COVID 19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduced forecasting procedures into Artificial Neural Network models compared with regression model. Data collected from Al Kindy Teaching Hospital from the period of 28/5/2019 to 28/7/2019 show an energetic part in forecasting. Forecasting of a disease can be done founded on several parameters such as the age, gender, number of daily infections, number of patient with other disease and number of death. Though, forecasting procedures arise with their private data of tests. This study chats these tests and also offers a set of commendations for the persons who are presently hostile the global COVID 19 disease.
翻译:COVID 19是全世界170多个国家的疾病,在全世界170多个国家中,受感染者(生病或死亡)的人数一直在以令人担忧的比例增长,几乎在所有受影响的国家中,受感染者的人数都在以令人担忧的比例增长。预测程序可以指导如何帮助规划良好的计划和激发创造性的结论。这些程序测量了以前的状况,从而可以对今后可能出现的压力和意义作出良好的预测。这些预测的强度有助于使可能的压力和意义发生矛盾。预测程序产生了弹性精确预测的一个非常主要的特点。在这个案例研究中,使用两种模型来比较产出,以诊断最佳的方法。这项研究将预测程序引入人工神经网络模型,与回归模型相比较。从19年5月28日至20年7月28日从Al Kindy教学医院收集的数据在预测中显示了积极的一面。对疾病进行预测可以基于诸如年龄、性别、每日感染人数、患其他疾病的病人人数和死亡人数等若干参数。不过,预测程序产生于他们的私人测试数据。这项研究与这些测试进行了交谈,并为目前属于敌对性COVI的人提供了一套推荐。