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  1. 16241

    A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

    Published 2024-10-01
    “…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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  2. 16242

    Motion and Inertia Estimation for Non-Cooperative Space Objects During Long-Term Occlusion Based on UKF-GP by Rabiul Hasan Kabir, Xiaoli Bai

    Published 2025-01-01
    “…In particular, we implement the multi-output GP to predict the projection measurements of a stereo-camera system onboard a chaser spacecraft. …”
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    Article
  3. 16243

    Calibration and uncertainty quantification for deep learning-based drought detection by Mengxue Zhang, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Gustau Camps-Valls

    Published 2025-06-01
    “…To address this shortcoming, we introduce methodologies for model calibration and entropy-based uncertainty quantification for deep learning-based drought detection. The calibration algorithm can deal with calibration errors by reducing distributional shifts and alleviating overconfident predictions. …”
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  4. 16244

    Machine learning developed immune-related exosome signature for prognosis and immunotherapy benefit in bladder cancer by Xiaoting Luo, Yi Luo

    Published 2025-04-01
    “…To investigate the performance of IES in predicting the immunotherapy benefit, three immunotherapy datasets (GSE91061, GSE78220 and IMvigor210) and several predicting scores were used. …”
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    Article
  5. 16245

    FORECASTING COHERENT VOLATILITY BREAKOUTS by A. S. Didenko, M. M. Dubovikov, B. A. Poutko

    Published 2017-10-01
    “…The paper develops an algorithm for making long-term (up to three months ahead) predictions of volatility reversals based on long memory properties of financial time series. …”
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    Article
  6. 16246

    ABC and HML-methods application for determination and optimization of stock for electrical equipment accessory parts by A. V. Beloglazov, A. G. Rusina, O. V. Fomenko, D. A. Pekhota, V. A. Fyodorova

    Published 2021-07-01
    “…To describe the use of ABC and HML-methods for predicting the volume of emergency stock for main electrical equipment accessory parts. …”
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    Article
  7. 16247

    A Few-shot Learning Method for Intent Analysis of Air Combat Confrontation Behaviors by PAN Ming, ZHENG Jingsong, LI Jinliang, FANG Long, YANG Yang, ZHAO Shijie

    Published 2024-08-01
    “…The experimental simulation results show that the accuracy of the few-shot contrastive learning algorithm based on data augmentation in predicting the behavior intention of few-shot air combat targets is 91. 13% .…”
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    Article
  8. 16248

    Load–Settlement Modeling of Micropiled Rafts in Cohesive Soils Using an Artificial Intelligence Technique by Ahmed Elsawwaf, Hany El Naggar

    Published 2025-03-01
    “…To advance the adoption of micropiles in geotechnical practice, this study employs a multi-objective genetic algorithm-based evolutionary polynomial regression (EPR-MOGA), a hybrid artificial intelligence method, to develop a robust and straightforward model for predicting the load–settlement response of micropiled rafts in cohesive soils under vertical loads. …”
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    Article
  9. 16249

    Wind Power Installed Capacity Forecast Based on a Two-Parameter Variable-Weight Buffer Operator and Subsidy Strategy Research by Ye Li, Xue Bai

    Published 2022-01-01
    “…Firstly, a new two-parameter variable-weight buffer operator is proposed to quantify the impact of the policy shock, whose optimal parameters are obtained by the genetic algorithm, and combined with the grey GM(1,1) model to predict the installed capacity of wind power in China under the cessation of subsidy policy. …”
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  10. 16250

    Analysis on waypoint-segment routing and performance evaluation for LEO satellite networks by Xin ZHAO, Guang ZHAO, Rui CHEN, Wennai WANG

    Published 2023-02-01
    “…A waypoint-segment routing (WSR) algorithm was proposed.Based on the predictable periodicity of the topological changes of satellite network, the location of satellite waypoints based on the link state of satellite nodes at the current moment was determined by WSR algorithm.The mechanism of flexible planning of packet transmission paths was responded by segment routing to changes in satellite network topology in advance, and a packet transmission path that was not affected by network topology snapshot switch was calculated.Simulation experiment was based on the NS-3, and the optimized link state routing (OLSR) algorithm and the shortest path algorithm were selected to compare with WSR in order to analyze the delay jitter and packet loss rate.It was proved that compared with OLSR, the maximum delay jitter of WSR was reduced by 46 ms and 126 ms respectively in the two scenarios, the packet loss rate was reduced by 30% and 21% respectively, and the problem of packet transmission path interruption caused by topology snapshot switching can be solved.…”
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    Article
  11. 16251

    The Sentiment Analysis Reviewing Indosat Services from Twitter Using the Naive Bayes Classifier by Febri Astiko, Achmad Khodar

    Published 2020-12-01
    “…This sentiment analysis uses machine learning to get patterns an model that can be used again to predict new data. …”
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  12. 16252

    Grasp Detection under Occlusions Using SIFT Features by Zhaojun Ye, Yi Guo, Chengguang Wang, Haohui Huang, Genke Yang

