Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
- 16 September 2020
- journal article
- research article
- Published by Elsevier BV in Environmental Pollution
- Vol. 268, 115663
- https://doi.org/10.1016/j.envpol.2020.115663
Abstract
No abstract availableKeywords
This publication has 57 references indexed in Scilit:
- SOAPdenovo2: an empirically improved memory-efficient short-read de novo assemblerGigaScience, 2012
- Parameter tuning for configuring and analyzing evolutionary algorithmsSwarm and Evolutionary Computation, 2011
- Integration of pathway knowledge into a reweighted recursive feature elimination approach for risk stratification of cancer patientsBioinformatics, 2010
- The relation between Acid Volatile Sulfides (AVS) and metal accumulation in aquatic invertebrates: Implications of feeding behavior and ecologyEnvironmental Pollution, 2010
- PCA-Based Feature Selection Scheme for Machine Defect ClassificationIEEE Transactions on Instrumentation and Measurement, 2004
- Assessing sediment contamination in estuariesEnvironmental Toxicology and Chemistry, 2001
- Environmental Impacts of Metal Ore Mining and Processing: A ReviewJournal of Environmental Quality, 1997
- Chemical Speciation and Fractionation in Soil and Sediment Heavy Metal Analysis: A ReviewInternational Journal of Environmental Analytical Chemistry, 1995
- Advanced supervised learning in multi-layer perceptrons — From backpropagation to adaptive learning algorithmsComputer Standards & Interfaces, 1994
- Genetic Algorithms: Principles of Natural Selection Applied to ComputationScience, 1993