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  1. 1681

    RACH Traffic Prediction in Massive Machine Type Communications by Hossein Mehri, Hani Mehrpouyan, Hao Chen

    Published 2025-01-01
    “…Furthermore, we develop a new low-complexity online prediction algorithm that updates the states of the LSTM network by leveraging frequently collected data from the mMTC network. …”
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    Article
  2. 1682

    Domain Adaptation for Pedestrian Detection Based on Prediction Consistency by Yu Li-ping, Tang Huan-ling, An Zhi-yong

    Published 2014-01-01
    “…Our approach combines the boosting-based learning algorithm with an entropy-based transferability, which is derived from the prediction consistency with the source classifications, to selectively choose the samples showing positive transferability in source domains to the target domain. …”
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    Article
  3. 1683

    Prediction and evaluation of residual life of casing with corrosion defects by JIA Aoyin, QIAN Liqin, WANG Jie, YANG Jingwei, WU Yaokun, WEI Mingji

    Published 2024-01-01
    “…The particle swarm optimization-gaussian process regression (PSO-GPR) algorithm was employed to construct a predictive model for casing corrosion rates.ResultsIntegration of the two models, the evaluation of the residual life of casings with corrosion defects was completed, it has theoretical guidance significance for the prevention and management of corroded casings in oil field operations.…”
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    Article
  4. 1684

    Residual Lifetime Prediction with Multistage Stochastic Degradation for Equipment by Zhan Gao, Qi-guo Hu, Xiang-yang Xu

    Published 2020-01-01
    “…Residual useful lifetime (RUL) prediction plays a key role of failure prediction and health management (PHM) in equipment. …”
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    Article
  5. 1685

    Personalized glucose prediction using in situ data only by Rohan Singh, Marouane Toumi, Marcel Salathé

    Published 2025-06-01
    “…Here, we show that a machine learning algorithm with such real-world data (RWD) collected from a digital cohort with over 1,000 participants can achieve high accuracy in PPGR prediction. …”
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    Article
  6. 1686

    Enhancing Relationship Link Prediction With Hierarchical Feature Enhancement by Zhouying Xu, Huiyue Wang

    Published 2024-01-01
    “…In this study, we endeavor to assess the potential for establishing friendships between users, a challenge that intersects with the domains of friend recommendation and link prediction. Notably, prevailing models in friend recommendation predominantly consider only the attributes of users, whereas link prediction models primarily emphasize network structure. …”
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    Article
  7. 1687

    Discrimination Analysis for Predicting Defect-Prone Software Modules by Ying Ma, Ke Qin, Shunzhi Zhu

    Published 2014-01-01
    “…By combating these two problems, we propose an algorithm based on kernel discrimination analysis called KDC to build more effective prediction model. …”
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    Article
  8. 1688

    Agricultural big data for predicting crop water demand by Zhongbo Liu, Guillermo Palacios-Navarro, Raquel Lacuesta

    Published 2025-12-01
    “…And using K-MEANS, KNN, Random Forest algorithm to mine the generated big data, and finally scientifically predict the water demand for crop growth in agricultural tomato greenhouses at 25–35° angles in Ningxia, China, the results show that the research results effectively predict the water demand of crops in this type of agricultural greenhouses in the region, and provide a reference to the prediction of water demand for other crops in the similar greenhouses in the region, as well as to the Water saving prediction of crops in agricultural greenhouses in the region, rational planning of water resource utilization, and development of scientific and reasonable irrigation system for agricultural greenhouses are all important references.…”
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    Article
  9. 1689

    Leveraging haplotype information in heritability estimation and polygenic prediction by Jonas Meisner, Michael Eriksen Benros, Simon Rasmussen

    Published 2025-01-01
    “…We introduce a framework, named hapla, with a novel algorithm for clustering haplotypes in phased genotype data to estimate heritability and perform reference-free polygenic prediction in complex traits. …”
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    Article
  10. 1690

    Using artificial intelligence tools to predict and alleviate poverty by Ghada Alturif, Wafaa Saleh, Alaa A. El-Bary, Radwa Ahmed Osman

