Air pollution has increased dramatically in the world, and Iraq is one of those countries where air pollution has increased due to the increase in the number of cars, trucks, factories, and electric generators. The mean objective of this research is to focuses for design and executes monitoring system to measure and determine the level of pollution in the stations of the Iraqi environment especially in the Baghdad city and determine the places that are more pollution in Baghdad. This study is first and a new application in the field of e-government by using these information be used to inform government agencies associated with the environment to take measures and try to reduce the level of pollution in areas with high pollution. This research introduces a novel approach by using Machine Learning Techniques with the Agent in order to offer Intelligent Environmental System called (MPSAS) for Monitoring Pollution System based on Agent System. Also, in this paper implement the Random Forest algorithm and Naïve algorithm with reinforcement learning is a novel learning not to be use before. The results showed that the accuracy rate of Naïve and Random Forest algorithm gradually increasing when using the reinforcement learning with various large scale data.
Volume 12 | 08-Special Issue
Pages: 898-910
DOI: 10.5373/JARDCS/V12SP8/20202594