Model for the Assessment of Seawater Environmental Quality Based on Multiobjective Variable Fuzzy Set Theory

Table 3

Comparison of the comprehensive seawater quality evaluation results.

Point; Number	Variable fuzzy evaluation method						Fuzzy comprehensive evaluation	BP neural Network	Fuzzy genetic neural Network
	𝛼=1; 𝑝=1	𝛼=1; 𝑝=2	𝛼=2; 𝑝=1	𝛼=2; 𝑝=2	Average value	Evaluation grade
Q1	1.464	1.593	1.309	1.471	1.46	Between I and II, tending toward I	Grade II	Grade II	Grade II
Q2	1.645	1.894	1.327	1.762	1.66	Between I and II, tending toward II	Grade II	Grade III	Grade III
Q3	1.597	1.761	1.504	1.694	1.64	Between I and II, tending toward II	Grade II	Grade II	Grade II
Q4	1.354	1.427	1.231	1.357	1.34	Between I and II, tending toward I	Grade I	Grade II	Grade I
Q5	1.614	1.823	1.465	1.707	1.65	Between I and II, tending toward II	Grade II	Grade III	Grade III
Q6	1.492	1.705	1.304	1.553	1.51	Between I and II, tending toward II	Grade II	Grade II	Grade II
Q7	1.636	1.802	1.491	1.716	1.66	Between I and II, tending to II	Grade II	Grade II	Grade II
Q8	1.451	1.539	1.370	1.497	1.46	Between I and II, tending toward I	Grade I	Grade II	Grade II
Q9	1.512	1.645	1.399	1.586	1.54	Between I and II, tending toward II	Grade II	Grade II	Grade II
Q10	1.273	1.352	1.124	1.229	1.24	Grade I	Grade I	Grade I	Grade I
Q11	1.402	1.507	1.309	1.510	1.43	Between I and II, tending toward I	Grade I	Grade II	Grade II
Q12	1.463	1.611	1.348	1.538	1.49	Between I and II, tending toward I	Grade I	Grade II	Grade II
Q13	1.476	1.552	1.453	1.602	1.52	Between I and II, tending toward II	Grade I	Grade II	Grade II
Q14	1.421	1.529	1.346	1.557	1.46	Between I and II, tending toward I	Grade I	Grade II	Grade II