Prediction Model for Connected Voids Ratio of the Porous Asphalt Mixture by Xiang Li, Zhaoyi He

“…The relation between the equivalent width, passing ratio of key sieve, and connected voids was discussed, and hence the prediction model for connected voids was established. …”
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Exploring the Implications of Modeling Choices on Prediction of Irrigation Water Savings by Chinedum Eluwa, Baptiste Francois, Alec Bernstein, Casey Brown

“…This study addresses that gap and explores how the modeling choices that are necessary to represent the hydrological effects of reduced non‐beneficial consumption influence the prediction of water savings. …”
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Nonlinearity Estimation and Compensation for Accurate PMSM Modeling and Voltage Prediction by Beichen Ding, Yuting Lu, Chunyan Lai, Weiwen Peng, Kaide Huang, Guodong Feng

“…For permanent magnet synchronous machine (PMSM), the machine model is critical to predict the operating states for motor control, which, however, can be greatly affected by system nonlinearities. …”
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Development of novel hybrid models for the prediction of Covid-19 in Kuwait by Ahmad Aldousari, Maria Qurban, Ijaz Hussain, Maha Al-Hajeri

“…There is a need to estimate a prediction model for the estimation of this epidemic size. …”
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Predictions With a Purpose: Elevating Standards for Clinical Modeling Research by Patrick G. Lyons, MD, MSc

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Deep Learning Models for Predicting the Recurrence of Idiopathic Granulomatous Mastitis by Li L, Yang W, Jia H

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A Markov Prediction Model Based on Page Hierarchical Clustering by Yao Yao, Lei Shi, Zhanhong Wang

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Optimizing Deep Learning Models with Improved BWO for TEC Prediction by Yi Chen, Haijun Liu, Weifeng Shan, Yuan Yao, Lili Xing, Haoran Wang, Kunpeng Zhang

Subjects: “…TEC prediction…”
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Flood Prediction in Ungauged Basins by Physical-Based TOPKAPI Model by Xiangyi Kong, Zhijia Li, Zhiyu Liu

“…Scarce historical flood data in ungauged basins make it difficult to establish empirical and conceptual model forecast in these areas. The physical-based distributed model TOPKAPI is introduced for flood prediction in an ungauged basin by parameter transplant. …”
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Core-Level Modeling and Frequency Prediction for DSP Applications on FPGAs by Gongyu Wang, Greg Stitt, Herman Lam, Alan George

“…Previous works have enabled model-based, design-space exploration to reduce DTE iterations but are limited by a lack of accurate model-based prediction of key design parameters, the most important of which is clock frequency. …”
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Stock price prediction using combined GARCH-AI models by John Kamwele Mutinda, Amos Kipkorir Langat

“…The non-linear and non-stationary nature of financial time series data poses significant challenges for standalone statistical and neural network methods. While predictive modeling in finance often focuses on volatility, there is a notable lack of research on predicting actual stock prices, particularly in the African market. …”
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Spatiotemporal data modeling and prediction algorithms in intelligent management systems by Xin Cao, Chunxiao Mei, Zhiyong Song, Hao Li, Jingtao Chang, Zhihao Feng

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Calibrating AI Models for Wireless Communications via Conformal Prediction by Kfir M. Cohen, Sangwoo Park, Osvaldo Simeone, Shlomo Shamai Shitz

“…This paper investigates the application of conformal prediction as a general framework to obtain AI models that produce decisions with formal calibration guarantees. …”
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Hybrid Deep Learning Models for Predicting Student Academic Performance by Kuburat Oyeranti Adefemi, Murimo Bethel Mutanga, Vikash Jugoo

“…This study aims to bridge this gap by proposing a deep learning model to predict student academic performance with greater accuracy. …”
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Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction by Ashutosh Modi, Ivan Titov, Vera Demberg, Asad Sayeed, Manfred Pinkal

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Heart Disease Prediction: Leveraging CNNs and XAI Modeling for Interpretability by Sakib Rokoni, Md. Amirul Islam, Md. Arafuzzaman, Shafiul Bashar, Md. Rakibul Hasan, Md Tariqul Islam

“… This study examines heart disease prediction using machine learning models, focusing on interpretability, leveraging a dataset of 1,319 entries containing nine health-related attributes. …”
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Hypernetwork link prediction method based on the SCL-CMM model by REN Yuyuan, MA Hong, LIU Shuxin, WANG Kai

“…Existing methods typically design reasoning models for the entire topology, often overlooking the implicit aggregation characteristics within the network, which leads to an incomplete prediction of hyperlink categories. …”
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Machine learning models for predicting tibial intramedullary nail length by Sercan Capkin, Ali Ihsan Kilic, Hakan Cici, Mehmet Akdemir, Mert Kahraman Marasli

“…The correlation between shoe size and the dependent variable was weaker (r = 0.823), and the inclusion of shoe size in the model negatively impacted the prediction accuracy. …”
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An explainable Bi-LSTM model for winter wheat yield prediction by Abhasha Joshi, Biswajeet Pradhan, Subrata Chakraborty, Subrata Chakraborty, Renuganth Varatharajoo, Abdullah Alamri, Shilpa Gite, Chang-Wook Lee

“…Thus, this study aims to develop and implement an explainable DL model capable of accurately predicting crop yield and providing explanations for the predictions. …”
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Modeling and Prediction of a Guidewire's Reachable Workspace and Deliverable Forces by Afsoon Nejati-Aghdam, M. Ali Tavallaei

“…<italic>Methods:</italic> We used finite element (FE) analysis to simulate the interaction between the guidewire and a model of a tortuous vessel, and we used this simulation to predict the reachable workspace and deliverable forces of the device for various entry positions and angles. …”
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