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Predict the logistic risk: fuzzy comprehensive measurement method or particle swarm optimization algorithm?
oleh: Dafeng Xu, Leon Pretorius, Dongdong Jiang
Format: | Article |
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Diterbitkan: | SpringerOpen 2018-06-01 |
Deskripsi
Abstract Risk analysis is an important fundamental basis of the decision-making process, and it has been applied in many fields. In order to improve the risk management of logistic, a new model based on particle swarm optimization (PSO) is proposed, which is a stochastic optimization method based on population. Through a comparison of performance with a Fuzzy Comprehensive Measurement Method (FCMM), the findings indicated that PSO can predict the logistic risk more accurately. The experimental results show that the model of logistic risk analysis and identification based on PSO algorithm is superior to FCMM model.