Digital security risk identification and model construction of smart city based on deep learning by Zhilei Zhao

“…Abstract In view of the network security risks caused by the integration of the Industrial Internet of Things (IIoT) in the construction of smart cities, this research proposes a digital security identification model (DL-DSIM) based on deep learning, which aims to improve the data transmission efficiency and system security in the smart city environment. …”
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A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data by Ovais A Jaffery, Lea Melki, Gregory Slabaugh, Wilson W Good, Caroline H Roney

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Effectiveness of machine learning models in diagnosis of heart disease: a comparative study by Waleed Alsabhan, Abdullah Alfadhly

“…An extensive array of preprocessing techniques is thoroughly examined in order to optimize the predictive models’ quality and performance. …”
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YOLOv8-POS: a lightweight model for coal-rock image recognition by Yanqin Zhao, Wenyu Wang

“…This reduces unnecessary computational overhead while preserving the integrity of critical feature information, thus significantly cutting down on the model’s parameters and computational demands. Additionally, an Overlapping Spatial Reduction Attention module is incorporated into the model’s architecture to optimize the fusion of spatial features, substantially improving the handling of complex scenarios. …”
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Development of a multi-level feature fusion model for basketball player trajectory tracking by Tao Wang

“…This study has the following two contributions. Firstly, a new model of athlete trajectory tracking is proposed, which improves the accuracy and efficiency of multi-target tracking by optimizing object detection algorithm and introducing hybrid branch network. …”
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The Use of BIM Models and Drone Flyover Data in Building Energy Efficiency Analysis by Agata Muchla, Małgorzata Kurcjusz, Maja Sutkowska, Raquel Burgos-Bayo, Eugeniusz Koda, Anna Stefańska

“…The findings highlight the potential for optimizing energy efficiency, improving facility management, and advancing low-emission building practices. …”
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Research on Financial Stock Market Prediction Based on the Hidden Quantum Markov Model by Xingyao Song, Wenyu Chen, Junyi Lu

“…Experimental results demonstrate that the proposed quantum model outperforms classical algorithmic models in handling higher complexity, achieving improved efficiency, reduced computation time, and superior predictive performance. …”
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IASB Framework: Construction of Data Asset Accounting System Based on PO-BP Model by Haixia Guo

“…The PO algorithm optimizes the weights and biases of the BP neural network, improving its global search and local development capabilities. …”
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Research on multimodal social media information popularity prediction based on large language model by WANG Jie, WANG Zitong, PENG Yan, HAO Bowen

“…Finally, an improved direct preference optimization (DPO) algorithm IDPOP was developed by constructing preference data and adding a parameter-tuned penalty to the DPO loss function, resolving instability and non-convergence in RLHF and incorrect optimization in standard DPO for social media popularity prediction. …”
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Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance by Firgiawan Faira, Dandy Pramana Hostiadi

“…The novelty of this research lies in the application of a data aggregation technique to address class imbalance, significantly improving machine learning model performance and optimizing training time. …”
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AgrUNet: A Multi-GPU UNet Based Model for Crops Classification by Andrea Miola, Enrico Calore, Sebastiano Fabio Schifano

“…In this study, we develop AgrUNet, a scalable, fast, and reliable UNet-based architecture DL model to perform crop classification on multispectral multitemporal satellite data, implemented and optimized to run on single and multi-GPU HPC systems. …”
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GA-Synthesized Training Framework for Adaptive Neuro-Fuzzy PID Control in High-Precision SPAD Thermal Management by Mingjun Kuang, Qingwen Hou, Jindong Wang, Jianping Guo, Zhengjun Wei

“…The controller maintains stability under structural perturbations and abrupt thermal disturbances without the need for offline retuning, owing to the real-time inference capabilities of the ANFIS model. By combining global evolutionary optimization with intelligent online adaptation, this approach improves both accuracy and generalization, offering a practical and scalable solution for SPAD thermal management in demanding environments such as quantum communication, sensing, and single-photon detection platforms.…”
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Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network by Xiaorong Li, Lijun Zhang, Dongchen Li, Dan Guo

“…The optimization of the model training process is finally completed, and the recommendation quality is improved. …”
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EUR Prediction for Shale Gas Wells Based on the ROA-CatBoost-AM Model by Weikang He, Xizhe Li, Yujin Wan, Honming Zhan, Nan Wan, Sijie He, Yaoqiang Lin, Longyi Wang, Wenxuan Yu, Liqing Chen

“…The hyperparameters of the model were optimized using the Rabbit Optimization Algorithm (ROA), and 10-fold cross-validation was employed to improve the stability and reliability of model evaluation, mitigating overfitting and bias. …”
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Advances in Miniaturized Computational Spectrometers by Qian Xue, Yang Yang, Wenkai Ma, Hanqiu Zhang, Daoli Zhang, Xinzheng Lan, Liang Gao, Jianbing Zhang, Jiang Tang

“…The reconstruction algorithms are classified into traditional and deep learning algorithms, and they are carefully analyzed based on the mathematical models required for spectral reconstruction. …”
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Empowering Fuel Cell Electric Vehicles Towards Sustainable Transportation: An Analytical Assessment, Emerging Energy Management, Key Issues, and Future Research Opportunities by Tuhibur Rahman, Md. Sazal Miah, Tahia F. Karim, Molla Shahadat Hossain Lipu, Abu M. Fuad, Zia Ul Islam, M. M. Naushad Ali, Mohammed Nazmus Shakib, Shafrida Sahrani, Mahidur R. Sarker

“…To address these challenges, smart energy management involving appropriate converters, controllers, intelligent algorithms, and optimizations is essential for enhancing the effectiveness of FCEVs towards sustainable transportation. …”
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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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Classification of edible vegetable oils based on three-dimensional fluorescence spectroscopy and ISSA-SVM by ZHANG Jing, QI Guohong, CHEN Jingzhao, CAO Xiaoli, LI Lili

“…ObjectiveTo improve the classification accuracy of edible vegetable oils, an identification model based on three-dimensional fluorescence spectroscopy and ISSA-SVM was established.MethodsCombining the feature information of three-dimensional fluorescence spectroscopy, an improved sparrow search algorithm was used to optimize the parameters of the SVM model, constructing an edible vegetable oil identification method that integrates the characteristics of three-dimensional fluorescence spectroscopy information and the ISSA-SVM model.ResultsCompared with the SVM model, GA-SVM model, PSO-SVM model, and SSA-SVM model, the classification accuracy of the ISSA-SVM model for edible vegetable oils reached 100%.ConclusionThe ISSA-SVM model has higher convergence efficiency, system stability, and the ability to avoid local optimal solutions, which can effectively cope with complex and variable sample classification tasks.…”
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Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs by Hatem Gasmi, Azher M. Abed, Ashit Kumar Dutta, Fahad M. Alhomayani, Ibrahim Mahariq, Fahad Alturise, Salem Alkhalaf, Tamim Alkhalifah, Yasser Elmasry, Baseem Khan

“…This study offers an in-depth thermodynamic analysis and optimization of an integrated renewable energy system that merges a double-flash geothermal system with a transcritical carbon dioxide Rankine cycle, utilizing machine learning algorithms. …”
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IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration by Sami Binyamin, Sami Ben Slama

“…The proposed approach can dynamically optimize household energy flows, deploying real-time data and adaptive algorithms to balance energy demand and supply. …”
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