Prediction of Coalbed Methane Production Using a Modified Machine Learning Methodology by Hongyang Zhang, Kewen Li, Shuaihang Shi, Jifu He

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Determinants of Financial Stability in Banks: The Impact of Key Regulatory Financial Indicators by Muslum Mursalov, Olga Niemi, Svitlana Kolomiiets, Darya Trofimenko

“…The methodological approach involved descriptive statistical analysis, normality testing, Box–Cox transformations, and multiple regression modelling using annual data from 2018 to 2024. …”
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Modeling the Higher Heating Value of Spanish Biomass via Neural Networks and Analytical Equations by Anbarasan Jayapal, Fernando Ordonez Morales, Muhammad Ishtiaq, Se Yun Kim, Nagireddy Gari Subba Reddy

“…Importantly, in direct comparisons it significantly outperformed 54 published analytical HHV correlations—the ANN achieved substantially higher R² and lower prediction error than any fixed-form formula in the literature. …”
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An Algorithm for Restoring a Function from Different Functionals for Predicting Rare Events in the Economy by Yu. A. Korablev

“…Moreover, all observations can occur with an error. Therefore, the author uses a method of recovering a function from different functionals observed with an error. …”
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Faults Detection and Diagnosis of a Large-Scale PV System by Analyzing Power Losses and Electric Indicators Computed Using Random Forest and KNN-Based Prediction Models by Yasmine Gaaloul, Olfa Bel Hadj Brahim Kechiche, Houcine Oudira, Aissa Chouder, Mahmoud Hamouda, Santiago Silvestre, Sofiane Kichou

“…Faults such as string disconnections, module short-circuits, and shading effects have been identified using two key indicators: current error (Ec) and voltage error (Ev). By focusing on power losses as a fault indicator, this method provides high-accuracy fault detection without requiring extensive labeled data, a significant advantage for large-scale PV systems where data acquisition can be challenging. …”
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Using multisource satellite products to estimate forest aboveground biomass in Oita prefecture: a novel approach with improved accuracy and computational efficiency by Hantao Li, Tomomichi Kato, Masato Hayashi, Jianhong Liu

“…Our results highlighted that the model using PCA and derivative features had the best performance [R2 = 0.69, root mean square error (RMSE) = 33.59 Mg/ha, mean absolute error = 25.01 Mg/ha, relative RMSE = 0.27]. …”
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Prediction of Rail Wear Under Different Railway Track Geometries Using Artificial Neural Networks by Hong Zhang, Weichen Shuai, Linya Liu, Pengfei Zhang, Kejun Zhang, Hongsong Lin, Yuke Zhang, Wei Li

“…It is hard to acquire rail wear data for different alignments with varying geometric parameters during the alignment design phase. …”
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Interpretable Deep Learning Models for Arrhythmia Classification Based on ECG Signals Using PTB-X Dataset by Ahmed E. Mansour Atwa, El-Sayed Atlam, Ali Ahmed, Mohamed Ahmed Atwa, Elsaid Md. Abdelrahim, Ali I. Siam

“…Manual ECG interpretation is labor-intensive and susceptible to errors, highlighting the demand for automated, scalable approaches. …”
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Use of New Methods to Determine the Inputs Effective in Estimating Soil Temperature by Babak Mohammadi

“…In this research, an estimate of the depth of 10 cm in the soil of the Synoptic Station of Tabriz in East Azerbaijan province was carried out using artificial neural network (ANN) and backward vector machine (SVM). Two main component analysis (PCA) and gamma (GT) tests were used for pre-processing data and input data. …”
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Design and Numerical Simulation of the Performance of Acoustic Plenum Chamber of a Marine Gas Turbine Air Supply System by Mehrdad RASOULIMOGHADAM, Saeid KHERADMAND

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Secrecy Performance Analysis of Mixed <italic>&#x03B1;</italic> &#x2212; <italic>&#x03BC;</italic> and Exponentiated Weibull RF-FSO Cooperative Relaying System by Nazmul Hassan Juel, A. S. M. Badrudduza, S. M. Riazul Islam, Sheikh Habibul Islam, Milton Kumar Kundu, Imran Shafique Ansari, Md. Munjure Mowla, Kyung-Sup Kwak

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Long Run Relationship Between Exports, Imports and its Determinants of Medical Instruments: Case of Pakistan by Fazal-ur-Rehman

“…After the review of literature, this study aims to check the existence of a long-run relationship between export of medical instruments and import of medical instruments, export promotion program and exchange rate index. The empirical analysis used the monthly time series data for June 2003 to December 2017 released by State Bank of Pakistan. …”
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Temperature Field Prediction of Glulam Timber Connections Under Fire Hazard: A DeepONet-Based Approach by Jing Luo, Guangxin Tian, Chen Xu, Shijie Zhang, Zhen Liu

