A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…Variational mode decomposition (VMD) parameters are optimized via a novel exponential triangular optimization (ETO) algorithm to extract multi-scale features. …”
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Sentiment Analysis Algorithm Based on Deep Transfer Learning for Multi-Source Data Fusion by Long Qin

“…The experiment outcomes indicate that the artificial bee colony-improved particle swarm optimization algorithm designed in the study has the minimum convergence value under single-peak and multi-peak test functions, with a standard deviation of less than 0.25 and a success rate of 100% in optimization. …”
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Improving Random Forest Algorithm for University Academic Affairs Management System Platform Construction by Jinyang Dai

“…In view of the complexity, heterogeneity, and security of college educational administration data and the difficulty of predicting and analyzing college students’ achievements, this paper designs a college educational administration management system platform based on improved random forest algorithm. Combining the advantages of three data-driven prediction algorithms, namely, random forest, extreme gradient boosting (XGBoost), and gradient boosting decision tree (GBDT), a model based on improved random forest algorithm is proposed. …”
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Evaluating the Efficiency of Gray Wolf Optimization and Colonial Competition Algorithm in Load Balancing of Distributed Systems by Asghar Molaei-Yeznabad, Amirhossein Dehghani

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Framework for truck–RPAS hybrid models in last-mile delivery by Armin Mahmoodi, Leila Hashemi, Jeremy Laliberte

“…To balance operating cost, service time, regulatory risk, and energy usage, a novel multi-objective mixed-integer linear programming model is developed. High-quality Pareto-optimal solutions are produced by the non-dominated sorting genetic algorithm II, which methodically manages trade-offs between the conflicting goals. …”
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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

“…However, the MPC’s performance depends on the optimal tuning of its key parameters, a challenge addressed using the Multivariate Gaussian Mixture Model Continuous Ant Colony Optimization (MGMM-<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>ACO</mi><mi>R</mi></msub></semantics></math></inline-formula>) algorithm. …”
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Deployment of On-Orbit Service Vehicles Using a Fuzzy Adaptive Particle Swarm Optimization Algorithm by Yaxiong Li, Xinglong Sun, Xinxue Liu, Jian Wu, Qingguo Liu

“…Second, an assignment optimization model of OSVs is established based on the discrete particle swarm optimization (DPSO) algorithm, laying the foundation of the next optimization model. …”
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A Feasibility Study of a Virtual Power Line Device to Improve Hosting Capacity in Renewable Energy Sources by Seong-Eun Rho, Sung-Moon Choi, Joong-Seon Lee, Hyun-Sang You, Seung-Ho Lee, Dae-Seok Rho

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A Judging Scheme for Large-Scale Innovative Class Competitions Based on Z-Score Pro Computational Model and BP Neural Network Model by Zhuoting Yu, Hongzhong Deng, Shuaiwen Tang

“…This study introduces a novel framework that integrates a genetic algorithm-based work cross-distribution model, advanced Z-score adjustment methods, and a BP neural network-enhanced score correction approach to tackle these issues. …”
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Improvement of Heavy Load Robot Positioning Accuracy by Combining a Model-Based Identification for Geometric Parameters and an Optimized Neural Network for the Compensation of Nong... by Yuxiang Wang, Zhangwei Chen, Hongfei Zu, Xiang Zhang, Chentao Mao, Zhirong Wang

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Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…[Objective] Factors such as road networks， temperature， and electric vehicle （EV） type affect the spatial and temporal distribution of EV charging loads. To improve prediction accuracy， a spatiotemporal EV charging load prediction model is developed by integrating multiparty information. …”
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A Novel Long Short-Term Memory Seq2Seq Model with Chaos-Based Optimization and Attention Mechanism for Enhanced Dam Deformation Prediction by Lei Wang, Jiajun Wang, Dawei Tong, Xiaoling Wang

“…However, the nonlinear relationships between deformation and time-varying environmental factors pose significant challenges, often limiting the accuracy of conventional and deep learning models. To address these issues, this study aimed to improve the predictive accuracy and interpretability in dam deformation modeling by proposing a novel LSTM seq2seq model that integrates a chaos-based arithmetic optimization algorithm (AOA) and an attention mechanism. …”
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A green hydrogen production model from solar powered water electrolyze based on deep chaotic Lévy gazelle optimization by Heba Askr, Mahmoud Abdel-Salam, Václav Snášel, Aboul Ella Hassanien

“…DeepGaz combines a new Chaotic-Lévy variant of the gazelle optimization algorithm (CGOA) with a recurrent neural network (RNN/LSTM) for hyperparameter optimization. …”
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A hybrid deep learning and differential evolution approach for accurate fake news detection by Shailendra Pratap Singh, Naween Kumar, Gyanendra Kumar, Ahamed Shafeeq B.M.

“…Experimental results on benchmark datasets demonstrate that the hybrid approach achieves superior accuracy, precision, recall, and F1-score compared to existing methods such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and standalone deep learning models. …”
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Presenting a multi-objective decision-making model for cost-time trade-off considering the time value of money and solving it using particle swarm optimization by Mohammadreza Shahriari

“…The model is then solved using the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to analyze the effects of time compression and activity delays on the outcomes.Findings:  The proposed model's results demonstrate its ability to optimize project resource usage by considering current constraints and capacities. …”
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A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data Inversion by Bin Yin, Jie Yang, Yue Li

“…After the benchmark function test, the improved algorithm has better optimization ability. …”
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Application of Three Neural Network Models in the Prediction ofStratospheric Wind Field by YUAN Junjie, LUO Rubin, LIAO Jun, YANG Zechuan, WANG Ning, LI Jun

“…The simulation results show that the neural network model can be applied to the prediction of stratospheric wind field and the BP neural networks optimized by genetic algorithm and particle swarm optimization can greatly improve the prediction accuracy of BP neural network, and the forecast wind speed is following the true value in a certain period of time. …”
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Optimized Rate Control Algorithm of High-Efficiency Video Coding Based on Region of Interest by Renjie Song, Yuandong Zhang

“…Firstly, the algorithm extracts the region of interest of video frames based on time and space domains by using the improved Itti model. …”
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Productivity Improvement of Garments Industry by Implementing Line Balancing Algorithms—A Case Study by Mst. Anjuman Ara, Nafisa Anjum, Dilir Ahbab, Mushfica Takia Sidiika, Risat Rimi Chowdhury

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Mitosis detection in histopathological images using customized deep learning and hybrid optimization algorithms. by Afnan M Alhassan, Nouf I Altmami

“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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