Addressing the Return Visit Challenge in Autonomous Flying Ad Hoc Networks Linked to a Central Station by Ercan Erkalkan, Vedat Topuz, Ali Buldu

“…This paper presents different approaches to efficiently directing UAVs and explains how heuristic algorithms can enhance our understanding and improve current methods for task assignments.…”
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Distribution Network Fault Risk Assessment Method Considering Difference in Entropy Value of Rare Factors by HUANG Junxian, CHEN Chun, CAO Yijia, QUAN Shaoli, WANG Yi

“…This method uses K-means clustering algorithm to classify failures based on their consequences and an improved association rule mining algorithm to analyze rare environmental factors and evaluate high-risk and low-probability factors, so as to realize the quantitative analysis of the association between rare factors and risk levels. …”
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Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM by Ramesh Bonela, Sriparna Roy Ghatak, Sarat Chandra Swain, Fernando Lopes, Sharmistha Nandi, Surajit Sannigrahi, Parimal Acharjee

“…In this work, a comprehensive planning framework for an electric vehicle charging ecosystem (EVCE) is developed, incorporating solar distributed generation (DG) and a distribution static compensator (DSTATCOM), to assess their long-term techno–economic and environmental impacts. The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. …”
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Response mitigations of adjacent structure with MPTMD under real and stochastic excitations by Mohammad Alibabaei Shahraki

“…The performance of the MPTMD system is optimized using the Particle Swarm Optimization (PSO) algorithm. …”
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State-of-the-Art Fault Detection and Diagnosis in Power Transformers: A Review of Machine Learning and Hybrid Methods by Lebo Dina Mashifane, Bongumsa Mendu, Bessie Baakanyang Monchusi

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Protection scheme of flexible MTDC transmission line based on ISSA-BiLSTM by LI Zheng, CHEN Tangxian, ZHANG Yunning, LIU Shuangyang, SUN Peisheng

“…Aiming at the problems of poor ability to withstand transition resistance and low recognition accuracy of multi-terminal flexible DC transmission line protection, a diagnostic model combining an improved sparrow search algorithm (ISSA) and bidirectional long short-term memory network (BiLSTM) is proposed. …”
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Route Generation and Built Environment Behavioral Mechanisms of Generation Z Tourists: A Case Study of Macau by Ying Zhao, Pohsun Wang, Yafeng Lai

“…Building on this behavioral mechanism, an interest-based Ant Colony Optimization (ACO) algorithm is implemented by incorporating point-of-interest (POI) preferences and distance matrices to improve personalized route generation. …”
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Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks by Jianhong Gan, Runqing Kang, Xun Deng, Chentao Mao, Zhibin Li, Peiyang Wei, Chunjiang Wu, Tongli He

“…Finally, the particle swarm optimization algorithm is used for hyperparameter optimization to improve the prediction accuracy. …”
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Transmission Line Anomaly Detection and Real-Time Monitoring System Combining Edge Computing and EfficientDet by Menghao Lin, Yang Ding, Tianle Wang, Yang Liu, Zewei Li

“…In the target recognition part, an improved EfficientDet algorithm is adopted as the main body, and the aspect ratio of anchor boxes in the algorithm is optimized using K-means clustering algorithm. …”
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Predicting Earthquake Casualties and Emergency Supplies Needs Based on PCA-BO-SVM by Fuyu Wang, Huiying Xu, Huifen Ye, Yan Li, Yibo Wang

“…Subsequently, the optimal hyperparameters for the SVM model are obtained using the Bayesian Optimization algorithm. …”
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Deep Reinforcement Learning Based Active Disturbance Rejection Control for ROV Position and Attitude Control by Gaosheng Luo, Dong Zhang, Wei Feng, Zhe Jiang, Xingchen Liu

“…The deep deterministic policy gradient (DDPG) algorithm was used to optimize the linear extended state observer (LESO). …”
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Full-Waveform Inversion of Two-Parameter Ground-Penetrating Radar Based on Quadratic Wasserstein Distance by Kai Lu, Yibo Wang, Heting Han, Shichao Zhong, Yikang Zheng

