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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“Revealing the future”: an ARIMA model analysis for predicting remittance inflows by Imran Khan, Darshita Fulara Gunwant

“…Purpose – The purpose of this research is to develop a predictive model that can estimate the volume of remittances channeled toward Yemen’s economic reconstruction efforts. …”
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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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An Intelligent Deep Learning Model for CO2 Adsorption Prediction by Hanan Ahmed Hosni Mahmoud, Nada Ali Hakami, Alaaeldin M. Hafez

“…Three tree machine learning models, namely, gradient decision model (GDM), scalable boosting tree model (SBT), and gradient variant decision tree model (GVD), were fused. …”
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A donor heart scoring model to predict transplant outcomes by E. A. Tenchurina, M. G. Minina

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Research on Yield Prediction Model Driven by Mechanism and Data Fusion by Xin Meng, Xingyu Liu, Hancong Duan, Ze Hu, Min Wang

“…Then, a Global–Local Branch Prediction Model is designed to enhance both long-term trend estimation and local feature capture in a production time series. …”
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Development of an Early-Warning Model for Predicting the Capecitabine-Induced Diarrhea by Liu Z, Qiu S, Xu Y, Wang X, Sun J, Cui L, Ye L, Liang Z, Gao S, Chen W, Wang Z

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Traffic Flow Prediction Based on Fractional Seasonal Grey Model by SHEN Qinqin; ZHANG Zhijie; QI Xucun; YUE Xinyi

“…The numerical results show that the average absolute percentage of the new model has a fitting error of 8. 1260% and a prediction error of 7. 6216%, which are much better than those of the seasonal rolling GM(1, 1)model, fractional GM(1, 1) model and seasonal discrete GM(1, 1) model.…”
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A Stock Prediction Model Based on Cart and Boosting Algorithm by WANG Yu, CHEN De-yun, TANG Yuan-xin

Subjects: “…stock prediction model…”
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A novel model for malaria prediction based on ensemble algorithms. by Mengyang Wang, Hui Wang, Jiao Wang, Hongwei Liu, Rui Lu, Tongqing Duan, Xiaowen Gong, Siyuan Feng, Yuanyuan Liu, Zhuang Cui, Changping Li, Jun Ma

“…<h4>Background and objective</h4>Most previous studies adopted single traditional time series models to predict incidences of malaria. A single model cannot effectively capture all the properties of the data structure. …”
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Prediction of Landslide Displacement Based on EMD-TAR Combined Model by CHEN Xi, GAO Yaping, TU Rui

Subjects: “…prediction of landslide displacement…”
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Predicting Excavation-Induced Tunnel Response by Process-Based Modelling by Linlong Mu, Jianhong Lin, Zhenhao Shi, Xingyu Kang

“…To illustrate such a concept, this paper presents a simple process-based model consisting of artificial neural network (ANN) module, inverse modelling module, and mechanistic module. …”
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Flight delay stacking ensemble prediction model for severe weather by SUN Yue, DING Jianli

“…Weather factors, as the primary factors affecting flight delays, have an important impact on flight delay prediction. Confronting the severe weather, multi-classification prediction of flight delay duration was made, and a Stacking-based integrated flight delay prediction model was proposed for the problems of low prediction accuracy and poor stability of traditional single model. …”
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Air Quality Index Prediction Using DNN-Markov Modeling by Roba Zayed, Maysam Abbod

“…DNN-Markov modeling techniques are used to predict air quality, based on environmental conditions at peak hours. …”
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Evaluation of changes in prediction modelling in biomedicine using systematic reviews by Lara Lusa, Franziska Kappenberg, Gary S. Collins, Matthias Schmid, Willi Sauerbrei, Jörg Rahnenführer, on behalf of the Topic Group for High-dimensional data of the STRATOS initiative

“…Abstract The number of prediction models proposed in the biomedical literature has been growing year on year. …”
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Building Fire Location Predictions Based on FDS and Hybrid Modelling by Yanxi Cao, Hongyan Ma, Shun Wang, Yingda Zhang

“…With the goal of addressing the difficulty of rapidly identifying the source of fire in commercial buildings, this study builds a numerical fire model based on the fire dynamics simulator (FDS) and combines it with a hybrid model to predict the location of a fire source. …”
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