Zhongmin Liang

发表

Discussion of “Performance Enhancement of a Conceptual Hydrological Model by Integrating Artificial Intelligence” by Ahmet Ali Kumanlioglu and Okan Fistikoglu

Ozgur Kisi, Rana Muhammad Adnan, Zhongmin Liang, 2020 .

A medium-term statistical method for rainfall predication

Zhongmin Liang, Chengtao Zhu, Xiaofan Zeng, 2004 .

A multi-model integration method for monthly streamflow prediction: modified stacking ensemble strategy

Yiming Hu, Dong Wang, Bin Xu, 2020, Journal of Hydroinformatics.

Streamflow forecasting using heuristic machine learning methods

Ozgur Kisi, Rana Muhammad Adnan, Zhongmin Liang, 2020, 2020 2nd International Conference on Computer and Information Sciences (ICCIS).

New Flood Early Warning and Forecasting Method Based on Similarity Theory

Zhongmin Liang, Jun Wang, Bo Hou, 2019, Journal of Hydrologic Engineering.

Toward Improved Probabilistic Predictions for Flood Forecasts Generated Using Deterministic Models

Hoshin Vijai Gupta, Xiaolei Jiang, Hoshin V. Gupta, 2019, Water Resources Research.

Study on GIS-based flood risk map for flood detention area

Ye Shi, Zhongmin Liang, Zhongbo Yu, 2008, Geoinformatics.

A Fatigue Driving Detection Algorithm Based on Support Vector Machine

Zhongmin Liang, 2019 .

Concept of Equivalent Reliability for Estimating the Design Flood under Non-stationary Conditions

Yiming Hu, Vijay P. Singh, Jun Wang, 2018, Water Resources Management.

Application of BP Neural Networks to Testing the Reasonableness of Flood Season Staging

Zhongmin Liang, Yan Guo, Suzhen Hou, 2013, 2013 Sixth International Symposium on Computational Intelligence and Design.

Daily streamflow prediction using optimally pruned extreme learning machine

Ozgur Kisi, Rana Muhammad Adnan, Zhongmin Liang, 2019, Journal of Hydrology.

Comparison of LSSVR, M5RT, NF-GP, and NF-SC Models for Predictions of Hourly Wind Speed and Wind Power Based on Cross-Validation

Ozgur Kisi, Xiaohui Yuan, Rana Muhammad Adnan, 2019, Energies.

Multi-source error correction for flood forecasting based on dynamic system response curve method

Vijay P. Singh, Zhongmin Liang, Binquan Li, 2021 .

Air temperature prediction using different machine learning models

Anurag Malik, Ozgur Kisi, Rana Muhammad Adnan, 2021 .

Using the SPEI to Assess Recent Climate Change in the Yarlung Zangbo River Basin, South Tibet

Kumud Acharya, Zhongmin Liang, Wei Zhou, 2015 .

Evaluation of drought and wetness episodes in a cold region (Northeast China) since 1898 with different drought indices

Kumud Acharya, Zhongmin Liang, Zhongbo Yu, 2014, Natural Hazards.

A data-driven SVR model for long-term runoff prediction and uncertainty analysis based on the Bayesian framework

Jun Wang, Zhongmin Liang, Binquan Li, 2018, Theoretical and Applied Climatology.

Bayesian flood frequency analysis in the light of model and parameter uncertainties

Zhongmin Liang, Binquan Li, Wenjuan Chang, 2012, Stochastic Environmental Research and Risk Assessment.

Regional comprehensive drought disaster risk dynamic evaluation based on projection pursuit clustering

Zhongmin Liang, Wang Lizhen, Yong Zhao, 2018 .

Application of Bayesian Model Averaging Approach to Multimodel Ensemble Hydrologic Forecasting

Dong Wang, Yan Guo, Yu Zhang, 2013 .

Comparison of parameter uncertainty analysis techniques for a TOPMODEL application

Kumud Acharya, Zhongmin Liang, Yingqing He, 2016, Stochastic Environmental Research and Risk Assessment.

A modified rational formula for flood design in small basins

Zhongmin Liang, Zhongbo Yu, Jiapeng Hua, 2003 .

A Stratified Sampling Approach for Improved Sampling from a Calibrated Ensemble Forecast Distribution

Dimitri Solomatine, Min Xu, Zhongmin Liang, 2016 .

Uncertainty analysis of SPI calculation and drought assessment based on the application of Bootstrap

Jun Wang, Zhongmin Liang, Yiming Hu, 2015 .

A modified weighted function method for parameter estimation of Pearson type three distribution

Zhongmin Liang, Zhongbo Yu, Binquan Li, 2014 .