Research on evaluation of emergency communication vehicle cabin’s internal environment design based on q-rung orthopair fuzzy information

Author:

Zhang Jiarui1

Affiliation:

1. Hoseo University, Asan City, South Chungcheong, South Korea

Abstract

The design of the emergency communication vehicle is centered around the overall layout, which is characterized by the fact that the vehicle chassis is mostly purchased parts and is equipped with an insulated and insulated box, mainly used for instrument operation and equipment placement. The emergency communication vehicle cabin environment includes: cabin seats; seat cover; control cabinet, including operation keyboard, display screen, etc; The ceiling and carpet that make up the interior space of the car; Storage box for storage equipment; tool cabinet; cabin control system facilities; Fire prevention and extinguishing facilities in the cabin; various handrails, coat racks, short ladders, lighting facilities, etc. inside the car. The design of emergency communication vehicle interior environment involves multiple disciplines, and the selection of design schemes requires scientific and reasonable evaluation methods to select reasonable schemes for optimization design. The evaluation of emergency communication vehicle cabin’s internal environment design is classical multiple attribute decision making (MADM) problems. In this article, based on bidirectional projection and grey relational projection measure, we shall propose some projection models with q-rung orthopair fuzzy sets (q-ROFSs). First of all, the definition of q-ROFSs is introduced. Furthermore, some projection models with q-ROFSs are proposed based on the bidirectional projection and grey relational projection model. Based on developed weighted projection models, the MADM model is established and all computing steps are simply depicted. Finally, a numerical example for evaluation of emergency communication vehicle cabin’s internal environment design is given to illustrate this new model and some comparisons are conducted to illustrate advantages of the new built method.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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