Data-driven intelligent productivity prediction model for horizontal fracture stimulation by Qian Li, Yiyong Sui, Mengying Luo, Bin Guan, Lu Liu, Yuan Zhao

“…Second, relevant characteristic parameters were chosen from geological conditions, production characteristics, and fracturing techniques to perform clustering analysis on fracturing intervals in the data sample. …”
Get full text

A new, fast method to search for morphological convergence with shape data. by Silvia Castiglione, Carmela Serio, Davide Tamagnini, Marina Melchionna, Alessandro Mondanaro, Mirko Di Febbraro, Antonio Profico, Paolo Piras, Filippo Barattolo, Pasquale Raia

“…The search.conv method was found to be powerful, correctly identifying simulated cases of convergent morphological evolution in 95% of the cases. Type I error rate is as low as 4-6%. We found search.conv is some three orders of magnitude faster than a competing method for testing convergence.…”
Get full text

Data-Driven Carbon Emission Dynamics Under Ship In-Port Congestion by Weiyu Liu, Bowei Xu, Junjun Li

Get full text

The Future of Vineyard Irrigation: AI-Driven Insights from IoT Data by Simona Stojanova, Mojca Volk, Gregor Balkovec, Andrej Kos, Emilija Stojmenova Duh

“…The low value of the statistical analysis (<i>p</i>-value = 0.0009) of a paired <i>t</i>-test confirmed that the improvement is significant. …”
Get full text

Impacts of Missing Data Imputation on Resilience Evaluation for Water Distribution System by Amrit Babu Ghimire, Binod Ale Magar, Utsav Parajuli, Sangmin Shin

“…Then, resilience values were evaluated and compared using unimputed and imputed datasets. An analysis of performance indicators based on NRMSE, NMAE, NR-Square, and N-PBIAS revealed that higher missing-data percentages led to increased deviation between the true and imputed datasets. …”
Get full text

Service-Life Study of Polycarbonate Outdoors Using Python with Incomplete Data by Jiangfeng An, Duncheng Peng, Xuejie Zhou, Jun Wu, Penghua Zheng

“…The results indicated that (1) the degradation of PC tensile properties is mainly affected by the experimental period (76.37%), whilst the effect of the environmental or pollutant factors on the degradation is less pronounced (23.63%); (2) the classification accuracy of the trained model on the training set is 91% (91/100), and on the testing set is 72.13% (44/61); and lastly, (3) it is inferred from the error analysis of the classification results that the performance change of polycarbonate in Qionghai and Wuhan is characterized by an initial reduction followed by a slight improvement. …”
Get full text

Filtering and Overlapping Data for Accuracy Enhancement of Doppler-Based Location Method by Rafał Szczepanik, Jan M. Kelner

“…Comparative analysis with direct position determination techniques additionally showed high effectiveness of the SDF method, especially using data filtration and overlapping. …”
Get full text

Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes by T. V. Zolotova, D. A. Volkova

“…The purpose of the study is to carry out a comparative analysis of various methods for correcting atypical values of statistical data on the stock market and to develop recommendations for their use.Materials and methods. …”
Get full text

Optimizing The Financial Domain With Robotic Process Automation: Invoice Data Extraction by Andre Suryaningprang, Yoyo Sudaryo, Riyandi Nur Sumawidjaja, Andhika Mochamad Siddiq, Dedi Supiyadi

“…This study, conducted on an Indonesian trading organization, reveals how RPA may be used to streamline financial workflows by automating repetitive, time-consuming procedures, minimizing human error, and enhancing data management processes. …”
Get full text

Big Data-Driven Deep Learning Ensembler for DDoS Attack Detection by Abdulrahman A. Alshdadi, Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, Faisal S. Alsubaei

“…EffiGRU-GhostNet integrates Gated Recurrent Units (GRU) with the GhostNet architecture, optimized through Principal Component Analysis with Locality Preserving Projections (PCA-LLP) to handle large-scale data effectively. …”
Get full text

