Zhi-bin He
Environmental Engineering · 2014–2018
A researcher in the Science corpus: 4 papers; trusts 5 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Environmental Engineering — 37 citations into it; #5,323 of 5,479 by trust here, #1,912 by citations
- Global and Planetary Change — 28 citations into it; #9,796 of 10,225 by trust here, #4,400 by citations
- Water Science and Technology — 25 citations into it; #1,632 of 1,711 by trust here, #676 by citations
- Artificial Intelligence — 21 citations into it
- Electrical and Electronic Engineering — 12 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
Whom Zhi-bin He trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Zhi-bin He overall
- Xiaohu Wen
- Zhenliang Yin
- Quoc Bao Pham
- Zhongmin Liang
- Ebrahim Sharifi Garmdareh
- Jianhua Si
- Zaher Mundher Yaseen
- Ozgur Kisi
- Behrooz Keshtegar
- Qi Feng
Papers from Zhi-bin He's perspective
Ordered by how strongly the researchers Zhi-bin He trusts endorse each paper. Same corpus, a different order for every researcher.
- The Nature of Statistical Learning Theory
- Model Induction with Support Vector Machines: Introduction and Applications
- Predicting Time Series with Support Vector Machines
- Two hybrid Artificial Intelligence approaches for modeling rainfall–runoff process
- Artificial intelligence based models for stream-flow forecasting: 2000-2015
- A wavelet-support vector machine conjunction model for monthly streamflow forecasting
- Learning With Continuous Classes
- Forecasting Evaporative Loss by Least-Square Support-Vector Regression and Evaluation with Genetic Programming, Gaussian Process, and Minimax Probability Machine Regression: Case Study of Brisbane…
- Wavelet support vector machine (IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics))
- Pan evaporation modeling using least square support vector machine, multivariate adaptive regression splines and M5 model tree
Their papers
- Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment (2018) — 54 citations
- Integrating genetic algorithm and support vector machine for modeling daily reference evapotranspiration in a semi-arid mountain area (2017) — 64 citations
- Support-Vector-Machine-Based Models for Modeling Daily Reference Evapotranspiration With Limited Climatic Data in Extreme Arid Regions (2015) — 146 citations
- A comparative study of artificial neural network, adaptive neuro fuzzy inference system and support vector machine for forecasting river flow in the semiarid mountain region (2014) — 330 citations