A two‐stage transformer fault diagnosis method based multi‐filter interactive feature selection integrated adaptive sparrow algorithm optimised support vector machine by Hanyu Shi, Mingxia Chen

“…Finally, Experiments were conducted using real fault data, and the diagnostic performance of different feature inputs, optimisation algorithms and classifiers were compared. …”
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AI-based system for food and beverage selection towards precision nutrition in Indonesian restaurants by Kudang Boro Seminar, Evy Damayanthi, Karlisa Priandana, Harry Imantho, Bonang Waspadadi Ligar, Annisa Utami Seminar, Angga Dwi Krishnajaya, Muhamad Reza Aditya, Muhammad Ilham Hakim Suherman, Ismy Fana Fillah

“…In this study, a genetic algorithm (GA) is used to develop a system that can address this issue in the context of Indonesian restaurants. …”
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A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns by Irene Biliani, Ekaterini Skamnia, Polychronis Economou, Ierotheos Zacharias

“…Remote sensing data play a crucial role in capturing and evaluating eutrophication, providing a comprehensive view of spatial and temporal variations in water quality parameters. …”
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Coverage optimization of wireless sensor network utilizing an improved CS with multi-strategies by Sen-Yu Yang, Chang-Feng Chen, Kai-Qing Zhou, Yun Ou

“…For WSN coverage optimization, the ICS-MS algorithm outperforms comparative algorithms. At 200 iterations, it achieves an average coverage increase of 2.32-22.17% for 20-node deployments and 2.75-22.21% for 30-node deployments. …”
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A KNN-based model for non-invasive prediction of hemorrhagic shock severity in prehospital settings: integrating MAP, PBUCO2, PTCO2, and PPV by Peng Zhao, Wencai Pan, Xin Zou, Jiaqing Yang, Shihui Zhang, Yufei Liu, Yang Li

“…We developed a multi-parameter predictive model integrating mean arterial pressure (MAP), buccal mucosal CO₂ (PBUCO₂), transcutaneous oxygen (PTCO₂), and pulse pressure variation (PPV). using K-nearest neighbors (KNN) algorithm. Methods Forty-five Wistar rats were randomly divided into five groups (n = 9) with different blood loss amounts. …”
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The Application of Machine Learning Algorithms to Predict HIV Testing in Repeated Adult Population–Based Surveys in South Africa: Protocol for a Multiwave Cross-Sectional Analysis... by Musa Jaiteh, Edith Phalane, Yegnanew A Shiferaw, Refilwe Nancy Phaswana-Mafuya

“…Furthermore, this study will evaluate and compare the performance metrics of the 4 different ML algorithms, and the best model will be used to develop an HIV testing predictive model. …”
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Accuracy Evaluation of Multi-Source Precipitation Data in Mountain Flood Simulation in Guoning Village， Xiahe County by Wubin HUANG, Jing FU, Runxia GUO, Junxia ZHANG, Yu LEI

“…From 22:00 on September 6， 2023 to 04:00 （Beijing Time） on September 7， Xiahe County in Gansu Province experienced severe convective weather， with short-term heavy rainfall in some areas， causing flash floods in Guoning Village， Xiahe County， resulting in casualties.In this study， the characteristics of Radar Quantitative Precipitation Estimation （Radar-QPE）， FengYun 4B Quantitative Precipitation Estimation （FY4B-QPE）， and CMA Multi-source Precipitation Analysis （CMPA） precipitation products were contrastive analyzed based on meteorological station observations.These precipitation data were used to drive the hydrodynamic hydrological model and evaluate the effect of different precipitation data in the flash flood simulation.The results showed that： （1） Among the 12-hour cumulative precipitation amounts， CMPA demonstrated higher accuracy in terms of the position of large value areas and differences in local precipitation levels； Radar-QPE was closer to AWS （Automatic Weather Station） in terms of cumulative precipitation level but showed significant differences in spatial distribution； FY4B-QPE overestimated the cumulative precipitation level by 33.8%.（2） In terms of hourly distribution， CMPA was most similar to AWS in terms of temporal evolution， spatial distribution， and precipitation level； Radar-QPE's peak values were smaller， and the peak times were lagged， with negative deviations in precipitation being dominant； FY4B-QPE's peak values and peak times were consistent with reality， but there were deviations in the start and end times of precipitation， with positive deviations in precipitation being dominant.（3） In the hydrological simulation study， CMPA， Radar-QPE， and FY4B-QPE all overestimated water levels， but the timing of water level peaks was more consistent with AWS.CMPA performed best in terms of RMSE （Root Mean Square Error）， NSE （Nash Efficiency Coefficient）， and Bias （Relative Deviation）， followed by Radar-QPE， and FY4B-QPE performed relatively poorly.Although existing site-observed precipitation cannot fully meet the needs of research and early warning for small and medium scale mountain floods， the high precision of CMPA data could effectively supplement the deficiencies of traditional meteorological observation stations to some extent.Meanwhile， the algorithms and accuracy of Radar-QPE and FY4B-QPE needed to be further improved and enhanced.…”
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Inversion of SPAD Values of Pear Leaves at Different Growth Stages Based on Machine Learning and Sentinel-2 Remote Sensing Data by Ning Yan, Qu Xie, Yasen Qin, Qi Wang, Sumin Lv, Xuedong Zhang, Xu Li

