The different member equivalent circulating density prediction model and drilling parameter optimization under narrow density window by Wanchun Zhao, Wanchun Zhao, Zhipeng Yang, Tingting Wang, Yan Zhou, Wei Song, Jingrun Li, Peihong Zhai

“…The model uses nonlinear regression algorithms to predict ECD values for different members. …”
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Deploying UAV-based detection of bridge structural deterioration with pilgrimage walk optimization-lite for computer vision by Jui-Sheng Chou, Chi-Yun Liu, Pin-Jun Guo

“…This system uses UAVs to capture high-resolution images, which are then processed by the You Only Look Once (YOLO) models for instance segmentation. The YOLOv7 model, fine-tuned with the Pilgrimage Walk Optimization (PWO)-Lite algorithm, achieved the highest accuracy, recording a 65.6 % mAP50 on the testing set. …”
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Charge and discharge scheduling method for large-scale electric vehicles in V2G mode via MLGCSO by Songling Pang, Kaidi Fan, Meiyi Huo

“…Compared with traditional methods, the diversity and convergence of particle swarm learning are enhanced, and the optimization performance is improved. Simulation results indicate that when compared with three state-of-the-art optimizers, the optimization accuracy of the proposed algorithm is increased by at least 34% and the total cost is reduced by 3.14% and 1.62% respectively, demonstrating that the MLGCSO exhibits high optimization performance and remarkable optimization effects.…”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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Anterior cruciate ligament tear detection based on Res2Net modified by improved Lévy flight distribution by Peiji Yang, Yanan Liu, Fei Liu, Mingxia Han, Yadegar Abdi

“…By optimizing the model using the ILFD algorithm, the diagnostic efficiency is greatly improved. …”
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Hybrid procurement model for the construction of library literature and information resource procurement by Chuanyu Zhang, Changsheng Wang

“…The results show that using genetic algorithm to optimize support vector machine can effectively improve the prediction speed and prediction efficiency of the model. …”
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Sparse support path generation for multi-axis curved layer fused filament fabrication by Tak Yu Lau, Dong He, Yamin Li, Yihe Wang, Danjie Bi, Lulu Huang, Pengcheng Hu, Kai Tang

“…Currently, most support generation algorithms are for the conventional 2.5D printing, which are not applicable to multi-axis printing. …”
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A Comprehensive Analysis of the Triple-Hybrid Metamodel of MLP-PSO-ARIMA for Forecasting the FDSD Index: A Case Study of Khuzestan Province by Mohammad Ansari Ghojghar

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Multi-objective data collecting strategies for wireless sensor network based on the time variable multi-salesman problem and genetic algorithm by Hao FENG, Lei LUO, Yong WANG, Miao YE

“…Comparing to the traditional data collecting method with data route,the technology of wireless mobile nodes has gradually became a new technique in the wireless sensor network.As the solution to the visiting order of the static nodes was an intrinsic NP-hard problem,a more general multi-objective data colleting strategies based on multi-mobile nodes was proposed.The proposed data collecting technique was abstracted as a model of time variable multiple traveling salesman problem.Belonging to a discrete optimal problem,the proposed model was solved by with a proposed hybrid genetic algorithm to determine the paths of the multi-mobile nodes.The convergence analysis of the proposed algorithm was given.With the experiment of open dataset,the proposed model based on the time variable multiple traveling salesman problem and the proposed hybrid genetic algorithm certify a certain improvement to the efficiency and real-time ability.…”
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Evaluation and Optimization of Traditional Mountain Village Spatial Environment Performance Using Genetic and XGBoost Algorithms in the Early Design Stage—A Case Study in the Cold... by Zhixin Xu, Xiaoming Li, Bo Sun, Yueming Wen, Peipei Tang

“…It then employed the Wallacei_X plugin, which uses the NSGA-II algorithm for multi-objective genetic optimization (MOGO) to optimize five energy consumption and comfort objectives. …”
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A Hybrid Deep Learning-ViT Model and A Meta-Heuristic Feature Selection Algorithm for Efficient Remote Sensing Image Classification by Bilal Ahmed, Syed Rameez Naqvi, Tallha Akram, Lu Peng, Fahdah Almarshad

“…In this study, we introduced XNANet, a self-attention-based CNN network for image classification. Bayesian optimization has been used to initialize the hyperparameters of the proposed model to improve training on the radiographic images. …”
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Optimizing Berth Allocation for Maritime Autonomous Surface Ships (MASSs) in the Context of Mixed Operation Scenarios by Lixin Shen, Xueting Shu, Chengcheng Li, Tomaž Kramberger, Xiaoguang Li, Lixin Jiang

“…A large-scale simulation of the mixed-type berth allocation model is carried out using an improved simulated annealing algorithm. …”
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Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

“…The GJO algorithm fine-tunes the hyperparameters of MARL to improve generalization across different WSN configurations. …”
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Few-shot hotel industry site selection prediction method based on meta learning algorithms and transportation accessibility by Na Li, Huaishi Wu

“…Abstract Exploring the rationality of hotel location selection is of significant importance for optimizing urban spatial structure and improving tourism service levels. …”
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Application of the Bidirectional Encoder Representations from Transformers Model for Predicting the Abbreviated Injury Scale in Patients with Trauma: Algorithm Development and Vali... by Jun Tang, Yang Li, Keyu Luo, Jiangyuan Lai, Xiang Yin, Dongdong Wu

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Potential of random forest machine learning algorithm for geological mapping using PALSAR and Sentinel-2A remote sensing data: A case study of Tsagaan-uul area, southern Mongolia by Munkhsuren Badrakh, Narantsetseg Tserendash, Erdenejargal Choindonjamts, Gáspár Albert

“…Geological mapping in remote and geologically complex regions can be substantially improved by integrating remote sensing data with machine learning algorithms. …”
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Optimizing Transportation Costs: Enhancing Logistics Efficiency and Resource Utilization in Dynamic Environments by Cao Ngoc Anh, Tran Bich Thao, Tran Ba Hung, Trinh Thu Huong, Nguyen Viet Hung

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Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe by Deborah De Moortel, Michelle C Turner, Ella Arensman, Alex Binh Vinh Duc Nguyen, Víctor Gonzalez

“…These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or digital monitoring of worker performance). …”
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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

“…The superiority of the proposed model (XGB-MPA) compared to two other hybrid models, including XGB-PSO (Particle Swarm Optimization) and XGB-GWO (Grey Wolf Optimization) was also investigated. …”
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UAV Path Planners in Complex Environments: A Multi-Dimensional Perturbation Based on Artificial Bee Colony by Xuzhao Chai, Guanhao Zhou, Haoyu Wang, Ping Liu, Zhongyun Liu, Chao Li, Li Yan

“…In the onlooker bee phase, the curvature-guided elite neighbor search strategy is used to prioritizes high-curvature waypoints, enhancing optimization efficiency in complex terrain. Furthermore, path costs are independently modeled in the horizontal and vertical directions. …”
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