TY - JOUR
T1 - Multi-granular linguistic distribution evidential reasoning method for renewable energy project risk assessment
AU - Liang, Yingying
AU - Ju, Yanbing
AU - Qin, Jindong
AU - Pedrycz, Witold
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2021/1
Y1 - 2021/1
N2 - Nowadays, renewable energy projects have constantly been emphasized and the assessment of potential risks has been considered as an indispensable activity prior to implementation of projects. To carry out a reasonable assessment, multi-granular linguistic distribution assessments (LDAs), an effective and uncertainty representation tool, are adopted to express and quantify opinions based on personalized individual linguistic term sets. Specifically, this study develops a novel uncertain multiple criteria decision making approach, named multi-granular linguistic evidential reasoning method, which can handle incomplete and personalized preferences. A novel comparison method for LDAs is first put forward based on numerical characteristics, namely an expectation value and central moment. To fuse the multi-granular LDAs, a lossless transformation technique is further introduced and some of itsessential properties are discussed. Finally, a case study on renewable energy project risk assessment is discussed to verify the feasibility of the proposed method. Besides, sensitivity analysis is conducted to investigate the sequencing stability and comparative analysis is included to highlight the superiority of the proposed method.
AB - Nowadays, renewable energy projects have constantly been emphasized and the assessment of potential risks has been considered as an indispensable activity prior to implementation of projects. To carry out a reasonable assessment, multi-granular linguistic distribution assessments (LDAs), an effective and uncertainty representation tool, are adopted to express and quantify opinions based on personalized individual linguistic term sets. Specifically, this study develops a novel uncertain multiple criteria decision making approach, named multi-granular linguistic evidential reasoning method, which can handle incomplete and personalized preferences. A novel comparison method for LDAs is first put forward based on numerical characteristics, namely an expectation value and central moment. To fuse the multi-granular LDAs, a lossless transformation technique is further introduced and some of itsessential properties are discussed. Finally, a case study on renewable energy project risk assessment is discussed to verify the feasibility of the proposed method. Besides, sensitivity analysis is conducted to investigate the sequencing stability and comparative analysis is included to highlight the superiority of the proposed method.
KW - Evidential reasoning
KW - Linguistic distribution
KW - Multi-granular linguistic information
KW - Multiple criteria group decision making
KW - Renewable energy project risk assessment
UR - http://www.scopus.com/inward/record.url?scp=85090183086&partnerID=8YFLogxK
U2 - 10.1016/j.inffus.2020.08.010
DO - 10.1016/j.inffus.2020.08.010
M3 - Article
AN - SCOPUS:85090183086
SN - 1566-2535
VL - 65
SP - 147
EP - 164
JO - Information Fusion
JF - Information Fusion
ER -