“…The extracted temperature field data was used to train a DeepONet neural network, which achieved accurate temperature predictions (with a L2 relative error of 1.5689% and an R² score of 0.9991) while operating faster than conventional finite element analysis. …”
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A Novel Method for Aging Life Evaluation of O-Rings Based on the Sealing Performance Degradation Model and the Artificial Neural Network Model by Xiaojia Wang, Yu Huang, Jianning Zhang, Zihui Wang, Weiping Hu, Chao Song

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Emerging strontium isoscapes of Anatolia (Türkiye): new datasets and perspectives in bioavailable 87Sr/86Sr baseline studies by G. Bike Yazıcıoğlu, David C. Meiggs, Maxwell Davis, Suzanne E. Pilaar Birch, Suzanne E. Pilaar Birch

“…We combine all published baseline 87Sr/86Sr data from Türkiye with our unpublished 87Sr/86Sr data from proxy samples (plants and snail shells) from central Anatolia, and by incorporating this data (n = 688) into the global database (where data from Türkiye is currently lacking), we create a modeled 87Sr/86Sr isoscape of Türkiye utilizing the R-script and we calculate the predicted standard error for this isoscape.Results and discussionThis study demonstrates how additional empirical data serves to improve the Türkiye section of the global model using kriging and random forest regression (RFR) techniques and it discusses how the uneven distribution of data impacts the resultant isoscape map. …”
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Trump’s 2016 Presidential Campaign and Adorno’s Psychological Technique: Content Analyses of Authoritarian Populism by Myra B Haverda, Jeffrey A Halley

“…Using Adorno’s understudied textual analysis of the radio addresses of Martin Luther Thomas and data from Trump’s 2016 US presidential campaign, we find that Trump’s own discourse can be condensed into three of Adorno’s rhetorical devices: (1) the lone wolf device or anti-statism/pseudo-conservatism, reflecting his criticism of “special interests” and his appraisal of business and (self-)finance; (2) the movement device, which amounted to glorification of action; and (3) the exactitude of error device which amounted to xenophobic, ethnonationalist hyperbole. …”
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Comparison of Item Difficulty Analyses of Exams Used in Teaching Turkish as a Foreign Language with Instructors’ Perceptions of Item Difficulty by Seçil Alaca, Funda Keskin

“…Various analytical methods were employed to examine and interpret the obtained data. Item analysis results of examined tests were compared with instructors' perceptions of difficulty using fit analysis. …”
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Research on Medium and Long-Term Runoff Forecast of Xijiang River in Dry Season Based on Statistical Model by LAN Yuxi, ZHANG Yin, NONG Zhenchang, WEI Yongjiang

“…Accurate medium and long-term runoff forecast is of great guiding significance to the development and utilization of water resources,allocation optimization,and water dispatch.Based on the three statistical models of mean generating function,periodic analysis,and multiple stepwise regression,this paper studied the medium and long-term runoff forecast of the Longtan Reservoir in the upper reaches of the Xijiang River and the Wuzhou hydrological station in the lower reaches from October to March of the following year and during the entire dry season (six months,from October to March of the following year).The results show that the three models all present positive forecast results.In the calibration and verification periods,the average pass rate exceeds 75%,and the mean absolute percentage error is basically within 30%.The forecast accuracy of the mean generating function and the multiple stepwise regression is significantly higher than that of the periodic analysis,with smaller forecast errors in larger values.Multiple stepwise regression is more stable than the other two models.Furthermore,affected by the consistency of data,the forecast accuracy of the Longtan Reservoir is significantly higher than that of the Wuzhou hydrological station.On the whole,multiple stepwise regression has the optimal forecast effect in the Xijiang River Basin.In addition,it can maintain high forecast accuracy at all levels and stages and provide a valuable reference for water dispatch decisions in the basin.In the future,multi-model fusion can be used to further improve the forecast effect.…”
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Copula-Based Bivariate Modified Fréchet–Exponential Distributions: Construction, Properties, and Applications by Hanan Haj Ahmad, Dina A. Ramadan

“…The classical exponential model, despite its flexibility, fails to describe data with non-constant failure or between-event dependency. …”
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Predicting mortality risk in Alzheimer’s disease using machine learning based on lifestyle and physical activity by Ruihong Tang, Liang Tan, Xia Chen, Zhengwu Shan, Zhao Zhang, Panpan Cheng

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