A machine-learning reconstruction of sea surface <i>p</i>CO₂ in the North American Atlantic Coastal Ocean Margin from 1993 to 2021 by Z. Wu, Z. Wu, W. Lu, A. Roobaert, L. Song, X.-H. Yan, W.-J. Cai

“…Compared with all the observation samples from SOCAT, the <span class="inline-formula"><i>p</i></span>CO<span class="inline-formula">₂</span> product yields a determination coefficient of 0.92, a root-mean-square error of 12.70 <span class="inline-formula">µ</span>atm, and an accumulative uncertainty of 23.25 <span class="inline-formula">µ</span>atm. …”
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Stacked hybrid model for load forecasting: integrating transformers, ANN, and fuzzy logic by Elakkiya E, Antony Raj S, Arunkumar Balakrishnan, Bhavyasri Sanisetty, Revanth Balaji Bandaru

“…Furthermore, these techniques are prone to errors in the presence of noisy data and have scalability issues when used on big, high-dimensional datasets. …”
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Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat by Zhikai Cheng, Xiaobo Gu, Yadan Du, Zhihui Zhou, Wenlong Li, Xiaobo Zheng, Wenjing Cai, Tian Chang

“…The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75, a root mean square error of 8.40, and a mean absolute value error of 6.53. …”
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Evaluating Feature Impact Prior to Phylogenetic Analysis Using Machine Learning Techniques by Osama A. Salman, Gábor Hosszú

“…The results emphasize that feature selection by DNNs, their essential role, outperforms other models in terms of area under the curve (AUC) and equal error rate (EER) across various datasets and fold sizes. …”
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Application of Hybrid ARIMA and Artificial Neural Network Modelling for Electromagnetic Propagation: An Alternative to the Least Squares Method and ITU Recommendation P.1546-5 for... by Ramz L. Fraiha Lopes, Simone G. C. Fraiha, Herminio S. Gomes, Vinicius D. Lima, Gervasio P. S. Cavalcante

“…The results indicate the model is, at least, 44% more precise than every ITU estimate and, in some situations, is at least 11% better than an LS estimate, depending on the respective values of the relative error (RE).…”
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Mapping football tactical behavior and collective dynamics with artificial intelligence: a systematic review by José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, Eduardo Maio, Eduardo Maio, Eduardo Maio, Pedro Afonso, Pedro Afonso, Samuel Encarnação, Samuel Encarnação, Samuel Encarnação, Guilherme F. Machado, Guilherme F. Machado, Ryland Morgans, Tiago M. Barbosa, Tiago M. Barbosa, António M. Monteiro, António M. Monteiro, Pedro Forte, Pedro Forte, Pedro Forte, Ricardo Ferraz, Ricardo Ferraz, Luís Branquinho, Luís Branquinho, Luís Branquinho, Luís Branquinho

“…Concretely, the tactical behavior was expressed by spatiotemporal tracking data using convolutional neural networks, recurrent neural networks, variational recurrent neural networks, and variational autoencoders, Delaunay method, player rank, hierarchical clustering, logistic regression, XGBoost, random forest classifier, repeated incremental pruning produce error reduction, principal component analysis, and T-distributed stochastic neighbor embedding. …”
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A Bio-Inspired Data-Driven Locomotion Optimization Framework for Adaptive Soft Inchworm Robots by Mahtab Behzadfar, Arsalan Karimpourfard, Yue Feng

“…The neural network achieves superior velocity prediction performance, with a coefficient of determination (R²) of 0.9362 and a root mean squared error (RMSE) of 0.3898, surpassing previously reported models, including linear regression, LASSO, decision trees, and random forests. …”
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Predictive identification of oral cancer using AI and machine learning by Saraswati Patel, Dheeraj Kumar

“…Using convolutional neural networks (CNNs), support vector machines (SVMs), and random forests, we compared the effectiveness of these techniques in improving diagnostic accuracy and mean squared error (MSE). …”
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Application of Sentinel-2A Images for Land Cover Classification Using NDVI in Jember Regency by Rufiani Nadzirah, Mochammad Kevin Rizqon, Indarto Indarto

“…The classification in this study encompassed five classes: water bodies, settlements, dry fields, irrigated paddy fields, and forests. Error analysis was conducted using a confusion matrix with the Overall and Kappa algorithms. …”
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Machine Learning Algorithms in Predicting Prices in Volatile Cryptocurrency Markets by Miguel Jiménez-Carrión, Gustavo A. Flores-Fernandez

