Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System

作     者：BILAL Ahmed Khan HASEEB ur Rehman QAISAR Nadeem MUHAMMAD Ahmad Naveed Qureshi JAWARIA Ahad MUHAMMAD Naveed Akhtar AMJAD Farooq MASROOR Ahmad BILAL Ahmed Khan;HASEEB ur Rehman;QAISAR Nadeem;MUHAMMAD Ahmad Naveed Qureshi;JAWARIA Ahad;MUHAMMAD Naveed Akhtar;AMJAD Farooq;MASROOR Ahmad

作者机构：Pakistan Institute of Engineering and Applied SciencesIslamabad 44000Pakistan 

出 版 物：《原子能科学技术》 (Atomic Energy Science and Technology)

年 卷 期：2024年第58卷第10期

页      面：2068-2076页

核心收录：

学科分类：082704[工学-辐射防护及环境保护] 08[工学] 0827[工学-核科学与技术] 

主　　题：prediction of meteorological parameters weather research and forecasting model artificial neural networks nuclear emergency support system 

摘      要：This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) *** meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support *** of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and ***,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological *** evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South *** performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological *** show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single ***,accuracy is slightly compromised when predicting wind speed *** mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of *** conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.