Product Demand Forecasting in Knowledgeable Manufacturing Based on Demand Forecasting Net

Xiangang, Meng; Yan, Hong‐Sen

doi:10.1109/dbta.2009.120

Cited by 1 publication

(3 citation statements)

References 10 publications

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“…For multi attribute Petri net, the research results can be seen such as [10], its ideas and theories are consistent with colored Petri net [9] [24]. Colored Petri net is classified by the signs of Petri net, using different colors to mark different classifications of signs, and in the whole Petri net the color classifications of each place are fixed.…”

Section: Credit Evaluation Of the Network Supplier Based On Petri Netmentioning

confidence: 95%

“…The credit degree value for commodity distribution The distribution period for commodity (q 8 1 ) w(p 8 ) 1 0.02 The distribution credit value for commodity (q 8 2 ) w(p 8 ) 2 0.05 p 9 The credit degree value for after-sales service acceptance (q 9 ) w(p 9 ) 0.01 p 10 The credit degree value for after-sales service (q 10 ) w(p 10 ) 0.02 p 11 The credit degree value for accepting to return and repair commodity (q 11 ) w(p 11 ) 0.02 p 12 The credit degree value for returning and repairing commodity (q 12 ) w(p 12 ) 0.02 p 13 The credit degree value for the durability and constancy of commodity using (q 13 ) w(p 13 ) 0.05 Table 4 The importance (v(p i ) j ) and credit value (…”

Section: Figure 5 B2c Transaction Process' Cwpsn Modelmentioning

confidence: 99%

“…(1) Flexible manufacturing system. Such as Meng and Yan [10] with the help of knowledgeable manufacturing systems' knowledge base, handling and training multi attribute fuzzy Petri net attribute, and regularization processing the irregular model, constructing the subsequent products' multi attribute fuzzy Petri net model on the basis of the original products' multi attribute fuzzy Petri net model. Simon, Oyekan, Hutabarat, et al [11] constructed the Petri net model for the manufacturing systems.…”

Section: Introductionmentioning

confidence: 99%

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Network Supplier Credit Management: Models Based on Petri Net

Zhu

2019

Teh. vjesn.

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In current credit evaluation methods, the credit condition of the network supplier and the credit degree of each index cannot be described well, and the credit evaluation data only source of the transaction platform have much limitation. This research proposes the method of calculating the importance and the value of the credit evaluation indexes, and proposes to put credit evaluation into big data environment. This research uses the transaction process of B2C as the case, and constructs multiple attribute weighted Petri net credit index subnet (CWPSN) for realizing the credit evaluation of the network supplier, and for presenting the correlations among the evaluation results of the credit evaluation indexes, and for presenting the importance of the indexes and the credit degree of each index, and describes the cost optimization process with credit cost optimization investment process Petri net (CCOIPPN). By the case to verify the credit evaluation method based on Petri net and the cost optimization method based on Petri net. The researches have provided methods for clearly and concretely describing the process of credit evaluation and cost optimization of network supplier, and have guidance significance for similar other researches.

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Section: Credit Evaluation Of the Network Supplier Based On Petri Netmentioning

confidence: 95%