“…Subsequently, four machine learning algorithms—K-Nearest Neighbors (KNN), Random Forest (RF), Support Vector Machine (SVM), and an Optimized Integrated Algorithm (OIA)—were employed to develop SPAD retrieval models, and the performance differences across various input combinations and models were systematically evaluated. …”
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Species-specific variation in predicted distribution and habitat suitability of phlebotomine sand flies in Italy under different climate change scenarios by Camila González, Johan Manuel Calderón, Ana María López, Ilaria Bernardini, Luigi Gradoni, Marco Pombi, Gioia Bongiorno, Simona Gabrielli

“…The predictions indicate suitable habitats for sand flies throughout Italy, and variations among the different scenarios evaluated. All species show potential for expansion, such as the main vector, P. perniciosus, which shows an increase in the percentage of suitable habitat over time. …”
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Synthetic Ensemble Forecasts: Operations‐Based Evaluation and Inter‐Model Comparison for Reservoir Systems Across California by Zachary P. Brodeur, William Taylor, Jonathan D. Herman, Scott Steinschneider

“…We address this research gap by first introducing a novel operations‐based validation framework, where reservoir storage and release simulations under a FIRO policy are compared when forced with a single ensemble hindcast and many different synthetic ensembles. We evaluate the suitability of synthetic forecasts based on formal probabilistic verification of the operational outcomes. …”
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Evaluating visitor perception and spatial preferences of various museums based on machine learning from 2016 to 2024. by Yuandi Jiang, Kalyna Pashkevych, Shibo Bi

“…TF-IDF and LDA algorithms identified key image perception themes. Visitor satisfaction was then evaluated with SnowNLP sentiment analysis to examine the dynamic correlation between the perception themes and satisfaction. …”
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Underwater Acoustic Communication Using Multi-Layer Vector Approximate Message Passing Evaluated on the Watermark Benchmark by Julian Winkler, Sabah Badri-Hoeher

“…The multi-layer vector approximate message passing algorithm is applied to the problem of channel estimation in underwater acoustic communication addressing the estimation of time-varying channel characteristics. …”
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Comparative Evaluation of Fractional-Order Models for Lithium-Ion Batteries Response to Novel Drive Cycle Dataset by Xinyuan Wei, Longxing Wu, Chunhui Liu, Zhiyuan Si, Xing Shu, Heng Li

“…However, the quantitative evaluations and adaptability of these models under different driving cycle datasets are still lacking and challenging. …”
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A new adaptive grey prediction model and its application by Jianming Jiang, Ming Zhang, Zhongyong Huang

“…The experimental results demonstrate that the proposed model outperforms the competing algorithms in all evaluation metrics, confirming its effectiveness.…”
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A CNN-Based Indoor Positioning Algorithm for Dark Environments: Integrating Local Binary Patterns and Fast Fourier Transform with the MC4L-IMU Device by Nan Yin, Yuxiang Sun, Jae-Soo Kim

“…In addition, all models show strong stability, and the prediction standard index (PSI) values are always below 0.02. To evaluate model robustness and MC4L-IMU work reliably under different conditions, the experiments were conducted in a controlled indoor environment with different obstacle materials and lighting conditions.…”
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Combining K-Means Clustering and Random Forest to Evaluate the Gas Content of Coalbed Bed Methane Reservoirs by Jie Yu, Linqi Zhu, Ruibao Qin, Zhansong Zhang, Li Li, Tao Huang

“…The results of this study show that the random forest method based on clustering can effectively distinguish the relationship between different logging responses and gas content. On this basis, the random forest algorithm modeling can effectively characterize the complex relationship between gas content and logging curve response. …”
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A new method of assessing microcirculation of the central retina in patients with different stages of diabetic macular edema in type 2 diabetes by S.A. Suk, S.Yu. Mogilevskyy, M.I. Kovtun, B.B. Zhupan

“…The ratio of the obtained indicators of the FAZ/CD of the superficial and deep capillary plexuses was evaluated, which corresponded to the deve­loped coefficient of microcirculation in the superficial and deep ca­pillary plexuses of the central retina at different stages of DME. …”
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Comprehensive MILP Formulation and Solution for Simultaneous Scheduling of Machines and AGVs in a Partitioned Flexible Manufacturing System by Cheng Zhuang, Jingbo Qu, Tianyu Wang, Liyong Lin, Youyi Bi, Mian Li

“…Results demonstrate that the proposed MILP formulation efficiently generates globally optimal solutions and consistently outperforms a greedy algorithm enhanced by A*-inspired heuristics. Although computationally intensive for large scenarios, the MILP’s optimal results serve as an exact benchmark for evaluating faster heuristic methods. …”
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Evaluating the utility of public-facing jail registers to inform public health practice, Washington state 2023 by Steven Erly, Richard J. Lechtenberg, Vasiliki Georgoulas-Sherry, Anna Berzkalns, Allison Moore, Julia C. Dombrowski, Jennifer E. Balkus

“…We applied a simple match algorithm to copies of these datasets that had been reduced to match the different combinations of identifier variables available in the public data (full names and ages, partial names, etc.) …”
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Paediatric pharmacovigilance: use of pharmacovigilance data mining algorithms for signal detection in a safety dataset of a paediatric clinical study conducted in seven African cou... by Dan K Kajungu, Annette Erhart, Ambrose Otau Talisuna, Quique Bassat, Corine Karema, Carolyn Nabasumba, Michael Nambozi, Halidou Tinto, Peter Kremsner, Martin Meremikwu, Umberto D'Alessandro, Niko Speybroeck

“…In this study we examine the use of data mining algorithms to identify signals from adverse events reported in a phase IIIb/IV clinical trial evaluating the efficacy and safety of several Artemisinin-based combination therapies (ACTs) for treatment of uncomplicated malaria in African children.…”
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