MODELS AND TOOLS OF PREDICTING ANALYTICAL RESEARCH FOR DIGITAL CORPORATION by Sergey N. Bruskin

“…The article discusses promising approaches to creating a digital corporation by using methods and technologies of predicting analytical research and describes principles of transforming the existing company information systems into digital systems of corporate governance. …”
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Generalizable deep learning models for predicting laboratory earthquakes by Chonglang Wang, Kaiwen Xia, Wei Yao, Chris Marone

“…Abstract Machine learning models can predict laboratory earthquakes using Acoustic emission, the lab equivalent of microseismicity, and changes in fault zone elastic properties during the lab seismic cycle. …”
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Comparative Analysis of Wear Models for Accurate Wear Predictions by Guntis Springis, Irina Boiko

“…Recent advancements have sought to address these limitations by integrating probabilistic surface modelling, fatigue-based degradation theories, and numerical simulations to enhance wear predictions. …”
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Incorporating prediction in models for two-dimensional smooth pursuit. by John F Soechting, Hrishikesh M Rao, John Z Juveli

“…The objective of this study was to characterize the predictive contributions to pursuit tracking more precisely by developing analytical models for predictive smooth pursuit. …”
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Bankruptcy Prediction Models for Construction Companies in the Russian Federation by A. V. Voiko

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Adversarial defense for battery state-of-health prediction models by Masoumeh Mohammadi, Insoo Sohn

“…Results indicate that the proposed strategy significantly improves the model’s ability to accurately predict SOH, even in the presence of malicious data.…”
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Tabular Data Models for Predicting Art Auction Results by Patryk Mauer, Szczepan Paszkiel

“…Additionally, we address the interpretability of models, which is crucial for understanding the influence of various features on predictions. …”
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Machine learning models for enhanced stroke detection and prediction by Shilpa Bajaj, Manju Bala, Mohit Angurala

“…This research evaluates the performance of three machine learning models—OzNet-mRMR-NB, Logistics Regression, and an Ensemble CNN—using medical images for stroke prediction. …”
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Comparative Analysis of Several Models for Churning Customer Prediction by Tan Zhaoyuan

“…This study compares three machine learning models: Random Forest, XGBoost Classifier, and Light Gradient Boosting Machine Classifier for predicting credit card customer churn using a dataset from Kaggle. …”
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Comparisons of Machine Learning Models for Prediction of Susceptibility to Diabetes by Jiao Yutian

“…This study compares the predictive performance of machine learning models such as Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM). …”
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Enhancing molecular property prediction with quantized GNN models by Areen Rasool, Jamshaid Ul Rahman, Rongin Uwitije

“…These challenges hinder the deployment of property prediction models on resource-constrained devices such as smartphones and IoT devices. …”
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Prediction of Air Quality Index Using Ensemble Models by Theresia Herlina Rochadiani

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Predicting Financial Market Volatility with Modern Model and Traditional Model by R. G. Aldeki

“…There is evidence that the GARCH-SVR model performs best for predicting volatility time series, and classical volatility model techniques have an enormous predictive performance better than machine learning models.…”
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Current preeclampsia prediction model and biomarker by Anak Agung Ngurah Jaya Kusuma

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Control of Electric Drive with Predicting Model by N. N. Micheev, E. P. Ratkevich

“…The proposed predicting model permits to exclude immediate rapid time calculations of a control value.…”
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Nonlinear Autoregressive Model for Stability and Prediction by Salim M. Ahmad, Anas S. Youns, Manal S. Hamdi

“…A proposed nonlinear autoregressive model was employed to predict daily new COVID-19 infections in Iraq. …”
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Grey Model for Stream Flow Prediction by Vishnu B, Syamala P

“…Statistical indices for the developed models indicate their ability to predict stream flow in the river under study with reasonable accuracy.…”
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Data Visualization and Prediction Model Analysis by Hua Ziyi

“…The purpose of this paper is to study the application of data visualization and compare different prediction models. In this work, I present three different prediction models and apply them on the US airline industry datasets by using Python as the programming language. …”
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From maps to models: Key concepts in Geographic Information Systems by Yohannes Shifera Daka, Kassaye Hussein, Ashenafi Yimam

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Machine Learning for Non-Destructive Prediction of Sunflower Leaf Area by Joao Everthon da Silva Ribeiro, Antonio Gideilson Correia da Silva, Pablo Henrique de Almeida Oliveira, Josiana Micarla da Silva Oliveira, Alessandra Nunes da Silva, John Victor Lucas Lima, Ivan Euzebio da Silva, Ester Dos Santos Coelho, Isaque de Oliveira Leite, Elania Freire da Silva, Toshik Iarley da Silva, Lindomar Maria da Silveira, Aurelio Paes Barros Junior

“…Therefore, the present study aimed to develop and compare linear regression models and machine learning algorithms for the non-destructive prediction of leaf area in four sunflower cultivars (BRS 323, Altis 99, Sany 66, and BRS 442). …”
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