Research Article

Mathematical Model Based on BP Neural Network Algorithm for the Deflection Identification of Storage Tank and Calibration of Tank Capacity Chart

Table 1

Testing data and result of model one.

Site 1Site 2
OH/mmAOR/LTOR/LIOR/LIEROH/mmAOR/LTOR/LIOR/LIER

159.02312.00322.88 313.46 0.47%486.891512.001564.74 1511.08 0.06%
176.14362.00374.63 362.90 0.25%498.951562.001616.49 1561.20 0.05%
192.59412.00426.36 412.41 0.10%510.971612.001668.24 1611.33 0.04%
208.50462.00478.13 462.03 0.01%522.951662.001719.98 1661.46 0.03%
223.93512.00529.85 511.67 0.06%534.901712.001771.73 1711.59 0.02%
238.97562.003581.61 561.39 0.11%546.821762.001823.46 1761.71 0.02%
253.66612.00633.35 611.16 0.14%558.721812.001875.19 1811.84 0.01%
268.04662.00685.08 660.95 0.16%570.611862.001926.95 1862.00 0.00%
282.16712.00736.85 710.81 0.17%582.481912.001978.68 1912.12 0.01%
296.03762.00788.58 760.67 0.17%594.351962.002030.43 1962.27 0.01%
309.69812.00840.33 810.58 0.18%606.222012.002082.20 2012.44 0.02%
323.15862.00892.06 860.49 0.18%618.092062.002133.95 2062.59 0.03%
336.44912.00943.80 910.44 0.17%629.962112.002185.67 2112.71 0.03%
349.57962.00995.54 960.41 0.17%641.852162.002237.43 2162.86 0.04%
362.561012.001047.30 1010.41 0.16%653.752212.002289.16 2212.99 0.04%
375.421062.001099.05 1060.43 0.15%665.672262.002340.89 2263.10 0.05%
388.161112.001150.81 1110.47 0.14%677.632312.002392.67 2313.27 0.06%
400.791162.001202.55 1160.51 0.13%678.542315.832396.61 2317.09 0.05%
413.321212.001254.29 1210.56 0.12%690.532365.832448.37 2367.23 0.06%
425.761262.001306.03 1260.62 0.11%690.822367.062449.62 2368.45 0.06%
438.121312.001357.77 1310.69 0.10%702.852417.062501.40 2418.60 0.06%
450.401362.001409.49 1360.75 0.09%714.912467.062553.11 2468.69 0.07%
462.621412.001461.24 1410.85 0.08%727.032517.062604.88 2518.82 0.07%
474.781462.001512.98 1460.95 0.07%739.192567.062656.59 2568.89 0.07%

Where OH, AOR, TOR, IOR, and IER are, respectively, oil height, actual oil reserve, theoretical oil reserve, improved oil reserve, and improved error ratio.