Parameter identification of smart float diving model based on ASNLS algorithm

Table 1. Specifications of the smart float
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Table 1. Specifications of the smart float
参数数值
质量（非下水状态）/kg 170.6
壳体直径/m 0.301
壳体长度/m 3.55
最大工作水深/m 4000
泵油速率/(mL·s⁻¹) 0.66～0.69
最大泵油量/mL 3 300

Table 2. Model parameter identification values

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Table 2. Model parameter identification values

参数	参数辨识值
参数	ASNLS	CLS	LS	SVM
(${D_{1 {\textit{z} } } }/{M_{\textit{z} } }$)/m−1	$ 4.4 \times {10^{ - 3}} $	$ 4.7 \times {10^{ - 3}} $	$1.9 \times {10^{ - 2}}$	$ 5.2 \times {10^{ - 2}} $
(${N_3}/{M_{\textit{z}}}$)/(m−2·s)	$ - 4.9 \times {10^{ - 10}} $	$ - 1.1 \times {10^{ - 9}} $	$ - 5.8 \times {10^{ - 10}}$	$ - 7.4 \times {10^{ - 10}}$
($ {N_2}/{M_{\textit{z}}} $)/(m−2·s−2)	$ 9.2 \times {10^{ - 4}} $	$ 9.3 \times {10^{ - 4}} $	$1.3 \times {10^{ - 3}}$	$9.4 \times {10^{ - 4}}$
(${N_1}/{M_{\textit{z}}}$)/(m−2·s−1)	$ 1.3 \times {10^{ - 6}} $	$ 1.9 \times {10^{ - 6}} $	$5.5 \times {10^{ - 6}}$	$1.9 \times {10^{ - 6}}$

Table 3. Depth inversion and prediction results

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Table 3. Depth inversion and prediction results

深度样本	指标	量化结果
深度样本	指标	ASNLS	CLS	SVM	LS
600 m级别（反演）	MAE /m	25.37	30.23	58.57	100.20
	RMSE /m	37.99	39.13	68.98	110.58
	MAPE /%	4.228	5.038	9.762	16.370
1 000 m级别（预测）	MAE /m	19.71	23.29	95.43	100.04
	RMSE /m	23.81	29.44	109.23	118.04
	MAPE /%	1.971	2.329	9.543	10.004
2 000 m级别（预测）	MAE /m	179.62	184.07	228.32	349.73
	RMSE /m	206.90	210.38	284.05	384.83
	MAPE /%	8.981	9.204	11.416	17.487

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Yiming ZHONG, Caoyang YU, Junjun CAO, Baoheng YAO, Lian LIAN. Parameter identification of smart float diving model based on ASNLS algorithm[J]. Chinese Journal of Ship Research, 2024, 19(2): 13

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