基于模糊贝叶斯-ANP舰载机出动回收综合评估

doi:10.12305/j.issn.1001-506X.2022.11.17

Abstract

Abstract:

The aircraft carrier is a typical complex system, the dispatch and recovery efficiency of the carrier aircraft is an important indicator to measure the combat capability of the entire system. Many indicators are involved in describing the efficiency of dispatch recovery, and the relationship between these indicators is complex. In order to determine the relationship between these indicators and avoid the defects of subjective judgment in the evaluation process, this paper proposes an extended Bayesian fusion method based on triangular fuzzy numbers to evaluate the dispatch and recovery efficiency of the carrier aircraft. At the same time, to solve the subjective judgment in the analysis of analytic network process (ANP), the triangular fuzzy number scale standard is adopted, and combined with historical experimental data and expert judgments for comprehensive analysis. In the simulation example, the rationality and validity of the proposed method of using fuzzy numbers and fusion of expert experience and historical experimental data are verified through multiple sets of comparative experiments.

Key words: carrier aircraft, dispatch and recovery efficiency, triangular fuzzy number, extended Bayesian fusion method, fuzzy analytic network process (ANP)

CLC Number:

E917

Jianing DENG, Yu WU, Shuting XU, Jinzhan GOU. Comprehensive evaluation of carrier aircraft's dispatch and recovery based on fuzzy Bayesian-ANP[J]. Systems Engineering and Electronics, 2022, 44(11): 3423-3432.

