M. J. Alam
Environmental Engineering · 2017
A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Environmental Engineering — 7 citations into it; #4,105 of 5,479 by trust here, #5,399 by citations
- Global and Planetary Change — 7 citations into it; #7,197 of 10,225 by trust here, #10,129 by citations
- Artificial Intelligence — 6 citations into it
- Electrical and Electronic Engineering — 6 citations into it; #11,946 of 16,539 by trust here, #16,387 by citations
Whom M. J. Alam trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts M. J. Alam overall
Papers from M. J. Alam's perspective
Ordered by how strongly the researchers M. J. Alam trusts endorse each paper. Same corpus, a different order for every researcher.
- The Mann-Kendall Test Modified by Effective Sample Size to Detect Trend in Serially Correlated Hydrological Series
- A combined neural-wavelet model for prediction of Ligvanchai watershed precipitation (Engineering applications of artificial intelligence)
- Wavelet support vector machine (IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics))
- Wavelet Methods for Time Series Analysis
- Wavelet Methods for Time Series Analysis
- Groundwater level forecasting using artificial neural networks
- Feature extraction via multiresolution analysis for short-term load forecasting (IEEE Transactions on Power Systems)
- Trend Analysis in Reference Evapotranspiration Using Mann-Kendall and Spearman’s Rho Tests in Arid Regions of Iran (Water resources management)
- Trend detection in hydrologic data: The Mann–Kendall trend test under the scaling hypothesis
- Power of the Mann–Kendall and Spearman's rho tests for detecting monotonic trends in hydrological series