Harnessing Novel Data‐Driven Techniques for Precise Rainfall–Runoff Modeling by Saad Sh. Sammen, Reza Mohammadpour, Karam AlSafadi, Ali Mokhtar, Shamsuddin Shahid

“…The root mean squared error (RMSE) was recorded as 56.7 and 69.7 m3/s for the GMDH and ELM models, respectively. …”
Get full text

Projection and assessment of future droughts in Iowa: developing a machine learning model and an interactive application by Ingrid Cintura, Antonio Arenas

Get full text

A secure and imperceptible communication system for sharing co-ordinate data by Ranjeet Bidwe, Sahil Kale, Gautam Khaire, Jay Patankar, Deepak Mane, Suraj Sawant

“…The proposed model achieved a peak PSNR of 94.76 dB and an average PSNR exceeding 82 dB across all image types, ensuring imperceptibility well above the 36 dB visibility threshold. The mean square error (MSE) was consistently below 0.001, and histogram analysis confirmed visual consistency between cover and stego images. …”
Get full text

Sentinel-2 Satellite-Derived Bathymetry with Data-Efficient Domain Adaptation by Christos G. E. Anagnostopoulos, Vassilios Papaioannou, Konstantinos Vlachos, Anastasia Moumtzidou, Ilias Gialampoukidis, Stefanos Vrochidis, Ioannis Kompatsiaris

“…In addition, the domain adaptation approach using 15 samples shows comparable performance to the site-specific model trained on all available data in Cyprus. Depth-stratified error analysis and paired statistical tests confirm that around 15 samples represent a practical lower bound for stable SDB, according to the MagicBathyNet benchmark. …”
Get full text

Innovative Modeling of IMU Arrays Under the Generic Multi-Sensor Integration Strategy by Benjamin Brunson, Jianguo Wang, Wenbo Ma

“…This method characterizes sensor errors (biases/scale factor errors) for each IMU in an IMU array, leveraging the novel Generic Multisensor Integration Strategy (GMIS) and the framework for comprehensive error analysis in Discrete Kalman filtering developed through the authors’ previous research. …”
Get full text

Enhancing the Prediction of Dam Deformations: A Novel Data-Driven Approach by Jonas Ziemer, Gideon Stein, Carolin Wicker, Jannik Jänichen, Daniel Klöpper, Katja Last, Joachim Denzler, Christiane Schmullius, Maha Shadaydeh, Clémence Dubois

“…The prediction performance of the pendulum data was improved by utilizing data-driven algorithms, reducing the mean absolute error from 0.51 mm in the baseline model (<i>R</i>² = 0.92) to as low as 0.05 mm using the full model search space (<i>R</i>² = 0.99). …”
Get full text

Multiscale Performance of Global Blended Satellite Precipitation Products Over Taiwan by Liping Wang, Haonan Chen, Zhe Li

Get full text

A Comprehensive Review: Molecular and Genealogical Methods for Preserving the Genetic Diversity of Pigs by Vladimir Margeta, Dubravko Škorput, Ivona Djurkin Kušec, Zlata Kralik, Goran Kušec, Kristina Gvozdanović

“…To reduce possible errors, it is necessary to combine genealogical data with molecular data. …”
Get full text

Damage Detection of Bridges Using Vibration Data by Adjoint Variable Method by Akbar Mirzaee, Mohsenali Shayanfar, Reza Abbasnia

Get full text

Data-Driven Computational Methods in Fuel Combustion: A Review of Applications by Jacek Lukasz Wilk-Jakubowski, Lukasz Pawlik, Damian Frej, Grzegorz Wilk-Jakubowski

“…This review article provides a comprehensive analysis of the recent advancements in combustion science and engineering, focusing on the application of machine learning and genetic algorithms from 2015 to 2024. …”
Get full text