Figures/Tables 9

Fig.1

Table 1

Fig.2

Table 2

Table 3

Table 4

Table 5

Table 6

Table 7

References 34

1	伍赛特. 航空母舰舰载机技术发展趋势研究[J]. 现代制造技术与装备, 2020, 4, 8- 11.
	WU S T . Research on the development trend of aircraft carrier technology[J]. Modern Manufacturing Technology and Equipment, 2020, 4, 8- 11.
2	DIETZ D C , JENKINS R C . Analysis of aircraft sortie generation with the use of a fork-join queueing network model[J]. Naval Research Logistics, 1997, 44 (2): 153- 164. doi: 10.1002/(SICI)1520-6750(199703)44:2<153::AID-NAV1>3.0.CO;2-8
3	MACKENZIE A , MILLER J O , HILL R R , et al. Application of agent based modelling to aircraft maintenance manning and sortie generation[J]. Simulation Modelling Practice and Theory, 2012, 20 (1): 89- 98. doi: 10.1016/j.simpat.2011.09.001
4	XIA G P , LUAN T T , SUN M X . Evaluation analysis for sortie generation of carrier aircrafts based on nonlinear fuzzy matter-element method[J]. Journal of Intelligent & Fuzzy Systems, 2016, 31 (6): 3055- 3066.
5	WANG X W , LIU J , SU X C , et al. A review on carrier aircraft dispatch path planning and control on deck[J]. Chinese Journal of Aeronautics, 2020, 33 (12): 3039- 3057. doi: 10.1016/j.cja.2020.06.020
6	WU Y, TAN W Q, SUN L G, et al. A decision-making method for landing routes of aircraft on the carrier[C]//Proc. of the MATEC Web of Conferences, 2016, 75: 05002.
7	WU Y , QU X J . Path planning for taxi of carrier aircraft launching[J]. Science China Technological Sciences, 2013, 56 (6): 1561- 1570. doi: 10.1007/s11431-013-5222-5
8	SEBOK A , WICKENS C , SARTER N , et al. The automation design advisor tool (ADAT): development and validation of a model-based tool to support flight deck automation design for nextgen operations[J]. Human Factors and Ergonomics in Ma-nufacturing & Service Industries, 2012, 22 (5): 378- 394.
9	万兵, 韩维, 梁勇, 等. 基于指标函数的舰载机机队回收调度优化研究[J]. 系统工程与电子技术, 2021, 43 (10): 2918- 2930. doi: 10.12305/j.issn.1001-506X.2021.10.27
	WAN B , HAN W , LIANG Y , et al. Research on optimization of carrier-based aircraft fleet recovery scheduling based on index function[J]. Systems Engineering and Electronics, 2021, 43 (10): 2918- 2930. doi: 10.12305/j.issn.1001-506X.2021.10.27
10	SU X C, LI H, ZHANG Y R, et al. Research on landing environment system of carrier-based aircraft[C]//Proc. of the Chinese Control and Decision Conference, 2019: 2747-2750.
11	刘相春, 卢晶, 黄祥钊. 国外航母舰载机出动回收能力指标体系分析[J]. 中国舰船研究, 2011, 6 (4): 1- 7. doi: 10.3969/j.issn.1673-3185.2011.04.001
	LIU X C , LU J , HUANG X Z . Analysis on the index system of sortie generation capacity of embarked aircrafts[J]. Chinese Journal of Ship Research, 2011, 6 (4): 1- 7. doi: 10.3969/j.issn.1673-3185.2011.04.001
12	韩维, 李正阳, 苏析超. 基于改进ANP和可拓理论的航空保障系统效能评估[J]. 兵器装备工程学报, 2019, 40 (8): 100- 105. doi: 10.11809/bqzbgcxb2019.08.021
	HAN W , LI Z Y , SU X C . Effectiveness evaluation of carrier aviation support system based on improved ANP and extension theory[J]. Journal of Ordnance Equipment Engineering, 2019, 40 (8): 100- 105. doi: 10.11809/bqzbgcxb2019.08.021
13	陈小飞, 时立攀, 毕玉泉. 美军航母舰载机出动回收能力和飞行甲板控制策略探讨[J]. 舰船科学技术, 2020, 42 (21): 174- 179.
	CHEN X F , SHI L P , BI Y Q . A discussion on the sortie generation capacity of embarked airwings and the doctrine of flight deck control of U.S. aircraft carrier[J]. Ship Science and Technology, 2020, 42 (21): 174- 179.
14	LIMA J F R , OSIRO L , CARPINETTI L C R . A comparison between fuzzy AHP and fuzzy TOPSIS methods to supplier selection[J]. Applied Soft Computing, 2014, 21, 194- 209. doi: 10.1016/j.asoc.2014.03.014
15	TAVAN A , MADJI D , SOLTANIFA R , et al. Analytical hierarchy process: revolution and evolution[J]. Annals of Operations Research, 2021, 2, 1- 29.
16	XU Z S , LIAO H C . Intuitionistic fuzzy analytic hierarchy process[J]. IEEE Trans.on Fuzzy Systems, 2014, 22 (4): 749- 761. doi: 10.1109/TFUZZ.2013.2272585
17	CHOL Y W, BOK R J, YON Y J, et al. Materials selection criteria weighting method using analytic hierarchy process (AHP) with simplest questionnaire and modifying method of inconsistent pairwise comparison matrix[J]. Proc. of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications, 2022, 236(1): 69-85.
18	ISHIZAKA A , LABIB A . Review of the main developments in the analytic hierarchy process[J]. Expert Systems with Applications, 2011, 38 (11): 14336- 14345.
19	KARRAMAN C , ERTAY T , BUYUKOZKAN G . A fuzzy optimization model for QFD planning process using analytic network approach[J]. European Journal of Operational Research, 2006, 171 (2): 390- 411. doi: 10.1016/j.ejor.2004.09.016
20	SAATY T L . Relative measurement and its generalization in decision making why pairwise comparisons are central in mathematics for the measurement of intangible factors the analytic hierarchy/network process[J]. RACSAM-Revista de la Real Aca-demia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas, 2008, 102 (2): 251- 318. doi: 10.1007/BF03191825
21	LEE J W , KIM S H . Using analytic network process and goal programming for interdependent information system project selection[J]. Computers & Operations Research, 2000, 27 (4): 367- 382. doi: 10.3969/j.issn.1001-4160.2000.04.018
22	王莲芬. 网络分析法(ANP)的理论与算法[J]. 系统工程理论与实践, 2001, 21 (3): 44- 50.
	WANG L F . The theory and algorithm of analytic network process (ANP)[J]. Systems Engineering-Theory & Practice, 2001, 21 (3): 44- 50.
23	MARZIEH M , REZA P H , JAFAR M M . A multi-criteria GIS-based model for wind farm site selection with the least impact on environmental pollution using the OWA-ANP method[J]. Environmental Science and Pollution Research International, 2022, 29, 43891- 43912.
24	WENJUN Z , TAOTAO L , YAO L . Risk assessment of water supply network operation based on ANP-fuzzy comprehensive evaluation method[J]. Journal of Pipeline Systems Engineering and Practice, 2022, 13 (1): 04021068.
25	MISTARIHI M Z , OKOUR R A , MUMANI A A . An integration of a QFD model with fuzzy-ANP approach for determining the importance weights for engineering characteristics of the proposed wheelchair design[J]. Applied Soft Computing, 2020, 90, 106136.
26	ZHANG F , JU Y B , GONZALEZ E D R S , et al. Evaluation of construction and demolition waste utilization schemes under uncertain environment: a fuzzy heterogeneous multi-criteria decision-making approach[J]. Journal of Cleaner Production, 2021, 313, 127907.
27	PANG N S , NAN M F , MENG Q C , et al. Selection of wind turbine based on fuzzy analytic network process: a case study in China[J]. Sustainability, 2021, 13 (4): 1792.
28	DONG J , LIU D R , LIU Y , et al. Trading performance evaluation for traditional power generation group based on an integrated matter-element extension cloud model[J]. Energy Reports, 2021, 7, 3074- 3089.
29	HOU Z Q , ZHAO P . Based on fuzzy Bayesian network of oil wharf handling risk assessment[J]. Mathematical Problems in Engineering, 2016, 2016, 6532691.
30	CHEMWENO P , PINTELON L , VAN HORENBEEK A , et al. Development of a risk assessment selection methodology for asset maintenance decision making: an analytic network process (ANP) approach[J]. International Journal of Production Economics, 2015, 170, 663- 676.
31	SAATY T L , ZHANG L . The need for adding judgment in Bayesian prediction[J]. International Journal of Information Technology & Decision Making, 2016, 15 (4): 733- 761.
32	石福丽, 方志刚, 杨峰, 等. 基于仿真的潜艇装备作战能力ANP幂指数评估方法[J]. 国防科技大学学报, 2011, 33 (4): 168- 174.
	SHI F L , FANG Z G , YANG F , et al. ANP power index evaluation method for operational capability of submarine equipment based on simulation[J]. Journal of National University of Defense Technology, 2011, 33 (4): 168- 174.
33	CHEN C J . Extensions of the TOPSIS for group decision-making under fuzzy environment[J]. Fuzzy Sets and Systems, 2000, 114 (1): 1- 9.
34	CHU T C , LIN Y C . Improved extensions of the TOPSIS for group decisionmaking under fuzzy environment[J]. Journal of Information and Optimization Sciences, 2013, 23 (2): 273- 286.