“…In comparison, alternative models such as Support Vector Machines (SVM), Extreme Gradient Boosting (XGBoost), and Random Forests exhibited significantly higher error rates; for instance, XGBoost recorded an RMSE of $17,849.66 and a MAPE of 27.74%. …”
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Creation of ICESat-2 Footprint Level Global Geodetic Control Points Using Crossover Analysis by Amy Neuenschwander, Eric Guenther, Lori Magruder, Jonathan Sipps

“…Comparisons of high-quality ICESat-2 crossovers against airborne lidar data serving as reference were found to have a mean error of less than 15 cm for each AOR examined and RMSE of less than 35 cm for two of the three sites; a RMSE value of 85 cm was obtained for the third site. …”
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TSSA-NBR: A Burned Area Extraction Method Based on Time-Series Spectral Angle with Full Spectral Shape by Dongyi Liu, Yonghua Qu, Xuewen Yang, Qi Zhao

“…TSSA-NBR achieved a Dice Coefficient (DC) of 87.81%, with commission (CE) and omission errors (OE) of 8.52% and 15.58%, respectively, demonstrating robust performance across all regions. …”
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Data-Driven Computational Methods in Fuel Combustion: A Review of Applications by Jacek Lukasz Wilk-Jakubowski, Lukasz Pawlik, Damian Frej, Grzegorz Wilk-Jakubowski

“…ANN-based models achieved high accuracy in predicting NO_x emissions and flame speed, with some studies reporting mean absolute errors below 5%. GA methods demonstrated effectiveness in fuel blend optimization and geometry design, achieving emission reductions of up to 30% in experimental setups. …”
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Productivity and socioeconomic sustainability of Bubalus bubalis in the western lowlands of Venezuela by Carlos Alberto Calles Navas, Verena Torres Cardenas

“…In contrast, buffalo farming requires forests. However, to convince farmers to apply this type of livestock; it was necessary to demonstrate its greater profitability. …”
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An Automated Method for Detection and Enumeration of Olive Trees Through Remote Sensing by Muhammad Waleed, Tai-Won Um, Aftab Khan, Zubair Ahmad

“…Country olive forests are one of the major contributors with economic aspects. …”
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Global 30-m annual median vegetation height maps (2000–2022) based on ICESat-2 data and Machine Learning by Maria O. Hunter, Leandro Parente, Yu-feng Ho, Carmelo Bonannella, Laerte Guimarães Ferreira, Douglas Morton, Davide Consoli, Lindsey Sloat

“…Our model achieves a root mean square error (RMSE) of 2.35 m, R2 values of 0.515 and a D2 regression score of 0.62 estimated on the testing set. …”
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A Comparative Analysis of Price Forecasting Methods for Maximizing Battery Storage Profits by Alessandro Fiori Maccioni, Simone Sbaraglia, Rahim Mahmoudvand, Stefano Zedda

“…Univariate SSA clearly outperformed all alternatives, achieving on average 98% of the theoretical maximum profit while maintaining the lowest forecast error. Among the other models, simpler approaches performed surprisingly well: they achieved comparable, if not superior, profit performance to more complex, hour-specific, or computationally intensive configurations. …”
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Mixed effect gradient boosting for high-dimensional longitudinal data by Oyebayo Ridwan Olaniran, Saidat Fehintola Olaniran, Jeza Allohibi, Abdulmajeed Atiah Alharbi, Nada MohammedSaeed Alharbi

“…In comprehensive simulations spanning linear and nonlinear data-generating processes, MEGB achieved 35-76% lower mean squared error (MSE) compared to state-of-the-art alternatives like Mixed-Effect Random Forests (MERF) and REEMForest, while maintaining 55-70% true positive rates for variable selection in ultra-high-dimensional regimes $$(p=2000)$$ ( p = 2000 ) . …”
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Suitability of multifunction mobile devices for registration of accounting data of game animals by V. M. Glushkov, Yu. V. Krotov

“…Connection speed, positioning accuracy and stability of the connection with the satellites in any natural landscapes, including forests with high crown closure were determined by the method of comparing the performance of the navigator Garmin GpsMap 62s and GPS-module of smartphone LG. …”
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Hybrid ANFIS systems: Evaluation of bearing capacity of driven piles by Yan Peng, Haiquan Gao

“…Comparing the outcomes of the single and hybrid models, the highest performance belonged to ARO-ANFIS, by gaining the largest values of correlation metrics and the lowest values of error-based metrics. After examining the dependability and considering the justifications, the ANFIS paired with ARO outperformed the COA-ANFIS and GWOANFIS in the Qt of driven piles forecasting model, this is the suggested system.…”
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