Maolin Shi

According to our database1, Maolin Shi authored at least 15 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Modeling and control methods of a multi-parameter system for threshing and cleaning in grain combine harvesters.
Comput. Electron. Agric., 2024

A hierarchical surrogate assisted optimization algorithm using teaching-learning-based optimization and differential evolution for high-dimensional expensive problems.
Appl. Soft Comput., 2024

2022
Efficient reliability analysis using prediction-oriented active sparse polynomial chaos expansion.
Reliab. Eng. Syst. Saf., 2022

A multivariate time series segmentation algorithm for analyzing the operating statuses of tunnel boring machines.
Knowl. Based Syst., 2022

A fuzzy clustering algorithm based on hybrid surrogate model.
J. Intell. Fuzzy Syst., 2022

A Study of Support Vector Regression-Based Fuzzy <i>c</i>-Means Algorithm on Incomplete Data Clustering.
J. Adv. Comput. Intell. Intell. Informatics, 2022

PR-FCM: A polynomial regression-based fuzzy C-means algorithm for attribute-associated data.
Inf. Sci., 2022

Recognition methods of threshing load conditions based on machine learning algorithms.
Comput. Electron. Agric., 2022

2021
Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods.
CoRR, 2021

2020
A fuzzy c-means algorithm based on the relationship among attributes of data and its application in tunnel boring machine.
Knowl. Based Syst., 2020

2019
A fuzzy c-means algorithm guided by attribute correlations and its application in the big data analysis of tunnel boring machine.
Knowl. Based Syst., 2019

A support vector regression-based multi-fidelity surrogate model.
CoRR, 2019

High-low level support vector regression prediction approach (HL-SVR) for data modeling with input parameters of unequal sample sizes.
CoRR, 2019

A Data-Driven Framework for Tunnel Geological-Type Prediction Based on TBM Operating Data.
IEEE Access, 2019

2018
Geology prediction based on operation data of TBM: comparison between deep neural network and statistical learning methods.
CoRR, 2018


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