Data-Driven Prediction Methods for Lithium-Ion Battery State of Health Based on Elbow Rule by Liu Zhang, Bo Xing, Yanbing Gao, Lei Yao, Dengfeng Zhao, Jinquan Ding, Yanyan Li

“…To eliminate data redundancy, a novel principal component analysis strategy based on the elbow optimization rule was introduced. …”
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Edge-Based Dynamic Spatiotemporal Data Fusion on Smart Buoys for Intelligent Surveillance of Inland Waterways by Ruolan Zhang, Chenhui Zhao, Yu Liang, Jingfeng Hu, Mingyang Pan

“…The method employs an enhanced Long Short-Term Memory network for precise trajectory prediction of AIS data and a single-stage target detection model for video data analysis. …”
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Automated Classification Model for Elementary Mathematics Diagnostic Assessment Data Based on TF-IDF and XGBoost by Seonghyun Park, Seungmin Oh, Woncheol Park

“…This study proposes a system that analyzes elementary school mathematics diagnostic assessment data to generate personalized feedback. The proposed system integrates Term Frequency-Inverse Document Frequency (TF-IDF) and eXtreme Gradient Boosting (XGBoost) to vectorize textual data and automatically classify learning error patterns. …”
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Sunrise in the Desert: Leveraging Big Data Analytics for Predictive Solar Energy Production in Saudi Arabia by Da'ad Albahdal, Maha Almousa, Wijdan Aljebreen, Aeshah A. Almutairi

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Metro Train Stopping Scheme Decision Based on Multisource Data in Express-Local Train Mode by Jin Li, Yaqiu Wang, Shiyin Zhang, Huasheng Liu

“…Based on the multisource data, the spatial weight function is introduced to fuse the point of interest data and real estate information data, from which one obtains the residential index and office index, and the cluster analysis is conducted to obtain the potential stop scheme. …”
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COMPARISON OF AUTOREGRESSIVE MODEL WITH MISSING DATA TREATED USING ORDINARY LEAST SQUARES AND INTERPOLATION WITH WEIGHTING METHOD by Syifani Akmaliah, Dianne Amor Kusuma, Budi Nurani Ruchjana

“…Therefore, in order to do a good time series analysis, it is necessary to make an effort to correct the missing data. …”
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Object-Based Downscaling Method for Land Surface Temperature with High-Spatial-Resolution Multispectral Data by Siyao Wu, Shengmao Zhang, Fei Wang

“…Numerous approaches have downscaled MODIS LST images to a finer spatial resolution using pixel-based image analysis (PBA). Meanwhile, object-based image analysis (OBIA) methods, which have developed rapidly in the analysis of high-spatial-resolution visible and near-infrared (VNIR) band data, have received little attention in the LST downscaling field. …”
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Artificial neural network forecast application for fine particulate matter concentration using meteorological data by M. Memarianfard, A.M. Hatami, M. Memarianfard

“…Furthermore, the “R” value for regression analysis of training, validation, test, and all data are 0.65898, 0.6419, 0.54027, and 0.62331, respectively. …”
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Enhancing Flow Direction in Geothermal Fields Using Sentinel-1 Data for Sustainability Water Management by Utama Widya, Anjasmara Ira Mutiara, Handayani Hepi Hapsari, Indriani Rista Fitri

“…The model is built with 500 trees (n.trees), using a mtry of 2 for the rainy season and 3 for the dry season, and out-of-bag (OOB) error estimates of 8.76% and 9.32%, respectively. …”
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Gravity Data Fusion and Imaging of Geological Structures in the Red River Fault Zone and Adjacent Areas by Guiju Wu, Fei Yu, Hongbo Tan, Jiapei Wang, Weihua Liu

