Quantification of MODIS Land Surface Temperature Downscaled by Machine Learning Algorithms by Qi Su, Xiangchen Meng, Lin Sun, Zhongqiang Guo

“…By establishing non-linear relationships between LST and predictive variables through eXtreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms, the proposed framework was rigorously validated using in situ measurements across China’s Heihe River Basin. …”
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TRENDS IN SPANISH LITERATURE. HOW NEW TECHNOLOGIES INFLUENCE THE PROCESS OF LITERARY CREATION by Alina-Viorela PRELIPCEAN

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A Review on Automated Detection and Identification Algorithms for Highway Pavement Distress by Zhenglong Lv, Zhexin Hao, Yuhan Zhu, Cong Lu

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Automated Input Variable Selection for Analog Methods Using Genetic Algorithms by P. Horton, O. Martius, S. L. Grimm

“…Previous work showed the potential of genetic algorithms (GAs) to optimize most of the AM parameters. …”
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Bandit Algorithms for Efficient Toxicity Detection in Competitive Online Video Games by Jacob Morrier, Rafal Kocielnik, R. Michael Alvarez

“…When no pre-existing predictive model of toxic behavior is available, one must be estimated in real-time. …”
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The Accuracy of the Uganda National Tuberculosis and Leprosy Program diagnostic algorithm and the World Health Organisation treatment decision algorithms for childhood tuberculosis... by Peter J Kitonsa, Bernard Kikaire, Peter Wambi, Annet Nalutaaya, Jascent Nakafeero, Gertrude Nanyonga, Emma Kiconco, Deus Atwiine, Robert Castro, Ernest A Oumo, Hellen T Aanyu, Mary N Mudiope, Ezekiel Mupere, Moorine P Sekadde, Swomitra Mohanty, Adithya Cattamanchi, Eric Wobudeya, Devan Jaganath

“…We applied the 2017 Uganda NTLP and 2022 WHO algorithms (A with chest x-ray [CXR], B without CXR) to make a decision to treat for TB or not, and calculated the sensitivity, specificity and predictive values in reference to Confirmed vs. …”
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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…Abstract Predicting agricultural commodity prices is inherently complex due to factors such as perishability, seasonality, and market volatility. …”
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Machine learning algorithms of riverbed change and environments of the Lower Apalachicola River by Ali R. Alruzuq, Joann Mossa

“…The study identifies potential drivers of riverbed changes using machine learning algorithms. The RF model has outperformed the XGBoost model with an R-square of 0.95 and 0.93 for the validation and testing sets, respectively, for RF, indicating high predictive accuracy while slightly less accurate with an R-square of 0.75 and 0.74 for the validation and testing sets. …”
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Analysis of Algorithms for AI Virtual Player in the Production Management Training Platform by Gąbka Joanna, Przybyś Krzysztof

“…The article presents research focused on design, testing and evaluation of the Artificial Intelligence (AI) algorithms dedicated for Virtual Player (VP/bot) embedded in the Production Management Training Platform (TP). …”
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Random Oversampling-Based Diabetes Classification via Machine Learning Algorithms by G. R. Ashisha, X. Anitha Mary, E. Grace Mary Kanaga, J. Andrew, R. Jennifer Eunice

“…The proposed approach considers ML algorithms such as random forest, gradient boosting models, light gradient boosting classifiers, and decision trees, as they are widely used classification algorithms for diabetes prediction. …”
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Compression Index Regression of Fine-Grained Soils with Machine Learning Algorithms by Mintae Kim, Muharrem A. Senturk, Liang Li

“…This study employs machine learning algorithms—the random forest regressor (RFR), gradient boosting regressor (GBR), and AdaBoost regressor (ABR)—to predict the <i>C_c</i> values based on a dataset comprising 915 samples. …”
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Research on fusion prediction model of wind speed, gas and dust concentration under wind flow control in fully-mechanized heading face by Xiaoyan GONG, Hao ZOU, Zhuangzhuang LIU, Long CHEN, Haoran FU, Yuheng SUN, Hao LI, Xinyu WANG, Huming NIU

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The impact of algorithm awareness training on competent interaction with intelligent voice assistants by André Markus, Maximilian Baumann, Jan Pfister, Andreas Hotho, Astrid Carolus, Carolin Wienrich

“…The modules offer a new approach to promoting the competent use of IVAs in society and provide a starting point for further research and educational institutions to increase algorithm awareness for IVAs and other AI-based systems.…”
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Prediction and Impact Analysis of Soil Nitrogen and Salinity Under Reclaimed Water Irrigation: A Case Study by Zeyu Liu, Kai Fang, Xiaoqin Sun, Yandong Wang, Zhuo Tian, Jing Liu, Liying Bai, Qilin He

“…The models achieved high predictive accuracy, with NSE values of 0.918, 0.946, 0.936, 0.967, and 0.887 for NO₃⁻-N, NH₄⁺-N, TN, EC, and Cl⁻, respectively, demonstrating their robustness. …”
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Neural Network VS Genetic and Particle Swarm Optimization Algorithms in Bankruptcy by Alireza Azarberahman

“…The evidence reveals the effectiveness of the metaheuristic algorithms compared to linear ones in predicting bankruptcy. …”
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Strong Convergence Algorithms for Hierarchical Fixed Points Problems and Variational Inequalities by Gendai Gu, Shenghua Wang, Yeol Je Cho

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Proactive spectrum handoff in distributed cognitive radio networks by Hua JIANG, Li-chuan MA, Ding-yu YAN, Nan PAN

Subjects: “…distributed cognitive radio network;spectrum handoff;spectrum prediction;task allocation algorithm of ant colony…”
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Novel load balancing mechanism for cloud networks using dilated and attention-based federated learning with Coati Optimization by Atul B. Kathole, Viomesh Kumar Singh, Ankur Goyal, Shiv Kant, Amit Sadanand Savyanavar, Swapnaja Amol Ubale, Prince Jain, Mohammad Tariqul Islam

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Development and Validation of an Interpretable Machine Learning Model for Prediction of the Risk of Clinically Ineffective Reperfusion in Patients Following Thrombectomy for Ischem... by Hu X, Qi D, Li S, Ye S, Chen Y, Cao W, Du M, Zheng T, Li P, Fang Y

“…Our CIR risk prediction platform enables early intervention and personalized treatment. …”
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Development and validation of multimodal deep learning algorithms for detecting pulmonary hypertension by Wei Zhao, Zhihua Huang, Xiaolin Diao, Zhan Yang, Zhihui Zhao, Yun Xia, Qing Zhao, Zhaohong Sun, Qunying Xi, Yanni Huo, Ou Xu, Jiahui Geng, Xin Li, Anqi Duan, Sicheng Zhang, Luyang Gao, Yijia Wang, Sicong Li, Qin Luo, Zhihong Liu

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