Radial Basis Function Neural Network Based on an Improved Exponential Decreasing Inertia Weight-Particle Swarm Optimization Algorithm for AQI Prediction by Jinna Lu, Hongping Hu, Yanping Bai

“…This paper proposed a novel radial basis function (RBF) neural network model optimized by exponential decreasing inertia weight particle swarm optimization (EDIW-PSO). …”
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Rejection-Free Monte Carlo Simulation of QUBO and Lechner–Hauke–Zoller Optimization Problems by Yoshihiro Nambu

“…Landscapes of success probabilities of finding the globally optimal solution as well as feasible solutions were evaluated as a function of a set of hyper-parameters used to characterize the weights of cost and penalty functions. …”
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Short-Term Power Load Forecasting Method based on Glowworm Swarm Optimization Algorithm by Haihong FAN

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Risk assessment of corn borer based on feature optimization and weighted spatial clustering: a case study in Shandong Province, China by Yanan Zuo, Min Ji, Jiutao Yang, Zhenjin Li, Jing Wang

“…Addressing the prevalent issue of class imbalance in pest datasets, a feature optimization model using Borderline-SMOTE to improve the Genetic Algorithm-Random Forest (GA-RF) was constructed, combined with Pearson correlation coefficient to jointly obtain a subset of features that affect corn borer. …”
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Multi-Condition Magnetic Core Loss Prediction and Magnetic Component Performance Optimization Based on Improved Deep Forest by Haotian Shi, Zipeng Jin

“…To achieve high efficiency and high power density designs, it is essential to study core loss characteristics and optimize operating parameters. This paper proposes a core loss prediction model based on an improved deep forest algorithm and information entropy-enhanced genetic algorithm. …”
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Improvement of reading platforms assisted by the spring framework: A recommendation technique integrating the KGMRA algorithm and BERT model by Yawen Su

“…To address these limitations, this study introduces a novel recommendation system that combines the Knowledge Graph-based Multi-Relational Association (KGMRA) algorithm with the Bidirectional Encoder Representations from Transformers (BERT) model. …”
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Dynamic parking space allocation at urban scale: Problem formulation and resolution by Hanae Errousso, Jihane El Ouadi, El Arbi Abdellaoui Alaoui, Siham Benhadou

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An Ensemble Model for Predicting Cardiovascular Disease utilizing Nature Inspired Optimization by Annwesha Banerjee Majumder, Somsubhra Gupta, Sourav Majumder, Dharmpal Singh

“… This paper represents an efficient model for heart disease prediction model utilizing an ensemble mechanism optimized through BAT algorithm. …”
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Fractional order modelling and optimal control of dual active bridge converters by Zengbo Dong, Peng Yang, Qian Li, Mingxiao Zhang, Yujian Chang, Shuohe Wang

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Optimization of deep learning architecture based on multi-path convolutional neural network algorithm by Chuan Zhou, Yan Liu, Xinghan An, Xiyao Xu, Hao Wang

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Energy-saving optimization solution for multiple freight trains based on maFOA algorithm by LAN Li, LI Le, MA Ruijie

“…Additionally, a multi-strategy adaptive fruit fly optimization algorithm for population partitioning (maFOA) was proposed, to address the challenges faced by existing algorithms in solving complex nonlinear “train-track-grid" models, which often result in low convergence accuracy. …”
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Supply Chains Problem During Crises: A Data-Driven Approach by Farima Salamian, Amirmohammad Paksaz, Behrooz Khalil Loo, Mobina Mousapour Mamoudan, Mohammad Aghsami, Amir Aghsami

“…Results demonstrate significant improvements in cost reduction, resource allocation, and service levels, highlighting the model’s practical applicability in real-world scenarios. …”
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Passenger Flow Prediction for Rail Transit Stations Based on an Improved SSA-LSTM Model by Xing Zhao, Chenxi Li, Xueting Zou, Xiwang Du, Ahmed Ismail

“…According to the experimental results, the proposed SSA-LSTM model has a more effective performance than the Support Vector Regression (SVR) method, the eXtreme Gradient Boosting (XGBoost) model, the traditional LSTM model, and the improved LSTM model with the Whale Optimization Algorithm (WOA-LSTM) in the passenger flow prediction. …”
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Aerodynamic Optimization Method for Propeller Airfoil Based on DBO-BP and NSWOA by Changjing Guo, Zhiling Xu, Xiaoyan Yang, Hao Li

“…To address the issues of tedious optimization processes, insufficient fitting accuracy of surrogate models, and low optimization efficiency in drone propeller airfoil design, this paper proposes an aerodynamic optimization method for propeller airfoils based on DBO-BP (Dum Beetle Optimizer-Back-Propagation) and NSWOA (Non-Dominated Sorting Whale Optimization Algorithm). …”
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Optimizing Vehicle Body Cross-Sections Using a Parametric Mathematical Model by Zhaohui Hu, Shuai Mo, Huang Liu, Fuhao Mo

“…In the example of this paper, after the optimization of the established meshless model, the mass of the whole vehicle is reduced by 30%, and the stiffness of the whole vehicle is greater than that of the benchmark vehicle (5128 N/mm, 4386 N/mm), and at the same time, compared with the conceptual design method of the body of CAE technology, the modeling time is greatly reduced, and the computational efficiency of the analytical method is greatly improved compared with the finite element method.…”
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An optimal control method considering degradation and economy based on mutual learn salp swarm algorithm of an islanded zero‐carbon DC microgrid by Ying Han, Yujing Hou, Luoyi Li, Weifeng Meng, Qi Li, Weirong Chen

“…This paper provides an optimal control method based on the mutual learn salp swarm algorithm (MLSSA) in real‐time, which aims to enhance the economy and extend the system's service life. …”
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Air quality prediction enhanced by a CNN-LSTM-Attention model optimized with an advanced dung beetle algorithm by Xiaojie Zhou, Majid Khan Majahar Ali, Farah Aini Abdullah, Lili Wu, Ying Tian, Tao Li, Kaihui Li

“…This study proposes a hybrid CNN-LSTM-Attention model optimized with an improved Dung Beetle Optimization (IDBO) algorithm to enhance predictive performance. …”
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Urban flood hazard assessment using FLA-optimized boost algorithms in Ankara, Türkiye by Enes Gul

“…By applying advanced boosting algorithms—specifically, XGBoost, GradientBoost, and CatBoost—along with hyperparameter optimization through the Fick’s law algorithm (FLA), this research introduces an innovative methodology aimed at improving the reliability and accuracy of flood hazard assessments in Ankara’s urban landscape. …”
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Mechanism- and data-driven algorithms of electrical energy consumption accounting and prediction for medium and heavy plate rolling by Qiang Guo, Zimeng Zhou, Jie Li, Fengwei Jing

“…Energy consumption accounting and prediction in the medium and thick plate rolling process are crucial for controlling costs, improving production efficiency, optimizing equipment management, and enhancing the market competitiveness of enterprises. …”
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Concrete Creep Prediction Based on Improved Machine Learning and Game Theory: Modeling and Analysis Methods by Wenchao Li, Houmin Li, Cai Liu, Kai Min

“…Therefore, in this study, three machine learning (ML) models, a Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting Machine (XGBoost), are constructed, and the Hybrid Snake Optimization Algorithm (HSOA) is proposed, which can reduce the risk of the ML model falling into the local optimum while improving its prediction performance. …”
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