribution network by Sunil Ankeshwarapu

“…Its performance was evaluated on the IEEE 33-bus system and benchmarked against Hybrid Genetic Algorithm (GA)-Jaya, Jaya Algorithm, Shuffled Frog-Leaping Algorithm (SFLA), Particle Swarm Optimization (PSO), and GA. …”
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Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

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Optimizing Unmanned Vehicle Navigation: A Hybrid PSO-GWO Algorithm for Efficient Route Planning by Gökhan Altun, İlhan Aydın

“…In the hybrid algorithm, the simplicity and powerful global search capabilities of the Particle Swarm Optimization (PSO) algorithm are combined with the strong exploration and local minimum avoidance features of the Grey Wolf Optimization (GWO) algorithm. …”
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MULTI-OBJECTIVE OPTIMIZATION DESIGN OF MW WIND TURBINE AIRFOILS by LI YingJue, WEI KeXiang, ZHOU Zhou

“…Designed to improve the aerodynamic performance of the blade and reduce noise,this paper aims to improve the aerodynamic performance of the blade and reduce the noise,optimize the airfoil structural equation based on the improved Hicks-Henne function,and combine the multi-objective particle swarm optimization algorithm to optimize the design of the S8035 airfoil. …”
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An optimized support vector machine for lung cancer classification system by Mayowa O. Oyediran, Olufemi S. Ojo, Ibrahim A. Raji, Abidemi Emmanuel Adeniyi, Oluwasegun Julius Aroba, Oluwasegun Julius Aroba

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Dynamic Inversion Method for Concrete Gravity Dam on Soft Rock Foundation by Guanglin Yin, Chaoning Lin, Taozhen Sheng, Wenbo Xue, Tongchun Li, Siyu Chen

“…To address this limitation, an improved particle swarm optimization (PSO) algorithm is developed for dynamic parameter inversion, combining real-time monitoring data with finite element modeling to evaluate the time-varying elastic modulus of the foundation. …”
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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

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Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees by Shobha Aswal, Neelu Jyothi Ahuja, Ritika Mehra

“…In this paper, we propose a novel structural formation of the oblique decision tree (OBT) using a swarm intelligence technique, namely, the Binary Bat Swarm Algorithm (BBSA). …”
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Research on Oil Well Production Prediction Based on GRU-KAN Model Optimized by PSO by Bo Qiu, Jian Zhang, Yun Yang, Guangyuan Qin, Zhongyi Zhou, Cunrui Ying

“…These selected features are used as input to the GRU-KAN model to establish the oil well production prediction model. Then, the Particle Swarm Optimization (PSO) algorithm is used to enhance the predictive performance. …”
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