Formula decision-making method for regulating water quality
A decision-making method and formula technology, applied in data processing applications, general water supply saving, special data processing applications, etc., can solve problems such as inability to effectively provide pharmaceutical formula processing or monitor system stability, avoid abnormalities or damage, and improve stability. sexual effect
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specific example 1 to 4
[0042] [Table 1]
[0043]
[0044]
[0045] Taking specific example 1 as an example, when the chromaticity removal rate 78 is input as the expected water quality parameter change value, two kinds of formula data will be generated by using the formula decision model, and each formula data includes component composition and component ratio.
specific example I to I
[0046] It is also worth mentioning that the formula decision model can not only carry out the process as in step 22, but also obtain the predicted water quality parameter change values according to the formula data to be used, such as the specific examples I to IV in Table 2 below:
[0047] [Table 2]
[0048]
[0049] Taking specific example I as an example, when the input composition is A drug and B drug, and the ingredient ratio is 154:24.7, the formula decision model can be used to obtain the predicted change value of water quality parameters, that is, the color removal rate is 82.60577.
[0050] In the step 23 , the water quality treatment device 2 regulates the water quality according to a target formula data in the at least one predicted formula data generated in the step 22 , so as to obtain a prepared water quality. It is worth mentioning that, in this embodiment, the determination of the target formula data can be selected by a user or randomly selected. In addi...
specific example 5 to 8
[0058] The step 32 is similar to the step 22 of the above-mentioned embodiment 1, except that each predicted formula data includes a predicted component composition, a predicted component ratio and a predicted formula cost of the formula. The implementation of this step 32 is for example but not limited to specific examples 5 to 8 of the following table 3: [Table 3]
[0059]
[0060]
[0061] The step 33 is to select a pair of target formula data corresponding to the least predicted formula cost from the at least one predicted formula data. The specific examples 5 to 8 in the above table 3 are selected as examples, and the implementation of the step 33 is such as but not limited to the specific examples 5 to 8 in the following table 4:
[0062] [Table 4]
[0063]
[0064] This step 34 is similar to the step 23 of the above-mentioned embodiment 1, the difference is that: this step 34 is to regulate and control the water quality according to the target formula data.
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