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Prediction of dust storms in construction projects using intelligent artificial neural network technology
Sandstorms (dust storms) are considered the most events which cause destructive and costly damages in lots of desert regions. These sandstorms may be a reason of huge disasters (damages) on Environmental as well as Health aspects. The aim of this paper is to develop a mathematical model for predicting the Dust Storm in Republic of Iraq using Artificial Neural Network (ANN) technique. As a case study, four construction projects in Iraqi cities were selected (Baghdad, Basrah, Samawa, and Nasiriya) in order to identifying and prediction of the sandstorms, which significantly help to reduce the effects of damages. Only one ANN model was built to predict a dust storm. The datas of this model cited from Iraqi Meteorological Organization and Seismology. Four factors were adapted to develop the model (Max. Temperature, Min. Temperature, Rain and Wind), It was found that ANN has the ability to predict the dust storm with a high accuracys off the correlation coefficient (R) which is 90.00%, with a percentage of average accuracy is 89%.
Prediction of dust storms in construction projects using intelligent artificial neural network technology
Sandstorms (dust storms) are considered the most events which cause destructive and costly damages in lots of desert regions. These sandstorms may be a reason of huge disasters (damages) on Environmental as well as Health aspects. The aim of this paper is to develop a mathematical model for predicting the Dust Storm in Republic of Iraq using Artificial Neural Network (ANN) technique. As a case study, four construction projects in Iraqi cities were selected (Baghdad, Basrah, Samawa, and Nasiriya) in order to identifying and prediction of the sandstorms, which significantly help to reduce the effects of damages. Only one ANN model was built to predict a dust storm. The datas of this model cited from Iraqi Meteorological Organization and Seismology. Four factors were adapted to develop the model (Max. Temperature, Min. Temperature, Rain and Wind), It was found that ANN has the ability to predict the dust storm with a high accuracys off the correlation coefficient (R) which is 90.00%, with a percentage of average accuracy is 89%.
Prediction of dust storms in construction projects using intelligent artificial neural network technology
Kh. Zamim, Salah (author) / Saad Faraj, Noora (author) / A. Aidan, Ibrahim (author) / M. S. Al-Zwainy, Faiq (author) / A. AbdulQader, Mohammed (author) / A. Mohammed, Ibraheem (author)
2019-12-02
doi:10.21533/pen.v7i4.857
Periodicals of Engineering and Natural Sciences; Vol 7, No 4 (2019); 1659-1666 ; 2303-4521 ; 10.21533/pen.v7i4
Article (Journal)
Electronic Resource
English
Sandstorms , Traning , Iraq , Validation , ANN , Testing , Predicting
DDC:
690
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