| Literature DB >> 35256874 |
Ziyi Ma1.
Abstract
In this study, a novel microcirculation chromatography with pulsed amperometric discovery (IC/PAD) system is established for the cyanide in business sewage. For business sewage with complicated substrates, the microstrewing means is leveraged for purification and decoration, and subsequently, the IC/PAD course is utilized to psychoanalyze and accuse the cyanide in the match. Under optimum plight, cyanide exhibits some kind of linearity in the frequency of 1.0-200.0 μg/L, and the perception termination and quantification check of cyanide in business sewage are 0.15 μg/L and 0.5 0 μg/L, respectively. The scold is between 88.6% and 1 08.5%. This mode is highly caring, tenacious and awesome, and calm to manage. It offers recent discrimination for the discovery of cyanide in business sewage. In this case, the insincere-frequent uninterrupted inundate analyzer is to decide business sewage with comprehensive distinction in ammonium propellant major. The spring is compared with the mensuration rise of Nessler's test spectrophotometry. The rise has shown that when the double-stroll regularity of extended overflow analyzer is a manner to simultaneously moderate lofty and blaze concentrations of ammonia packaging gas, there is no important contention compared with the mensuration inference of Nessler's test spectrophotometry. The analysis of the regularity has whole reagents, and harmless and strong transformation. This can optimally decrease the effort intenseness of testers and is valuable of preferment. Index Terms-DE oxidation, industrial wastewater, purification, fuzzy control, simulation.Entities:
Mesh:
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Year: 2022 PMID: 35256874 PMCID: PMC8898132 DOI: 10.1155/2022/2843055
Source DB: PubMed Journal: Comput Intell Neurosci
Figure 1The pipeline of our proposed model.
Figure 2An illustration of the fuzzy control.
Figure 3Tendency of the DE oxidation.
Figure 4Flowchart of the waste water treatment plant.
Figure 5Business dismal.
Performance decrement (−)/increment (+) of different algorithms on our adopted dataset.
| Settings | S11 | S12 | S13 | S14 |
|---|---|---|---|---|
| Accuracy (%) | −2.31 | −1.76 | −4.47 | −3.87 |
Performance decrement (−)/increment (+) of different algorithms on [12].
| Settings | S11 | S12 | S13 | S14 |
|---|---|---|---|---|
| Accuracy (%) | −4.36 | −2.65 | −4.11 | −4.32 |
Performance decrement (−)/increment (+) of different algorithms on [7].
| Settings | S11 | S12 | S13 | S14 |
|---|---|---|---|---|
| Accuracy | -3.43% | -1.76% | -5.11% | -3.21% |
Performance decrement (−)/increment (+) of different algorithms on [9].
| Settings | S11 | S12 | S13 | S14 |
|---|---|---|---|---|
| Accuracy (%) | −5.78 | −2.54 | −4.87 | −3.76 |
Accuracy decrement (-)/increment (+) and time cost of different algorithms on our adopted dataset.
| Settings | S21 | S22 | S23 | S24 | Ours |
|---|---|---|---|---|---|
| Accuracy (%) | −13.11 | −15.43 | −4.32 | −7.33 | n/a |
| Time | 43 m 51 s | 17 m 51 s | 9 m 21 s | 5 m 28 s | 4 m 32 s |
Accuracy decrement (−)/increment (+) and time cost of different algorithms on [12].
| Settings | S21 | S22 | S23 | S24 | Ours |
|---|---|---|---|---|---|
| Accuracy (%) | −10.32 | −15.43 | −9.76 | −5.44 | n/a |
| Time | 16 m 7 s | 5 m 21 s | 5 m 32 s | 6 m 15 s | 12 m 3 s |
Accuracy decrement (−)/increment (+) and time cost of different algorithms on [7].
| Settings | S21 | S22 | S23 | S24 | Ours |
|---|---|---|---|---|---|
| Accuracy (%) | −14.63 | −24.31 | −6.71 | −6.43 | n/a |
| Time | 32 m 32 s | 12 m 44 s | 7 m 33 s | 8 m 15 s | 4 m 11 s |
Accuracy decrement (−)/increment (+) and time cost of different algorithms on [9].
| Settings | S21 | S22 | S23 | S24 | Ours |
|---|---|---|---|---|---|
| Accuracy (%) | −12.32 | −15.54 | −7.43 | −5.43 | n/a |
| Time | 14 m 32 s | 7 m 11 s | 6 m 43 s | 4 m 43 s | 4 m 43 s |
The accuracy of image retrieval using different distance measure.
| Distance measure | Accuracy |
|---|---|
| Euclidean distance | 0.6754 |
| Cosine distance | 0.6342 |
| Manhattan distance | 0.7111 |
| Minkowski distance |
|
The bold means the best performer.
The accuracy of image retrieval using different distance measure.
| Distance measure | Accuracy |
|---|---|
| Euclidean distance | 0.5343 |
| Cosine distance | 0.6121 |
| Manhattan distance | 0.8754 |
| Minkowski distance |
|
The bold means the best performer.