“…In this study, the Wasserstein distance is computed by using entropy regularization and the Sinkhorn algorithm to reduce computational complexity and improve efficiency. …”
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Dry-Type Air-Core Series Reactor Turn-to-Turn Short Circuit Fault Detection Method Based on Multi-Parameter Data Fusion by WANG Yin, WANG Yuanyuan, CAO Chengjun, ZHANG Lizhi, YIN Youpeng, JI Hongzhen, DOU Di

“…Subsequently， the denoised features with high saturation are input into the k-nearest neighbors （KNN） algorithm to construct a fault identification and classification model. …”
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CHPOA-DBN Transformer Fault Diagnosis Method Considering Sample Within-Class Imbalance by Shuang WANG, Qian LUO, Bo TANG, Lan JIANG, Jin LI

“…Then, the Tent chaotic map embedded chaotic hybrid pelican optimization algorithm (CHPOA) is developed to optimize the number of hidden layer nodes and reverse fine-tuning learning rate of DBN, and the CHPOA-DBN transformer fault diagnosis model is constructed. …”
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Application of Support Vector Machines in High Power Device Technology by RAO Wei, LI Yong, YAN Ji

“…It presented a support vector machines regression model (SVR) with Gauss kernel function (RBF). The best prediction model was obtained by normalization and dimensionality reduction for data and cross-validation for parameter optimization. …”
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Adaptive drive-based integration technique for predicting rheological and mechanical properties of fresh gangue backfill slurry by Chaowei Dong, Jianfei Xu, Nan Zhou, Jixiong Zhang, Hao Yan, Zejun Li, Yuzhe Zhang

“…Analysis demonstrates that the particle swarm optimal (PSO) algorithm based on adaptive adjustment strategy can effectively optimize the hyperparameters of support vector regression (SVR), and the MC-PSO-SVR model exhibits better predictive capability (R2> 0.88) and lower error coefficients (MAE, RSE, and RMSE values approaching 0) and narrower widths of 95 % confidence intervals for yield stress, plastic viscosity, fluidity, and UCS. …”
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Advanced intrusion detection technique (AIDT) for secure communication among devices in internet of medical things (IoMT) by M. Ramya, Pradeep Sudhakaran, Yuvaraj Sivagnanam, C. Santhana Krishnan

“…By employing the integrated patient sensing and network traffic datasets, our research achieves a superior accuracy rate of 96.4% in network intrusion detection compared to the competing algorithms. Furthermore, we incorporated a comprehensive analysis of the implementation of different classification algorithms in IoMT network intrusion detection, further supporting the claim that the proposed framework performs marginally better than alternative models.…”
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Enhanced water saturation estimation in hydrocarbon reservoirs using machine learning by Ali Akbari, Ali Ranjbar, Yousef Kazemzadeh, Dmitriy A. Martyushev

“…To improve model performance, a Gaussian outlier removal technique was applied to eliminate anomalous data points. …”
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Machine Learning and Metaheuristics Approach for Individual Credit Risk Assessment: A Systematic Literature Review by Álex Paz, Broderick Crawford, Eric Monfroy, José Barrera-García, Álvaro Peña Fritz, Ricardo Soto, Felipe Cisternas-Caneo, Andrés Yáñez

“…Although no unified experimental comparison was conducted due to heterogeneity in study protocols, this structured summary reveals consistent trends in algorithm effectiveness and evaluation practices. The review concludes with practical recommendations and outlines future research directions to improve fairness, scalability, and real-time application in credit risk modeling.…”
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A Hybrid Approach of DenseNet121 with Attention and Bi-LSTM for Yoga Pose Estimation by Aarthy K., Alice Nithya

“…The system is designed to integrate advanced AI techniques, providing an innovative approach to pose recognition that leverages several sophisticated machine learning models and algorithms to enhance performance. The pre-processing stage involves applying a Wiener Filter (WF) for effective noise removal, ensuring that the data is clean and ready for analysis. …”
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