Journal
PETROLEUM SCIENCE AND TECHNOLOGY
Volume 37, Issue 24, Pages 2364-2373Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/10916466.2018.1542439
Keywords
anthropogenic; Caspian Sea; feed forward artificial neural; organic pollutants; particle swarm optimization
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In this paper an intelligent model is proposed to predict the amount of organic pollutants in Caspian Sea sediment based on a feed forward artificial neural network (ANN) optimized by particle swarm optimization (PSO) algorithm. Organic pollutants have carcinogenesis and mutagenesis properties which are derived from anthropogenic and natural sources. The PSO-ANN was developed by experimental data collected from different literature. The statistical parameters prove the satisfactory performance of the proposed PSO- ANN model. A good correlation was obtained between the predicted organic pollutants and the experimental data for test, train and validation data were 0.996, 0.997, 0.993, respectively.
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