Update README.md

Author: papari1123

README.md

@@ -22,8 +22,8 @@ Pandas, Nummpy, Keras, Tensorflow
 
 ## 4.Model
 <p align="center">
-<img src="image/모델.png" width= 500, height = 720>
-</p>
+<img src="image/모델.png" width= 500, height = 720></p>
+
 ## 5.Code
 ### Pre-processing
 
@@ -32,16 +32,16 @@ Pandas, Nummpy, Keras, Tensorflow
 ## 6.Result
 This is an prediction example of one area in Korea divided 8x10 grid. <br/>
 <p align="center">
-**next 1hour<br/>**
+ next 1hour<br/>
 <img src="image/R1.png"><br/>
-**next 4hour<br/>**
+<center>next 4hour</center><br/>
 <img src="image/R4.png"><br/>
-**next 12hour<br/>**
+<center>next 12hour</center><br/>
 <img src="image/R12.png"><br/>
-**next 24hour<br/>**
+<center>next 24hour</center><br/>
 <img src="image/R24.png"><br/>
-<br/>
 </p>
+
 ## 7.Recommanded paper to follow this research
 1. Li, X., Peng, L., Yao, X., Cui, S., Hu, Y., You, C., & Chi, T. (2017). Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation. Environmental Pollution, 231, 997–1004.
 2. Huang, C. J., & Kuo, P. H. (2018). A deep cnn-lstm model for particulate matter (Pm2.5) forecasting in smart cities. Sensors (Switzerland), 18(7).