“…The experimental results show that the fuses data not only reflect the regional anomaly trend but also maintain the local anomaly information; the root-mean-square error of the fused data is less than 5% and the correlation coefficient is greater than 90%. …”
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Learning model combined with data clustering and dimensionality reduction for short-term electricity load forecasting by Hyun-Jung Bae, Jong-Seong Park, Ji-hyeok Choi, Hyuk-Yoon Kwon

“…As a result, the prediction accuracy of the proposed method outperforms those of the existing methods by 1.01–1.76 times for summer data and by 1.03–1.36 times for winter data in terms of mean absolute percentage error (MAPE).…”
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Predictions of Equatorial Vertical Plasma Drift Using TEC Data and a Neural Network Model by S. A. Reddy, X. Pi, C. Forsyth, A. Aruliah, A. Smith

“…The model is capped at quiet and unsettled activity levels (Kp < 3). MC analysis reveals that predictions should be interpreted as distributions and the uncertainty can vary with distributions of TEC data and regions of prediction even if the predicted value is the same. …”
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A novel small-scale wind-turbine blade failure detection according to monitored-data by A. Aranizadeh, H. Shad, B. Vahidi, A. Khorsandi

“…Also, this procedure is completely based on logic and mathematical analysis and is far from human error. Accordingly, it has high performance accuracy. …”
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Linking citation and retraction data reveals the demographics of scientific retractions among highly cited authors. by John P A Ioannidis, Angelo Maria Pezzullo, Antonio Cristiano, Stefania Boccia, Jeroen Baas

“…Using data from the Retraction Watch database (RWDB), retraction records were linked to Scopus citation data. …”
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Uncertainty Quantification of Geophysical and Hydrologic Parameters Estimated From Borehole Nuclear Magnetic Resonance Data by Burke J. Minsley, Stephanie N. Phillips, Stephanie R. James

“…Additionally, data error is estimated as an unknown parameter. …”
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Control-Relevant Adaptive Personalized Modeling From Limited Clinical Data for Precise Warfarin Management by Affan Affan, Jacek M. Zurada, Tamer Inanc

“…<italic>Conclusion:</italic> This paper proposes an adaptive personalized patient modeling framework from limited patientspecific clinical data. It is shown by rigorous simulations that the proposed framework can accurately predict a patient&#x0027;s doseresponse characteristics and it can alert the clinician whenever identified models are no longer suitable for prediction and adapt the model to the current status of the patient to reduce the prediction error.…”
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GeneCOCOA: Detecting context-specific functions of individual genes using co-expression data. by Simonida Zehr, Sebastian Wolf, Thomas Oellerich, Matthias S Leisegang, Ralf P Brandes, Marcel H Schulz, Timothy Warwick

“…These methods typically use gene sets as input data, and subsequently return overrepresented terms along with associated statistics describing their enrichment. …”
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A hybrid model for multimedia data compression using generative adversarial networks and chaotic encryption by P.T. Sivagurunathan, A. Sridevi

“…Hence there arises a dire need for data compression and encryption for an effective and secure transmission of data. …”
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Impact of Instantaneous Parameter Sensitivity on Ensemble‐Based Parameter Estimation: Simulation With an Intermediate Coupled Model by Lige Cao, Guijun Han, Wei Li, Haowen Wu, Xiaobo Wu, Gongfu Zhou, Qingyu Zheng

“…Abstract On ensemble‐based coupled data assimilation, cross‐component parameter estimation (CPE), has not been as extensively developed and applied as weakly coupled state and parameter estimation along with cross‐component state estimation. …”
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Evaluating reservoir permeability from core data: Leveraging boosting techniques and ANN for heterogeneous reservoirs by Amad Hussen, Tanveer Alam Munshi, Minhaz Chowdhury, Labiba Nusrat Jahan, Abu Bakker Siddique, Mahamudul Hashan

“…This work investigates and implements four novel approaches for permeability prediction from standard core analysis data. These approaches include hybrid stacking and three boosting techniques: AdaBoost, gradient boosting, and extreme gradient boosting (XGB). …”
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