Showing 1,721 - 1,740 results of 16,799 for search '"Prediction', query time: 0.10s Refine Results
  1. 1721

    Real-Time Ship Motion Prediction Based on Time Delay Wavelet Neural Network by Wenjun Zhang, Zhengjiang Liu

    Published 2014-01-01
    “…The time delay wavelet neural network was implemented to real-time ship motion prediction, simulations are conducted based on the measured data of vessel “YUKUN,” and the results demonstrate that the feasibility of the proposed method.…”
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    Article
  2. 1722

    Classifying, Predicting, and Reducing Strategies of the Mesh Excitations of Gear Whine Noise: A Survey by Menglei Sun, Chihua Lu, Zhien Liu, Yi Sun, Hao Chen, Cunrui Shen

    Published 2020-01-01
    “…The mechanisms, characteristics, predicting approaches, measuring methods, and decreasing strategies for these excitations are summarized. …”
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    Article
  3. 1723
  4. 1724

    The Optimized Multivariate Grey Prediction Model Based on Dynamic Background Value and Its Application by Tongfei Lao, Xiaoting Chen, Jianian Zhu

    Published 2021-01-01
    “…As a tool for analyzing time series, grey prediction models have been widely used in various fields of society due to their higher prediction accuracy and the advantages of small sample modeling. …”
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    Article
  5. 1725

    AI-based prediction of androgen receptor expression and its prognostic significance in prostate cancer by Jiawei Zhang, Feng Ding, Yitian Guo, Xiaoying Wei, Jibo Jing, Feng Xu, Huixing Chen, Zhongying Guo, Zonghao You, Baotai Liang, Ming Chen, Dongfang Jiang, Xiaobing Niu, Xiangxue Wang, Yifeng Xue

    Published 2025-02-01
    “…The model showed strong performances, with high accuracy in identifying regions with high AR expression and BCR prediction. This AI model may help identify high-risk patients, aiding in better treatment strategies, particularly in underdeveloped areas.…”
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    Article
  6. 1726

    Radiomics-based Machine Learning Approach to Predict Chemotherapy Responses in Colorectal Liver Metastases by Yuji Miyamoto, Takeshi Nakaura, Mayuko Ohuchi, Katsuhiro Ogawa, Rikako Kato, Yuto Maeda, Kojiro Eto, Masaaki Iwatsuki, Yoshifumi Baba, Toshinori Hirai, Hideo Baba

    Published 2025-01-01
    “…Objectives: This study explored the clinical utility of CT radiomics-driven machine learning as a predictive marker for chemotherapy response in colorectal liver metastasis (CRLM) patients. …”
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    Article
  7. 1727
  8. 1728

    Limit Cycle Predictions of Nonlinear Multivariable Feedback Control Systems with Large Transportation Lags by Tain-Sou Tsay

    Published 2011-01-01
    “…A practical method is developed for limit-cycle predictions in the nonlinear multivariable feedback control systems with large transportation lags. …”
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    Article
  9. 1729
  10. 1730

    Development and Validation of 3D Finite Element Models for Prediction of Orthodontic Tooth Movement by Udomsak Likitmongkolsakul, Pruittikorn Smithmaitrie, Bancha Samruajbenjakun, Juthatip Aksornmuang

    Published 2018-01-01
    “…The aim of this study was to develop and validate three-dimensional (3D) finite element modeling for prediction of orthodontic tooth movement. Materials and Methods. …”
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    Article
  11. 1731
  12. 1732

    Expression of some circulating microRNAs as predictive biomarkers for prognosis and treatment response in glioblastoma by Elham Ali, Marwa Adel Ahmed, May A. Shawki, Lobna R. Ezz El Arab, Mohamed K. Khalifa, Menha Swellam

    Published 2025-01-01
    “…Despite multimodal therapies, clinicians lack efficient prognostic and predictive markers. Therefore, new insights into GBM management are urgently needed to increase the chance of therapeutic success. …”
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    Article
  13. 1733

    Development and validation of a nomogram for predicting lung cancer based on acoustic–clinical features by Zhou Lu, Zhou Lu, Jiaojiao Sha, Xunxia Zhu, Xiaoyong Shen, Xiaoyu Chen, Xin Tan, Rouyan Pan, Shuyi Zhang, Shi Liu, Tao Jiang, Jiatuo Xu

    Published 2025-01-01
    “…This nomogram, a unique contribution to the field, provides a reliable tool for predicting lung cancer.…”
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    Article
  14. 1734
  15. 1735
  16. 1736

    A Deep Graph-Embedded LSTM Neural Network Approach for Airport Delay Prediction by Weili Zeng, Juan Li, Zhibin Quan, Xiaobo Lu

    Published 2021-01-01
    “…Due to the strong propagation causality of delays between airports, this paper proposes a delay prediction model based on a deep graph neural network to study delay prediction from the perspective of an airport network. …”
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    Article
  17. 1737

    Nitrogen dynamic and precise management to predict corn yield in tropical upland acid soils by A. Kasno, A.A. Rivaie, C. Tafakresnanto, E. Pratiwi, E. Karmawati, A.F. Siregar, M. Hatta, M.T. Sutriadi

    Published 2024-10-01
    “…This research aims to determine nitrogen dynamics and precise nitrogen nutrient management in corn cultivation using a leaf chlorophyll meter and nitrogen response tests to predict corn yield in tropical upland acid soils.METHODS: This research was conducted in an Ultisol and verified in an Oxisol. …”
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    Article
  18. 1738

    Model-Based Leakage Estimation and Remaining Useful Life Prediction of Control Gas Cylinder by Zhenzhen Zhang, Hui Chen, Chao Qi, Yazhou Liu

    Published 2023-01-01
    “…Calibration results have proved the validity and universality of the method, with the mean absolute error (MAE) for the remaining 80% useful life prediction results being less than 0.02, 0.04, and 1.10. …”
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    Article
  19. 1739

    Development and validation of a deep learning-enhanced prediction model for the likelihood of pulmonary embolism by Yu Tian, Yu Tian, Jingjie Liu, Shan Wu, Yucong Zheng, Rongye Han, Qianhui Bao, Lei Li, Lei Li, Tao Yang

    Published 2025-02-01
    “…Its convolutional architecture and residual modules substantially enhance predictive performance.…”
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    Article
  20. 1740

    Predicting GPR Signals from Concrete Structures Using Artificial Intelligence-Based Method by Wael Zatar, Tu T. Nguyen, Hai Nguyen

    Published 2021-01-01
    “…It is shown that the “trainlm” learning algorithm produced the high accuracy prediction of the reflection amplitude of GPR signals. …”
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    Article