An interactive ball training partner robot based on YOLOv5 by Zeng Yangji, Liu Zihong, Cai Yong, Guo Xingchen, Mo Jinlong

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Adaptive Tracking Method for Time-Varying Underwater Acoustic Channel Based on Dynamic Gaussian Window by Zemin Zhou, Zhikuan Chen, Bin Wang, Yunjiang Zhao, Yi Lou

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An Edge-Computing-Driven Approach for Augmented Detection of Construction Materials: An Example of Scaffold Component Counting by Xianzhong Zhao, Bo Cheng, Yujie Lu, Zhaoqi Huang

“…Two practical case studies demonstrated that the method, when deployed on edge devices, achieved 98.9% accuracy and reduced time consumption for counting tasks by 87.9% compared to the conventional method. This research provides an edge-computing-driven framework for counting massive materials, establishing a comprehensive workflow for intelligent applications in construction management. …”
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Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

“…To improve the accuracy of dissolved oxygen prediction,this paper researches and proposes a prediction method that combines seagull optimization algorithm (SOA) with support vector machine (SVM) and BP neural network,prepares four prediction schemes based on the monthly dissolved oxygen monitoring data of the Jinghong Power Station in Xishuangbanna,a national important water supply source in Yunnan Province,from January 2009 to September 2020,optimizes the key parameters of SVM and weight threshold of BP neural network by SOA to construct SOA-SVM and SOA-BP models,predicts the dissolved oxygen of Jinghong Power Station based on the models,and compares the prediction results with those of SVM and BP models.The results show that:The absolute values of the average relative errors of the SOA-SVM and SOA-BP models for the 4 schemes of dissolved oxygen prediction are between 4.07%~4.98% and 3.85%~4.83%,and that of the average absolute errors are 0.309~0.374 mg/L and 0.294~0.371 mg/L,respectively.With better prediction accuracy than SVM and BP models,they have good prediction accuracy and generalization ability.SOA can effectively optimize the key parameters of SVM and weight threshold of BP neural network.SOA-SVM and SOA-BP models are feasible for dissolved oxygen prediction,which can provide references for related prediction research.…”
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Assimilation of the total electron content obtained from GNSS to a model of the ionosphere using a hierarchical Bayesian network by Tang Jun, Hu Jiacheng, Zhang Wei, Fan Cihang, Zhou Qiangbo

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A Novel Linguistic Relational Fuzzy C-Means by Peerawich Phaknonkul, Sansanee Auephanwiriyakul, Nipon Theera-Umpon

“…The proposed algorithm does not defuzzify fuzzy attributes beforehand. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Study on Tourism Development Using CRITIC Method for Tourist Satisfaction by Xi Yang, Noor Azman Ali, Huam Hon Tat

“…This paper presents a novel approach for evaluating tourist satisfaction and developing optimized strategies by integrating the CRITIC method, deep learning with Multilayer Perceptron (MLP), and Genetic Algorithms (GA). The CRITIC method was employed to calculate the weights of various satisfaction indicators, such as accommodation quality and local services, based on their variance and correlation. …”
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Robust Photovoltaic Power Forecasting Model Under Complex Meteorological Conditions by Yuxiang Guo, Qiang Han, Tan Li, Huichu Fu, Meng Liang, Siwei Zhang

“…Experimental results demonstrate that the proposed model exhibits superior robustness across multiple evaluation metrics, including coefficient of determination, mean square error, mean absolute error, and root mean square error, with comparatively low latency. This research provides valuable model support for reliable PV system dispatch and its application in smart grids.…”
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Thermodynamic optimization of a multi-generation system integrating gas turbine-helium reactor cycle with hydrogen production and desalination by Yang Wang, Yuliang Chen, Zhen Su

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An autonomous vehicles’ test case extraction method: Example of vehicle-to-pedestrian scenarios by Zhengping Tan, Qian Wang, Wenhao Hu, Pingfei Li, Liangliang Shi, Hao Feng

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Parameter fitting-based traveling wave fault location method for multi-terminal DC grids by Le Liu, Fan Xie, Xiaoning Kang, Zhiguo Hao, Aleksandra Lekić, Marjan Popov

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Enhancing Agricultural Futures Return Prediction: Insights from Rolling VMD, Economic Factors, and Mixed Ensembles by Yiling Ye, Xiaowen Zhuang, Cai Yi, Dinggao Liu, Zhenpeng Tang

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A High-Resolution Spectral Analysis Method Based on Fast Iterative Least Squares Constraints by Yanyan Ma, Haixia Kang, Weifeng Luo, Yunxiao Zhang, Lintao Luo

“…Based on this, we propose a least squares constrained spectral analysis method using a greedy fast shrinkage algorithm. This method replaces the traditional Tikhonov regularization objective function with an L1-norm regularized objective function and employs a greedy fast shrinkage algorithm. …”
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Protecting digital assets using an ontology based cyber situational awareness system by Tariq Ammar Almoabady, Yasser Mohammad Alblawi, Ahmad Emad Albalawi, Majed M. Aborokbah, S. Manimurugan, Ahmed Aljuhani, Hussain Aldawood, P. Karthikeyan

“…These results outperformed the benchmarks, highlighting the model’s effectiveness in proactive anomaly detection and cyber situational awareness enhancement.DiscussionThe integration of STIX and ontology development within the proposed methodology significantly enhanced threat information standardization and semantic analysis. The dual-algorithm approach provided improved detection capabilities compared to traditional methods, underscoring its potential for scalable and effective cybersecurity applications. …”
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Fusion of UAV-Acquired Visible Images and Multispectral Data by Applying Machine-Learning Methods in Crop Classification by Zuojun Zheng, Jianghao Yuan, Wei Yao, Paul Kwan, Hongxun Yao, Qingzhi Liu, Leifeng Guo

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Embedded feature fusion for multi-label criteria selection via local search strategy and particle swarm optimization by Suhua Chen, Xu Fang, Feng Zhai, Li Wang, Lin Lv

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Using artificial intelligence methods for the optimal synthesis of reversible networks by Taras Kyryliuk, Mykhailo Palahuta, Vitaly Deibuk

“…Reversible logic allows for a reduction in energy and information losses because logical reversible operations are performed without loss. The research synthesized optimal reversible circuits based on reversible gates using evolutionary algorithms and compare them with existing analogues. …”
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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

“…In terms of clustering performance, the weighted K-means clustering algorithm achieves higher Silhouette coefficient by 0.0138 and 0.1885 compared with the weighted agglomerative hierarchical clustering algorithm (weighted AHC) and weighted DBSCAN, respectively, the Calinski-Harabasz index is higher by 3.8017 and 22.4039, and the Davies-Bouldin index is lower by 0.1006 and 0.4889, demonstrating superior clustering results. …”
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Clustering Iranian women according to their menopausal severity symptoms and exploring the factors associated with severe categories, using baseline category logit model by Fahimeh Hoseinzadeh, Habibollah Esmaily, Sedigheh Ayatiafin, Azadeh Saki

“…Result K-Means clustering algorithm, extracted three major clusters based on different menopausal symptoms. …”
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