    Published 2021-01-01
    “…There are two key steps for the proposed method in the process of grasping occluded object: generating template information and grasp detection using the matching algorithm. A neural network, trained by the RGB-D data from the Cornell Grasp Dataset, predicts multiple grasp rectangles on template images. …”
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  13. 16253

    Machine learning enhanced expert system for detecting heart failure decompensation using patient reported vitals and electronic health records by Shumit Saha, Heather Ross, Pedro Elkind Velmovitsky, Chloe X. Wang, Julie K. K. Vishram-Nielsen, Cedric Manlhiot, Bo Wang, Joseph A. Cafazzo

    Published 2025-08-01
    “…Further, patients’ electronic health records (EHR) were not used when developing the rules-based algorithm. This study aimed to enhance Medly’s performance with machine learning and include a richer set of data, including EHR, for predicting decompensated HF episodes. …”
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    Article
  14. 16254

    Machine-learning aided calibration and analysis of porous media CFD models used for rotating packed beds by Ahmed M. Alatyar, Abdallah S. Berrouk

    Published 2024-11-01
    “…The algorithm is used to improve CFD predictions of dry pressure drop in rotating packed beds (RPBs) for a wide range of operating conditions. …”
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    Article
  15. 16255

    A unique, consistent identifier for alternatively spliced transcript variants. by Alberto Riva, Graziano Pesole

    Published 2009-10-01
    “…The isoform signature uniquely identifies a transcript structure, and can therefore be used as a key in databases of alternatively spliced isoforms, or to compare alternative splicing predictions produced by different methods. In this paper we present the algorithm to generate isoform signatures, we provide some examples of its application, and we describe a web-based resource to generate isoform signatures and use them in database searches.…”
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  16. 16256

    Particle Filter Tracking without Dynamics by Jaime Ortegon-Aguilar, Eduardo Bayro-Corrochano

    Published 2007-01-01
    “…In this paper, an alternative to address people tracking is presented. The proposed algorithm is based in particle filters, but instead of using a dynamical model, it uses background subtraction to predict future locations of particles. …”
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  17. 16257

    Research on the invulnerability of regional network based on topology analysis by Changqing AN, Yujia LIU, Hui WANG, Zhiyan ZHENG, Tao YU, Jilong WANG

    Published 2021-11-01
    “…To measure the overall impact of different attacks a network region may encounter, an evaluation algorithm can be used to capture the difference in invulnerability of regional network topologies.Specifically, the vulnerability of regional network and that of connection topology between regions both internally and externally was analyzed.To find predictions between regions as supplemental topology data and create the Internet topology, data would be measured in various ways and verified.Using stratified probability sampling, multiple damage simulations could predict the worst-case scenarios in real conditions.Damage was simulated multiple times based on stratified probability sampling to approximate the damage situation of the area under real conditions.A significance tester was realized to measure the impact of damage from the overall level and special weak points respectively, discover the difference of the damage between the areas, and calculate the regional invulnerability ranking.Finally, the ranking and clustering results of forty-eight regions were given.…”
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  18. 16258

    Measuring Respiration Rate from Speech by Sidharth Abrol, Biswajit Das, Srikanth Nallanthighal, Okke Ouweltjes, Ulf Grossekathofer, Aki Härmä

    Published 2025-02-01
    “…We use deep learning models to predict respiratory signals during speech-breathing, from which the respiration rate is estimated. …”
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    Article
  19. 16259

    Research on the invulnerability of regional network based on topology analysis by Changqing AN, Yujia LIU, Hui WANG, Zhiyan ZHENG, Tao YU, Jilong WANG

    Published 2021-11-01
    “…To measure the overall impact of different attacks a network region may encounter, an evaluation algorithm can be used to capture the difference in invulnerability of regional network topologies.Specifically, the vulnerability of regional network and that of connection topology between regions both internally and externally was analyzed.To find predictions between regions as supplemental topology data and create the Internet topology, data would be measured in various ways and verified.Using stratified probability sampling, multiple damage simulations could predict the worst-case scenarios in real conditions.Damage was simulated multiple times based on stratified probability sampling to approximate the damage situation of the area under real conditions.A significance tester was realized to measure the impact of damage from the overall level and special weak points respectively, discover the difference of the damage between the areas, and calculate the regional invulnerability ranking.Finally, the ranking and clustering results of forty-eight regions were given.…”
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    Article
  20. 16260

    Multifactor Stock Selection Strategy Based on Machine Learning: Evidence from China by Jieying Gao, Huan Guo, Xin Xu

    Published 2022-01-01
    “…The main findings are as follows: the support vector regression has the most stable successful rate for predicting, while ridge regression and linear regression have the most unstable successful rate with more extreme cases; algorithm of support vector regression fitting higher-degree polynomials in Chinese A-share market is optimized, compared with the traditional linear regression both in terms of stock return and retracement control; the results of support vector regression significantly outperforming the CSI 500 index prove further.…”
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    Article