模糊判断语言变量	三角模糊数
无影响关系或无信心	(0.0, 0.1, 0.3)
影响关系较弱或信心较弱	(0.1, 0.3, 0.5)
影响关系不强或信心不强	(0.3, 0.5, 0.7)
影响关系强或信心强	(0.5, 0.7, 0.9)
影响关系很强或信心很强	(0.7, 0.9, 1.0)

含义	标度	1/标度
两个指标相比同样重要	L1 (1, 1, 1)	V1 (1, 1, 1)
相邻判断的中间值	L2 (1, 2, 3)	V2 (1/3, 1/2, 1)
两个指标相比前者稍微重要	L3 (2, 3, 4)	V3 (1/4, 1/3, 1/2)
相邻判断的中间值	L4 (3, 4, 5)	V4 (1/5, 1/4, 1/3)
两个指标相比前者明显重要	L5 (4, 5, 6)	V5 (1/6, 1/5, 1/4)
相邻判断的中间值	L6 (5, 6, 7)	V6 (1/7, 1/6, 1/5)
两个指标相比前者强烈重要	L7 (6, 7, 8)	V7 (1/8, 1/7, 1/6)
相邻判断的中间值	L8 (7, 8, 9)	V8 (1/9, 1/8, 1/7)
两个指标相比前者极端重要	L9 (9, 9, 9)	V9 (1/9, 1/9, 1/9)

指标	1	2	3
1	(1, 1, 1)	(1, 2, 3)	(2, 3, 4)
2	(1/3, 1/2, 1/1)	(1, 1, 1)	(4, 5, 6)
3	(1/4, 1/3, 1/2)	(1/6, 1/5, 1/4)	(1, 1, 1)

