A method of evaluating swimming pool water quality using backpropagation neural network model
A neural network model and back-propagation technology, which is applied in the field of evaluating swimming pool water quality using back-propagation neural network model, can solve the problems of few and imperfect research on comprehensive water quality evaluation.
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[0044] A method for evaluating the water quality of a swimming pool using a backpropagation neural network model, comprising a. index screening, b. standard selection, c. demarcation grading and d. model fitting, characterized in that: the following steps are followed in order:
[0045] a. Index screening:
[0046] Select the following 7 indicators, and the units in the brackets are the indicators used: ①free residual chlorine (mg / L), ②cyanuric acid (mg / L), ③oxidation-reduction potential (mV), ④pH value, ⑤total alkali degree (mg / L), ⑥ calcium hardness (mg / L) and ⑦ urea (mg / L);
[0047] b. Standard selection: The standard limits of the seven indicators selected in step a from ① to ⑦ are: [0.2,1.0], ≤150, ≥650, [7.0,7.8], [60,200], [200,450] and ≤ 3.5;
[0048] c. Classification: The grading standards for each indicator are shown in Table 1:
[0049] Table 1:
[0050]
[0051]
[0052] d. Model Fitting:
[0053] d.1 Establishment of training samples: the data in the g...
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