Developing A Predictive Model for Small Business Loan Default by Refiloe Gladys Benedict, O Stumke, Veruschka Pelser Carstens

“…This paper proposes a model aimed at proactively increasing loan repayment probabilities. …”
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Ada-GCNLSTM: An adaptive urban crime spatiotemporal prediction model by Miaoxuan Shan, Chunlin Ye, Peng Chen, Shufan Peng

“…Additionally, the inherent randomness and volatility of crime data at the spatiotemporal level introduce noise, which can mislead prediction models. While many effective spatiotemporal crime prediction methods have been proposed, most overlook this issue, reducing their ability to generalize. …”
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Predictive Modeling of Environmental Impact on Drone Datalink Communication System by I. Bennageh, H. Mahmoudi, H. Hajjaji, I. Laabousse, A. Hamdouchi

“…Through a comparative analysis of the model’s predictions against actual signals received in three distinct environments, the model’s efficacy in diverse scenarios is affirmed. …”
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Research on network traffic prediction based on Bi-GRU model by Xu Haibing, Guo Jiuming

“…This paper proposes an improved GRU model for traffic prediction. Firstly, based on GRU neural network, a network model integrating Bi-GRU neural network and artificial neural network is proposed, which satisfies the input of multi-dimensional vectors such as traffic features, time features and event features. …”
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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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Predictions With a Purpose: Elevating Standards for Clinical Modeling Research by Patrick G. Lyons, MD, MSc

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

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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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Establishment and validation of predictive model of ARDS in critically ill patients by Senhao Wei, Hua Zhang, Hao Li, Chao Li, Ziyuan Shen, Yiyuan Yin, Zhukai Cong, Zhaojin Zeng, Qinggang Ge, Dongfeng Li, Xi Zhu

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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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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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Historical Use of Markov Model and Posterior Predictive Checks in Pharmacometrics by Pascal Girard, Helen Kastrissios

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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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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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Research on link prediction model based on hierarchical attention mechanism by Xiaojuan ZHAO, Yan JIA, Aiping LI, Kai CHEN

“…In order to solve the problem that the existing graph attention mechanism tends to cause attention distribution to certain relations with high frequency when performing link prediction related tasks, a new link prediction model based on hierarchical attention mechanism was proposed.In the link prediction task, a hierarchical attention mechanism was designed to give different attention to the relationships of different relationship types connected to a given entity in the knowledge graph according to the relationship in the prediction task.While the characteristics of multi-hop neighbor entities were pay attention to, the relationship characteristics was pay more attention to find the relationship type that matches the target relationship.Through comparison experiments with the mainstream models on multiple benchmark data sets, the results show that the performance of the model is better than the mainstream models and has good robustness.…”
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