%0 Journal Article
%T Prediction of Environmental Health by Using Gene Expression and Bayesian Network Techniques in Taleghan Watershed
%J Journal of Range and Watershed Managment
%I دانشکده منابع طبیعی دانشگاه تهران
%Z 5044-2008
%A ebrahimi, payam
%A Salajegheh, Ali
%A Mohseni Saravi, Mohsen
%A Malekian, Arash
%A Sadoddin, Amir
%D 2020
%\ 05/21/2020
%V 73
%N 1
%P 1-18
%! Prediction of Environmental Health by Using Gene Expression and Bayesian Network Techniques in Taleghan Watershed
%K Watershed Health
%K Taleghan
%K gene expression
%K Bayesian network
%R 10.22059/jrwm.2018.250908.1221
%X One of the important criteria for quality of life is the health of the watershed. Researches in this field show that in Iran, a model for assessing the health of the watershed is not prepared. So, In this study, using the statistical data of 27 years (1990-2016) 5 environmental variables in the Taleghan watershed in the province of Alborz is estimated using gene expression and Bayesian network techniques. By using the gene expression programming and the Bayesian network of each variable, the years from 1991 to 2006 selected as a training data and 2006 to 2014 as test data, and from 2014 to 2016 selected as validation period (predictive accuracy). In comparison, the estimation accuracy of the gene expression and Bayesian network, the mean correlation values of 5 variables are 0.87 and 0.78, respectively. In the case of the gene expression model, the values of the coefficient of determination in the training section were: 0.87 for discharge, sediment, 0.92, precipitation, 89.9, temperature 0.91 and evaporation 0.77, and also in the Bayesian network, the values were 0.73, 0.88, 0.78, 0.71 and 0.81. The amount of gene expression scheduling will have a high power in simulating future values, given the generation of a generation of 200,000 times. The results of this study indicate that the health state of the watershed with a score of 8 in 2016 has advanced cancer status, and according to the results of the model in 2017, it can be in the recurrence of cancer.
%U https://jrwm.ut.ac.ir/article_76835_251fa27aa238c2bc3c7c60c8d3affa4f.pdf