TY - GEN
T1 - HUMAN-MACHINE FUNCTION ALLOCATION METHOD FOR SINGLE PILOT OPERATION USING HESITANT FUZZY 2-TUPLE LINGUISTIC INFORMATION
AU - Bi, Wenhao
AU - Liu, Yuhui
AU - Wang, Weixiang
AU - Zhang, An
N1 - Publisher Copyright:
© 2022 ICAS. All Rights Reserved.
PY - 2022
Y1 - 2022
N2 - Single pilot operation(SPO) is the key technology for the next generation operation of the future commercial aircraft. It consists of single pilot in the cockpit, advanced onboard automation and ground airline operator. In order to make the overall system efficient, safe, reliable and economic, human-machine function allocation for single-pilot operation should comprehensively consider various factors. Thus, the human-machine function allocation can be viewed as a typical multiple attribute group decision making (MAGDM) problem under uncertainty and ambiguity. To this end, this paper introduces a human-machine function allocation method based on hesitant fuzzy 2-tuple linguistic information. Firstly, the prioritized weighted hesitant fuzzy 2-tuple linguistic Bonferroni mean (PWHF2TLBM) operator is defined. Then the human-machine function allocation method is proposed, where the evaluations of experts are presented in the form of hesitant fuzzy 2-tuple linguistic information, and the PWHF2TLBM operator is used to aggregate the evaluations of different attributes. Finally, an illustrative example is provided to demonstrate the practicality of this method.
AB - Single pilot operation(SPO) is the key technology for the next generation operation of the future commercial aircraft. It consists of single pilot in the cockpit, advanced onboard automation and ground airline operator. In order to make the overall system efficient, safe, reliable and economic, human-machine function allocation for single-pilot operation should comprehensively consider various factors. Thus, the human-machine function allocation can be viewed as a typical multiple attribute group decision making (MAGDM) problem under uncertainty and ambiguity. To this end, this paper introduces a human-machine function allocation method based on hesitant fuzzy 2-tuple linguistic information. Firstly, the prioritized weighted hesitant fuzzy 2-tuple linguistic Bonferroni mean (PWHF2TLBM) operator is defined. Then the human-machine function allocation method is proposed, where the evaluations of experts are presented in the form of hesitant fuzzy 2-tuple linguistic information, and the PWHF2TLBM operator is used to aggregate the evaluations of different attributes. Finally, an illustrative example is provided to demonstrate the practicality of this method.
KW - 2-tuple linguistic information
KW - Fuzzy 2-tuple linguistic Bonferroni mean (HF2TLBM) operator
KW - hesitant fuzzy set
KW - human-machine function allocation
KW - prioritized weighted hesitant Fuzzy 2-tuple linguistic Bonferroni mean (PWHF2TLBM) operator
KW - single pilot operation
UR - http://www.scopus.com/inward/record.url?scp=85159723713&partnerID=8YFLogxK
M3 - 会议稿件
AN - SCOPUS:85159723713
T3 - 33rd Congress of the International Council of the Aeronautical Sciences, ICAS 2022
SP - 1602
EP - 1609
BT - 33rd Congress of the International Council of the Aeronautical Sciences, ICAS 2022
PB - International Council of the Aeronautical Sciences
T2 - 33rd Congress of the International Council of the Aeronautical Sciences, ICAS 2022
Y2 - 4 September 2022 through 9 September 2022
ER -