A. Pham
Civil and Structural Engineering · 2013–2020
A researcher in the Science corpus: 3 papers; trusts 19 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Civil and Structural Engineering — 33 citations into it; #1,813 of 6,160 by trust here, #2,398 by citations
- Building and Construction — 13 citations into it
- Artificial Intelligence — 11 citations into it
- Algorithms & Complexity — 6 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it
- Evaluation & Benchmarks — 5 citations into it
- Information Systems — 5 citations into it
- Statistics and Probability — 5 citations into it
Whom A. Pham trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- I-Cheng Yeh
- Jui-Sheng Chou
- Vladimir Naumovich Vapni
- Niko Speybroeck
- Wei-Yin Loh
- Alex Smola
- Ilker Bekir Topcu
- B. Prasad
- Muhammad Fauzi Mohd. Zain
- S. Tiryaki
Who trusts A. Pham overall
Papers from A. Pham's perspective
Ordered by how strongly the researchers A. Pham trusts endorse each paper. Same corpus, a different order for every researcher.
- Modeling of strength of high-performance concrete using artificial neural networks
- A tutorial on support vector regression
- Ensemble based systems in decision making
- Classification and regression trees
- Prediction of elastic modulus of normal and high strength concrete by support vector machine
- Estimation of exposed temperature for fire-damaged concrete using support vector machine
- Concrete compressive strength analysis using a combined classification and regression technique
- An artificial neural network model for predicting compression strength of heat treated woods and comparison with a multiple linear regression model
- Linear Regression Analysis: Theory and Computing
- Multiple regression model for compressive strength prediction of high performance concrete
Their papers
- Predicting energy consumption in multiple buildings using machine learning for improving energy efficiency and sustainability (2020) — 349 citations
- Machine learning in concrete strength simulations: Multi-nation data analytics (2014) — 439 citations
- Enhanced artificial intelligence for ensemble approach to predicting high performance concrete compressive strength (2013) — 344 citations