指标集	指标	1				2			…	7
指标集	指标	11	12	13	14	21	22	23	…	73
1	11	0.072 7	0.072 7	0.072 7	0.072 7	0.078 1	0.078 1	0.078 1	…	0.076 8
	12	0.072 7	0.072 7	0.072 7	0.072 7	0.078 1	0.078 1	0.078 1		0.076 8
	13	0.072 7	0.072 7	0.072 7	0.072 7	0.078 1	0.078 1	0.078 1		0.076 8
	14	0.072 7	0.072 7	0.072 7	0.072 7	0.078 1	0.078 1	0.078 1		0.076 8
2	21	0.115 8	0.115 8	0.115 8	0.115 8	0.282 4	0.282 4	0.282 4	…	0.282 3
	22	0.115 8	0.115 8	0.115 8	0.115 8	0.282 4	0.282 4	0.282 4		0.282 3
	23	0.115 8	0.115 8	0.115 8	0.115 8	0.282 4	0.282 4	0.282 4		0.282 3
									
7	73	0.090 5	0.090 5	0.090 5	0.090 5	0.085 7	0.085 7	0.085 7	…	0.081 2

对比项	经典ANP	模糊ANP
尺度标准	准确数字1~9	基于1~9标度改进的三角模糊标度
融合历史实验数据与否	否	是

Comprehensive evaluation of carrier aircraft's dispatch and recovery based on fuzzy Bayesian-ANP

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 9

References 34

Related Articles 15

Recommended Articles

Metrics

Comments

指标号	指标	权重1	排序1	子系统层1	子系统层排序1	权重2	排序2	子层系2统	子排系序统2层
11	飞行甲板停机区面积	0.028 2	11	0.078	7	0.027 6	11	0.078	7
12	机库甲板停机区面积	0.012 4	19			0.013 4	19
13	舰载机尺寸	0.010 4	20			0.010 3	20
14	舰载机可用度	0.026 8	12			0.026 5	12
21	起飞位数量	0.104 8	3	0.253	1	0.110 9	2	0.254	1
22	起飞循环工作周期	0.034 4	10			0.037 0	10
23	波次最大出动能力	0.114 0	2			0.105 9	3
31	波次最大回收舰载机数量	0.064 3	5	0.094	6	0.062 9	5	0.092	6
32	回收间隔时间	0.008 2	21			0.008 4	21
33	拦阻装置的工作周期	0.015 5	18			0.015 0	18
34	复飞率	0.005 8	23			0.005 4	24
41	指挥舰载机最大数量	0.018 6	17	0.244	2	0.019 2	17	0.245	2
42	保障计划决策时间	0.057 0	7			0.058 7	7
43	应急状态调度反应时间	0.145 7	1			0.141 4	1
44	保障监控信息覆盖率	0.022 6	15			0.025 4	15
51	波次最大保障数量	0.070 8	4	0.173	3	0.068 1	4	0.173	3
52	油电气液供给保障能力	0.026 7	13			0.025 9	13
53	保障设备数量	0.053 8	8			0.056 7	8
54	保障工作周期	0.021 5	16			0.022 4	16
61	平均修复性维修时间	0.053 2	9	0.124	4	0.053 9	9	0.124	4
62	设备备件配套率	0.063 2	6			0.062 2	6
63	可完成维修项目比率	0.007 2	22			0.007 5	22
71	人员数量	0.025 6	14	0.035	5	0.025 5	14	0.035	5
72	人员疲劳程度	0.005 2	24			0.005 4	23
73	人员健康状况	0.004 0	25			0.004 4	25

指标号	指标	权重3	排序3	子系统层3	子系统层排序3	权重4	排序4	子层系4统	子排系序统4层
11	飞行甲板停机区面积	0.028 2	11	0.078	7	0.027 4	12	0.078	7
12	机库甲板停机区面积	0.012 4	19			0.012 2	19
13	舰载机尺寸	0.010 4	20			0.010 8	20
14	舰载机可用度	0.026 8	12			0.027 7	11
21	起飞位数量	0.104 8	3	0.253	1	0.103 6	3	0.253	1
22	起飞循环工作周期	0.034 4	10			0.033 1	10
23	波次最大出动能力	0.114 0	2			0.116 6	2
31	波次最大回收舰载机数量	0.064 3	5	0.094	6	0.063 9	6	0.094	6
32	回收间隔时间	0.008 2	21			0.008 3	21
33	拦阻装置的工作周期	0.015 5	18			0.015 6	18
34	复飞率	0.005 8	23			0.006 1	23
41	指挥舰载机最大数量	0.018 6	17	0.244	2	0.018 0	17	0.244	2
42	保障计划决策时间	0.057 0	7			0.056 3	7
43	应急状态调度反应时间	0.145 7	1			0.145 8	1
44	保障监控信息覆盖率	0.022 6	15			0.023 7	15
51	波次最大保障数量	0.070 8	4	0.173	3	0.070 5	4	0.173	3
52	油电气液供给保障能力	0.026 7	13			0.026 7	13
53	保障设备数量	0.053 8	8			0.053 6	8
54	保障工作周期	0.021 5	16			0.022 1	16
61	平均修复性维修时间	0.053 2	9	0.124	4	0.052 2	9	0.123	4
62	设备备件配套率	0.063 2	6			0.064 1	5
63	可完成维修项目比率	0.007 2	22			0.007 2	22
71	人员数量	0.025 6	14	0.035	5	0.025 1	14	0.035	5
72	人员疲劳程度	0.005 2	24			0.005 3	24
73	人员健康状况	0.004 0	25			0.004 2	25

