A Combined PSO-LSTM Prediction Model for Dam Deformation by HAO Ze-jia, SHI Yu-qun, CHENG Bo-chao, HE Jin-ping

“…By leveraging the long-short-term memory (LSTM) model and particle swarm optimization (PSO) algorithm from artificial intelligence technology, a combined PSO-LSTM dam deformation prediction model is established, offering a novel approach for enhancing the accuracy of dam deformation prediction. …”
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PREDICTING THE SHELF LIFE OF SUNFLOWER MEAL USING KINETIC MODELS by T. Matveeva, V. Papchenko, P. Petik, N. Staroselska, V. Khareba, O. Khareba

“…The study proposes a method for predicting the oxidative stability of sunflower meal during long-term storage using the Arrhenius model, which describes the dependence of the reaction rate on temperature. …”
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Applying binary mixed model to predict knee osteoarthritis pain by Helal El-Zaatari, Liubov Arbeeva, Amanda E. Nelson

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Machine learning modeling for predicting adherence to physical activity guideline by Ju-Pil Choe, Seungbak Lee, Minsoo Kang

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A hybrid VMD-LSTM-SVR model for landslide prediction by Nianhong Wang, Meijun Wang, Jun Zhang

“…The results indicate that the VMD-SVR-LSTM model, with an RMSE of 0.0328 and an R2 of 0.8487, demonstrates the best predictive accuracy and fitting capability. …”
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Introducing Weather Factor Modelling into Macro Traffic State Prediction by Yuwei Bie, Tony Z. Qiu, Can Zhang, Cunbao Zhang

“…This paper proposes a weather factor model to be plugged into a macroscopic traffic prediction model, so that under bad weather traffic variables can be more accurately and reasonably estimated and predicted for traffic control use. …”
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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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Prediction and modeling of connectivity probability in vehicular Ad Hoc networks by Huimin WANG, Haitao ZHAO

“…Recently，with the rapid development of vehicular communication technology，IoV（internet of vehicles）as one of the applications of IoT（internet of things），is attracting more and more attention as well as its basic applications.The algorithm of predicting the connectivity probability based on highway model was proposed.Also，the joint distribution of vehicles on highway was studied，and the equation calculating the boundaries of connectivity probability on one road segment was analyzed quantitatively.The diagram presenting the relationship between the connectivity probability on one road segment and the average number of vehicles in each tuple was depicted by Rstudio.As a consequence，the model of connectivity probability on one path was achieved by calculating the products of the connectivity probability on all road segments along one path.The analysis result shows that the connectivity probability on one path can be improved by increasing the communication range or the density of vehicles.…”
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Prediction of coalbed methane productivity based on neural network models by JIN Yi, ZHENG Chenhui, SONG Huibo, MA Jiaheng, YANG Yunhang, LIU Shunxi, ZHANG Kun, NI Xiaoming

“…The prediction accuracy is significantly higher than the BP model.ConclusionsThe model has good stability and high prediction accuracy. …”
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Ensemble prediction modeling of flotation recovery based on machine learning by Guichun He, Mengfei Liu, Hongyu Zhao, Kaiqi Huang

“…Nevertheless, current prediction models suffer from low accuracy and high prediction errors. …”
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A modular protein language modelling approach to immunogenicity prediction. by Hugh O'Brien, Max Salm, Laura T Morton, Maciej Szukszto, Felix O'Farrell, Charlotte Boulton, Laurence King, Supreet Kaur Bola, Pablo D Becker, Andrew Craig, Morten Nielsen, Yardena Samuels, Charles Swanton, Marc R Mansour, Sine Reker Hadrup, Sergio A Quezada

“…Here we describe ImmugenX, a modular protein language modelling approach to immunogenicity prediction for CD8+ reactive epitopes. …”
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Road Accident Prediction Model for the Roads of National Significance of Lithuania by Vilma Jasiūnienė, Donatas Čygas

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Delving into Underwater Image Utility: Benchmark Dataset and Prediction Model by Jiapeng Liu, Yi Liu, Qiuping Jiang

“…On the other hand, based on this newly constructed OD-UIUA dataset, we train a deep UIUA network (DeepUIUA) that can automatically and accurately predict UIUS. To the best of our knowledge, this is the first benchmark dataset for UIUA and also the first model focusing on the specific UIUA problem. …”
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USING MACHINE LEARNING MODELS TO PREDICT THE NUMBER OF ELECTRONIC TRANSACTIONS by Andrey Valeryevich Malikov, David Mherovich Aghajanyan, Pavel Petrovich Tarasevich

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Development of an Injury Burden Prediction Model in Professional Baseball Pitchers by Garrett Bullock, Charles Thigpen, Gary Collins, Nigel Arden, Thomas Noonan, Michael Kissenberth, Ellen Shanley

“…Separate elbow and shoulder prediction models demonstrated decreased performance. …”
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An optimized informer model design for electric vehicle SOC prediction. by Xin Xie, Feng Huang, Yefeng Long, Youyuan Peng, Wenjuan Zhou

“…Informer model is better than other models in SOC prediction, but there is still a gap in practical application. …”
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Predicting avalanche danger in northern Norway using statistical models by K.-U. Eiselt, R. G. Graversen, R. G. Graversen

“…The binary-case RF model exhibits a much higher overall accuracy (76 %) than the four-level case RF model (57 %), which is due to the latter model often misclassifying ADL 1 as ADL 2 and ADL 4 as ADL 3. …”
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Development of risk prediction model for small incision lenticule extraction by Shaowei Zhang, Yulin Yan, Zhengwei Shen, Lei Liu, Pengqi Wang, Jian Zhu, Yanning Yang

“…The RF model, based on clinical characteristics, showed excellent performance in predicting SMILE suitability and has potential as a valuable tool for clinical decision-making in the future.…”
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A novel hybrid model for predicting the bearing capacity of piles by Li Tao, Xinhua Xue

“…The main objective of this study is to propose a hybrid model coupling least squares support vector machine (LSSVM) with an improved particle swarm optimization (IPSO) algorithm for the prediction of bearing capacity of piles. …”
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Sand Production Prediction Model for Tight Sandstone Oil Reservoirs by Zhan-dong Li, Hong Pang, Zhong Li, Hai-xiang Zhang, Dian-ju Wang, Ji Li

“…Based on the combination of the formation fluid seepage law and the stress distribution around the well, a sand production prediction model is proposed to quantitatively estimate the sand production rate. …”
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