Machine learning approach for revealing the nickel grade and recovery optimization in reduction process of laterite ores by Vuri Ayu Setyowati, Fakhreza Abdul

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RAPO: An Automated Performance Optimization Tool for Redis Clusters in Distributed Storage Metadata Management by Yunkai Zhu, Tian Xia, Te Zhu, Zhoujie Zhao, Kexin Li, Xingbo Hu

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Modeling the Relationship between Financial Stability and Banking Risks: Artificial Intelligence Approach by Hakeem Faraj Gumar, Parviz Piri, Mehdi Heydari

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Leveraging mixed-effects regression trees for the analysis of high-dimensional longitudinal data to identify the low and high-risk subgroups: simulation study with application to g... by Mina Jahangiri, Anoshirvan Kazemnejad, Keith S. Goldfeld, Maryam S. Daneshpour, Mehdi Momen, Shayan Mostafaei, Davood Khalili, Mahdi Akbarzadeh

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Adaptive Inertia Control for Virtual Synchronous Generators to Enhance Response Performance of a Wind-Solar-Storage Combined Power Generation System by Haibo Zhang, Haoyu Zhu, Zhe Zhang, Xianfu Gong

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Comparative Analysis of Diabetes Prediction Models Using the Pima Indian Diabetes Database by Zhao Yize

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Combined L-Band Polarimetric SAR and GPR Data to Develop Models for Leak Detection in the Water Pipeline Networks by Yuyao Zhang, Hongliang Guan, Fuzhou Duan

“…The model features are selected with the Boruta wrapper algorithm based on the SAOCOM-1A images after pre-processing, and the SSRDC values at sampling locations within the research area are calculated with the reflected wave method based on the GPR data. …”
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Reactive Power Optimization Control for Renewable Energy in Distribution Networks Considering Active Power Uncertainties by Jingzhong ZHANG, Fei MENG, Yang SUN, Huixia YU

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Factors influencing the spatial distribution of police stops and their efficacy in crime prevention and control by Zhuoying Fan, Xuewei Zhang, Guangwen Song, Chunxia Zhang

“…Second, by clustering based on different associated factors of police stops, existing police stops can be classified into five categories according to their purposes: (i) composite stops positively associated with “Alarm, Visiting Population, Criminals” (AVC-CPS); (ii) composite stops positively associated with “Alarm, Visiting Population, Bus Station” (AVB-CPS); (iii) random stops with no significant positive association (NA-RPS); (iv) single police stops positively associated with “Alarm” (A-SPS); and (v) single stops positively associated with “Visiting Population” (V-SPS). …”
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Forecasting water quality indices using generalized ridge model, regularized weighted kernel ridge model, and optimized multivariate variational mode decomposition by Marjan Kordani, Mohsen Bagheritabar, Iman Ahmadianfar, Arvin Samadi-Koucheksaraee

“…The proposed framework includes a new hybrid machine learning (ML) model based on generalized ridge regression and kernel ridge regression with a regularized locally weighted (GRKR) method. This research developed an optimized multivariate variational mode decomposition (OMVMD) technique, optimized by the Runge-Kutta algorithm (RUN), to decompose the input variables. …”
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An Evaluation of the Sensitivity of a Source Term Estimation Methodology of Sensor Configuration in an Urban-like Environment by Panagiotis Gkirmpas, Fotios Barmpas, George Tsegas, George Efthimiou, Paul Tremper, Till Riedel, Christos Vlachokostas, Nicolas Moussiopoulos

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Leveraging Finite-Precision Errors in Chaotic Systems for Enhanced Image Encryption by B. M. El-Den, Saad Aldosary, Haitham Khaled, Tarek M. Hassan, Walid Raslan

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Wetland Gain and Loss in the Mississippi River Bird‐Foot Delta by Jiangjie Yang, Zhijun Dai, Xuefei Mei, Yaying Lou, Sergio Fagherazzi

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Optimizing ensemble learning for satellite-based multi-hazard monitoring and susceptibility assessment of landslides, land subsidence, floods, and wildfires by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Farman Ali, Biswajeet Pradhan, Soo-Mi Choi

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Computer analysis shows differences between mitochondrial miRNAs and other miRNAs by P. S. Vorozheykin, I. I. Titov

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Multi-Temporal Remote Sensing Satellite Data Analysis for the 2023 Devastating Flood in Derna, Northern Libya by Roman Shults, Ashraf Farahat, Muhammad Usman, Md Masudur Rahman

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Energy-Aware Task Allocation for Multi-Cloud Networks by Sambit Kumar Mishra, Sonali Mishra, Ahmed Alsayat, N Z Jhanjhi, Mamoona Humayun, Kshira Sagar Sahoo, Ashish Kr. Luhach

“…However, the average energy consumption improved through <italic>ETAMCN</italic> is approximately 14&#x0025;, 6.3&#x0025;, and 2.8&#x0025; in opposed to the random allocation algorithm, Cloud Z-Score Normalization (<italic>CZSN</italic>) algorithm, and multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS), respectively. …”
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Spatial and temporal distribution patterns and factors influencing hepatitis B in China: a geo-epidemiological study by Kang Fang, Na Cheng, Chuang Nie, Wentao Song, Yunkang Zhao, Jie Pan, Qi Yin, Jiwei Zheng, Qinglin Chen, Tianxin Xiang

“…Spatial autocorrelation analysis and spatiotemporal scanning were used to analyze the spatiotemporal distribution characteristics. The random forest algorithm was used to screen the potential influencing factors. …”
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A Multi-Source Data-Driven Analysis of Building Functional Classification and Its Relationship with Population Distribution by Dongfeng Ren, Xin Qiu, Zehua An

“…The proposed model innovatively incorporates texture, geometric, and temporal features of building images, as well as socio-economic characteristics extracted using the distance decay algorithm. The results yield the following conclusions: (1) The proposed method achieves an overall classification accuracy of 0.77, which is 0.12 higher than that of the random forest-based approach. (2) The introduction of time features and the distance decay method further improved the model performance, increasing the accuracy by 0.04 and 0.03, respectively. (3) The correlation between the building functions and population distribution varies significantly across different scales. …”
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A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization by Songping He, Xiangxi Li, Fangyu Peng, Jiazhi Liao, Xia Lu, Hui Guo, Xin Tan, Yanyan Chen

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