    Published 2024-12-01
    “…A one-dimensional Convolutional Neural Network (1D-CNN) is used in the model to examine and extract patterns from historical socio-economic data from 2000 to 2022. The algorithm uses deep learning techniques to efficiently extract temporal correlations from the data, allowing for accurate predictions of each country's progress towards ending poverty and raising living standards. …”
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    Article
  11. 1691

    Enhancing molecular property prediction with quantized GNN models by Areen Rasool, Jamshaid Ul Rahman, Rongin Uwitije

    Published 2025-05-01
    “…This paper presents a systematic approach to molecular networks by integrating GNN models with the DoReFa-Net quantization algorithm. The proposed method aims to enhance computational efficiency while maintaining predictive performance, enabling lightweight yet effective models suitable for molecular task. …”
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    Article
  12. 1692

    Research on rock burst prediction based on an integrated model by Junming Zhang, Qiyuan Xia, Hai Wu, Sailei Wei, Zhen Hu, Bing Du, Yuejing Yang, Huaixing Xiong

    Published 2025-05-01
    “…This study proposes a rockburst risk prediction method based on the SSA-CNN-MoLSTM-Attention model. …”
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    Article
  13. 1693

    Software pipeline for predicting and analyzing the structure of the receptor–ligand by A.S. Kozlova, A.R. Mukhametgalieva, A.N. Fattakhova, N.I. Akberova

    Published 2022-03-01
    “…Such a pipeline involves a complex algorithm, from predicting the structure of the receptor to searching and analyzing the interaction of ligands with the receptor. …”
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  14. 1694

    Overlap matrix completion for predicting drug-associated indications. by Mengyun Yang, Huimin Luo, Yaohang Li, Fang-Xiang Wu, Jianxin Wang

    Published 2019-12-01
    “…We then propose the OMC2 algorithm to fill out the values of the missing entries in these two adjacency matrices, and predict the scores of unknown drug-disease pairs. …”
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    Article
  15. 1695

    Naive Bayes Analysis for Nutritional Fulfillment Prediction in Children by Satrio Agung Wicaksono, Satrio Hadi Wijoyo, Fatmawati Fatmawati, Tri Afirianto, Diva Kurnianingtyas, Mochammad Chandra Saputra

    Published 2025-06-01
    “…Addressing this issue requires an effective approach to predicting and preventing inadequate nutritional fulfillment. …”
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  16. 1696

    Review of Research on Trajectory Prediction of Road Pedestrian Behavior by YANG Zhiyong, GUO Jieru, GUO Zihang, ZHANG Ruixiang, ZHOU Yu

    Published 2025-05-01
    “…This paper also reviews commonly used datasets and evaluation metrics in the field, providing a thorough evaluation of current algorithmic performance. Finally, it addresses the challenges in pedestrian trajectory prediction for autonomous driving, particularly the dynamic coupling between pedestrians with multi-directional traffic and infrastructure, offering potential solutions and discussing future research directions.…”
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    Article
  17. 1697

    EFFICIENCY OF RAW GLUTEN CONTENT PREDICTION IN WHEAT KERNELS by A. V. Pasynkov, E. N. Pasynkova

    Published 2019-09-01
    “…There have been developed and presented an algorithm and results of testing the predictive capabilities of the equation based on independent data. …”
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  18. 1698

    Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

    Published 2024-04-01
    “…Software defect prediction (SDP) is used to identify defects in software modules that can be a challenge in software development. …”
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  19. 1699

    Correlation and Prediction Analysis of Cyanobacteria with Water Environment Data by Sang-Leen Yun

    Published 2024-12-01
    “…Furthermore, cyanobacteria occurrence was predicted using a random forest algorithm, with a linear regression model serving as a baseline for comparison. …”
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    Article
  20. 1700

    Method and application of stability prediction model for rock slope by Yun Qi, Chenhao Bai, Xuping Li, Hongfei Duan, Wei Wang, Qingjie Qi

    Published 2025-05-01
    “…To accurately and efficiently predict the stability state of slopes, we propose a combined model that integrates the Newton–Raphson optimization algorithm (NRBO) with an optimized extreme gradient boosting tree (XGBoost). …”
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