Aquaculture Prediction Model Based on Improved Water Quality Parameter Data Prediction Algorithm under the Background of Big Data

Table 1

Initial monitoring data of aquaculture water quality.

Data collection time	Water temperature (°C)	Air temperature (°C)	Illuminance (w.m^2)	Humidity (RH%)	pH	Wind value	Ammonia nitrogen concentration (mg.l)
1 day	Twenty-one	Twenty-two	1251.65	65.45	7.05	2	3.58
2 days	17	20	1345.54	75.45	6.97	2	3.78
3 days	19	Twenty-one	1054.54	68.54	6.45	2	3.89
4 days	Twenty-one	25	1454.56	61.54	6.79	2	3.85
5 days	17	Twenty-one	954.14	73.54	7.06	3	4.15
6 days	18	Twenty-two	1254.52	76.45	6.87	2	4.15
7 days	17	Twenty-three	1354.45	72.45	6.78	2	3.45
8 days	18	Twenty-four	1385.54	64.56	6.65	4	3.56
9 days	19	Twenty-one	1256.54	67.54	6.67	1	3.54
10 days	19	20	1156.5 2	78.54	6.87	2	3.45
11 days	20	Twenty-one	1005.54	76.45	6.79	2	3.75
12 days	Twenty-one	Twenty-two	1234.54	71.54	6.97	3	3.56