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  1. 1861

    Low‐rank isomap algorithm by Eysan Mehrbani, Mohammad Hossein Kahaei

    Published 2022-07-01
    “…Abstract Isomap is a well‐known nonlinear dimensionality reduction method that highly suffers from computational complexity. …”
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    Article
  2. 1862

    Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale by Harsh Vazirani, Xiaofeng Wu, Anurag Srivastava, Debajyoti Dhar, Divyansh Pathak

    Published 2024-11-01
    “…This combined dataset, named GeoBlendMDWC, was specifically designed for SOC prediction. The primary aim of this research is to develop and evaluate a novel optimization algorithm for accurate SOC prediction by leveraging multi-source environmental data. …”
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    Article
  3. 1863

    A Comparative Study of Hybrid Adaptive Neuro-Fuzzy Inference Systems to Predict the Unconfined Compressive Strength of Rocks by Annabelle Graham, Emma Scott

    Published 2024-06-01
    “…Performance metrics like R2, RMSE, NMSE, MAE, and n_10 index were used to assess the predictive capability of models, indicating that ANAS with maximum and minimum =3.103, has the most optimal prediction performance for practical applications.…”
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    Article
  4. 1864
  5. 1865
  6. 1866

    Extreme high accuracy prediction and design of Fe-C-Cr-Mn-Si steel using machine learning by Hao Wu, Jianyuan Zhang, Jintao Zhang, Chengjie Ge, Lu Ren, Xinkun Suo

    Published 2024-12-01
    “…In this study, a data-driven model combining machine learning (ML), firefly optimization algorithm (FA) and conditional generative adversarial networks (CGANs) were proposed to predict solid solution strengthening theory of Fe-C-Cr-Mn-Si steel. …”
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    Article
  7. 1867

    The Controlling Factors and Prediction of Deep-Water Mass Transport Deposits in the Pliocene Qiongdongnan Basin, South China Sea by Jiawang Ge, Xiaoming Zhao, Qi Fan, Weixin Pang, Chong Yue, Yueyao Chen

    Published 2024-11-01
    “…Our study indicates that a random forest artificial intelligence algorithm could be useful in predicting the susceptibility of deep-water MTDs and can be applied to other study areas to predict and avoid submarine disasters caused by wasting processes.…”
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    Article
  8. 1868
  9. 1869

    A comparative study of hybrid adaptive neuro-fuzzy inference systems to predict the unconfined compressive strength of rocks by Wei Cao

    Published 2025-01-01
    “…However, the inclusion of optimization algorithms significantly improved the performance of the SVR framework. …”
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    Article
  10. 1870
  11. 1871
  12. 1872
  13. 1873
  14. 1874
  15. 1875
  16. 1876

    Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

    Published 2024-12-01
    “…Based on the experimental data of corrosion rates of 3C steel in different seawater environments, an improved Elman neural network model was established by using the whale optimization algorithm. The corrosion rates of 3C steel in different seawater environments were predicted, and the influences of the number of hidden layer nodes, the population sizes, and the number of iterations on the prediction results of the improved model were analyzed. …”
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    Article
  17. 1877
  18. 1878
  19. 1879
  20. 1880