[1]	Bin ZENG, Yuanyuan CHEN, Houpu LI. Launch scheduling optimization considering availability of maintenance equipment for carrier aircraft [J]. Systems Engineering and Electronics, 2021, 43(7): 1856-1865.
[2]	JIANG Dengying, ZHANG Xujun. Multi-attribute group decision-making method with triangular fuzzy numbers based on the TFNCD operator [J]. Systems Engineering and Electronics, 2019, 41(9): 2065-2071.
[3]	YUAN Peilong, HAN Wei, SU Xichao, GAO Shaohui. Predictivereactive dynamic scheduling strategy for carrieraircraft support in uncertain environment [J]. Systems Engineering and Electronics, 2019, 41(6): 1265-1277.
[4]	XIA Guoqing, LUAN Tiantian, SUN Mingxiao, ZHONG Weidong, LIU Yanwen. Reduction and catastrophe progression evaluation method for sortie generation of carrier aircraft [J]. Systems Engineering and Electronics, 2018, 40(2): 330-337.
[5]	TAN XU, WU Junjiang, MAO Taitian, TAN Yuejin. Multi-attribute intelligent decision making method based on triangular fuzzy number hesitant intuitionistic fuzzy sets [J]. Systems Engineering and Electronics, 2017, 39(4): 829-836.
[6]	HUANG Zhi-li, LUO Jian. Similarity programming model for triangular fuzzy number-based uncertain multi-attribute decision making and its application [J]. Systems Engineering and Electronics, 2016, 38(5): 1100-.
[7]	HAN Wei, SU Xi-chao, CHEN Jun-feng. Integrated maintenance support scheduling method of multi carrier aircrafts [J]. Systems Engineering and Electronics, 2015, 37(4): 809-816.
[8]	YUE Kui-zhi, JIA Zhong-hu, JI Jin-zu, SU Min. Numerical simulation on the RCS of carrier based electronic warfare aircraft [J]. Systems Engineering and Electronics, 2014, 36(5): 852-858.
[9]	YUE Kui-zhi, SUN Cong，LUO Ming-qiang, SU Min, ZHAO Hong-chao. Operation model on the carrier warship recovering carrier aircraft [J]. Systems Engineering and Electronics, 2013, 35(12): 2527-2532.
[10]	SUN Shi-quan, GAO Shu-ping, LIANG Yuan, BIAN Jiang. Method of multiple attributive group decision making based on data fusion [J]. Journal of Systems Engineering and Electronics, 2012, 34(10): 2094-2097.
[11]	FENG Qiang, ZENG Sheng-kui, KANG Rui. Multiagent-based modeling method for integrated logistic support of the carrier aircraft [J]. Journal of Systems Engineering and Electronics, 2010, 32(1): 211-216.
[12]	ZHANG Su, CHENG Qi-yue, WANG Ying-long. Coordination efficiency evaluating of air-defense missile composite group [J]. Journal of Systems Engineering and Electronics, 2009, 31(8): 1923-1926.
[13]	WU Shi-hui, YANG Jian-jun, GUO Nai-lin. Study on the optimal strategies solution of triangular fuzzy matrix game [J]. Journal of Systems Engineering and Electronics, 2009, 31(5): 1231-1234.
[14]	WEI Gui-wu. Fuzzy ordered weighted harmonic averaging operator and its application to decision making [J]. Journal of Systems Engineering and Electronics, 2009, 31(4): 855-858.
[15]	LIU Xiu-mei, ZHAO Ke-qin, WANG Chuan-bin. New multiple attribute decision-making model with triangular fuzzy numbers based on connection numbers [J]. Journal of Systems Engineering and Electronics, 2009, 31(10): 2399-2403.