A Real-World Study of Prognosis of N0M0 Hepatocellular Carcinoma with Hepatic Resection Based on SEER Database by Guangxi Zhu, Wensheng Wang, Qin Liu, Dongfeng Chen, Liangzhi Wen

“…To develop and validate a simple-to-use nomogram for prediction of 3-/5-year survival in patients with N0M0 hepatocellular carcinoma after curative liver resection. …”
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Dynamic Response Analysis of Planar Multilink Mechanism considering Wear in Clearances by Shuai Jiang, Xiulong Chen, Yu Deng

“…The iterative wear prediction process based upon Archard’s model has been applied to calculate wear characteristics. …”
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A Dynamic Source Tracing Method for Food Supply Chain Quality and Safety Based on Big Data by Jun Song, Hong Huo, Teng Li, Lingyun Chu

“…At first, this paper summarized the variables of food supply chain quality and safety, constructed a Petri net model and a Bayesian network model for food quality prediction and source tracing, and realized the prediction of food quality features. …”
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Performance evaluation metric for statistical learning trading strategies by Jiawei He, Roman N. Makarov, Jake Tuero, Zilin Wang

“…We analyze how the sentiment of financial news can be used to predict stock returns and build profitable trading strategies. …”
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Forecasting of Ionospheric Total Electron Content Data Using Multivariate Deep LSTM Model for Different Latitudes and Solar Activity by Nayana Shenvi, Hassanali Virani

“…We also tested its prediction capability during the occurrence of a geomagnetic storm. …”
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An enhanced rainfall-induced landslide catalogue in Italy by Maria Teresa Brunetti, Stefano Luigi Gariano, Massimo Melillo, Mauro Rossi, Silvia Peruccacci

“…Abstract With the increasing use of data-driven landslide prediction models also based on artificial intelligence, the availability of accurate information on the occurrence of landslides and the rigorous reconstruction of their triggering rainfall conditions are crucial. …”
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Advantages of Combining Factorization Machine with Elman Neural Network for Volatility Forecasting of Stock Market by Fang Wang, Sai Tang, Menggang Li

“…The Elman recurrent network is renowned for its capability of dealing with dynamic information, which has made it a successful application to predicting. We developed a hybrid approach which combined Elman recurrent network with factorization machine (FM) technique, i.e., the FM-Elman neural network, to predict stock market volatility. …”
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Parking Volume Forecast of Railway Station Garages Based on Passenger Behaviour Analysis Using the LSTM Network by Songxue Gai, Xiaoqing Zeng, Tengfei Yuan

“…Compared with the ungrouped data model and the conventional forecast model, the proposed parking volume forecast model based on passenger behaviours with the LSTM network achieves a better performance and provides more accurate prediction.…”
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An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning by Néstor Rodríguez-Padial, Marta Marín, Rosario Domingo

“…This paper addresses this tactical goal and aims to provide greater knowledge and better predictions by projecting reliable behavior in the medium-term, integrating this new functionality into classic Balance Scorecards, and making it possible to extend their current measuring function to a new aptitude: predicting evolution based on historical data. …”
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Analysis of College Students’ Public Opinion Based on Machine Learning and Evolutionary Algorithm by Jinqing Zhang, Pengchao Zhang, Bin Xu

“…The experiment result shows that the new pipeline works well, and the predictor has high accuracy on predicting fresh samples. The design procedure and the prediction design will provide suggestions to deal with students’ state of mind and the college’s public opinion.…”
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Coupling WRF Double-Moment 6-Class Microphysics Schemes to RRTMG Radiation Scheme in Weather Research Forecasting Model by Soo Ya Bae, Song-You Hong, Kyo-Sun Sunny Lim

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Compensation of Linear Multiscale Doppler for OFDM-Based Underwater Acoustic Communication Systems by A. E. Abdelkareem, B. S. Sharif, C. C. Tsimenidis, J. A. Neasham

“…The first method employed to achieve an estimate of this particular parameter is based upon centroid localization and this prediction is reinforced by a second technique which utilises linear prediction, based on the assumption that the speed changes linearly during the OFDM symbol time. …”
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A Topological Approach to Enhancing Consistency in Machine Learning via Recurrent Neural Networks by Muhammed Adil Yatkin, Mihkel Kõrgesaar, Ümit Işlak

“…In other words, if different time stamps are used during the prediction phase after training, the model is still expected to give consistent predictions based on the knowledge it has learned. …”
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Applications of the Atmospheric Transport and Diffusion of LES Modeling to the Spread and Dissipation of COVID-19 Aerosol Particles inside and outside the Japan National Stadium (T... by Takanori Uchida, Ryo Araya

“…First, to verify the prediction accuracy of the gas diffusion using RIAM-COMPACT, comparisons with past wind tunnel test results conducted on simple and complex terrains are presented under neutral atmospheric stability. …”
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Data-Driven Decision Algorithm for Open Caisson Foundation Construction by Wei Tian, Hao Li, Yongwei Wang, Yanjiang Zhu, Hao Zhu, Kunyao Li

“…The multilabel classification task of predicting the instructions of large open caisson excavation is accomplished through the problem analysis. …”
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Hybrid Model–Data-Driven Radar Jamming Effectiveness Evaluation Method for Accuracy Improvement by Runyang Chen, Yi Zhang, Xiuhe Li, Jinhe Ran, Qianqian Shi

“…Compared with the model-driven method, the RMSE (Root Mean Square Error) of the prediction results of this method is reduced by 88.26% and the MRE (Mean Relative Error) is reduced by 92.00%.…”
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Fatigue Characteristics of Prestressed Concrete Beam under Freezing and Thawing Cycles by Yuanxun Zheng, Lei Yang, Pan Guo, Peibing Yang

“…Finally, the relation between fatigue characteristics and numbers of freeze-thaw cycles was established, and the fatigue life prediction formulas of prestressed concrete beams under freeze-thaw cycles were developed. …”
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Modeling and Error Compensation of Robotic Articulated Arm Coordinate Measuring Machines Using BP Neural Network by Guanbin Gao, Hongwei Zhang, Hongjun San, Xing Wu, Wen Wang

“…To avoid tedious training and improve the training efficiency and prediction accuracy, a data acquisition strategy is developed according to the actual measurement behavior in the joint space. …”
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A 3.5-Dimensional Variational Method for Doppler Radar Data Assimilation and Its Application to Phased-Array Radar Observations by Qin Xu, Li Wei, Wei Gu, Jiandong Gong, Qingyun Zhao

“…In this method, incremental analyses are performed in three steps to update the model state upon the background state provided by the model prediction. First, radar radial-velocity observations from three consecutive volume scans are analyzed on the model grid. …”
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Deep Learning of Temperature – Dependent Stress – Strain Hardening Curves by Nikolić, Filip, Čanađija, Marko

“…The ML model has shown excellent prediction accuracy in the temperature range from 20 °C to 250 °C. …”
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