A Combination Evaluation Method Based on FAHP and Entropy Weigh Method

Zhou, Wei; Zhao, Rui

doi:10.1109/wicom.2007.1448

Cited by 2 publications

(3 citation statements)

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“…Additionally, some multiple-criteria decision making (MCDM) evaluation methods such as Analytical Hierarchy Process (AHP), data envelopment analysis (DEA), and TOPSIS [34,35] were adopted. However, these methods mostly rely on surveybased subjective data of criteria, and overlook the objectivity of the factors, which may has a negative impact on the accuracy of evaluation results [36].…”

Section: B Evaluating Methods Of Maturitymentioning

confidence: 99%

“…Especially, an AHP-Entropy method has been developed to evaluate the environmental management maturity level [32], as well as the construction industrialisation development of construction firms [29]. A FAHP-entropy method has also been utilised in evaluating issues with more practical and effective results than AHP-Entropy [36,45].…”

Section: B Evaluating Methods Of Maturitymentioning

confidence: 99%

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Developing a Fuzzy Multi-Criteria Evaluation Model for Prefabrication Development Maturity of Construction Firms

et al. 2020

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Section: B Evaluating Methods Of Maturitymentioning

confidence: 99%

Section: B Evaluating Methods Of Maturitymentioning

confidence: 99%

Developing a Fuzzy Multi-Criteria Evaluation Model for Prefabrication Development Maturity of Construction Firms

et al. 2020

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“…In this paper, HHT is used to extract the distinctive features of the interactive force signal, and obtain the instantaneous amplitude. By combination evaluation [8], the linear weighting method is used to conduct an comprehensive evaluation index. Four feature parameters are extracted from the evaluation index and combined as feature vectors, including average amplitude, kurtosis, crest factor and average remaining.…”

Section: Introductionmentioning

confidence: 99%

Hilbert-Huang Transform based state recognition of bone milling with force sensing

Deng

Zhang

Guo

et al. 2013

2013 IEEE International Conference on Information and Automation (ICIA)

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Bone milling is one of the most common operations in various kinds of orthopedical surgeries, such as laminectomy surgery. For safety issue and efficacy, it is very important to recognize the states in milling operation. In this paper, an approach to recognize the states of bone milling is proposed, which identify the cortical tissue layer and cancellous tissue layer. Hilbert-Huang Transform (HHT) based on Empirical Mode Decomposition (EMD) is used to analysis and extract the features of the interactive force in milling operation. The instantaneous amplitude of the Intrinsic Mode Functions (IMF) are combined by means of linear weighting method to obtain one comprehensive evaluation index. The feature vector of the index consists of average amplitude, kurtosis, crest factor and average remaining of EMD. With the feature vector, states of cortical and cancellous layer in milling process are recognized based on Support Vector Machine (SVM). Finally, the milling experiment with pig scapula is performed to show the effectiveness of the proposed approach.

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A Combination Evaluation Method Based on FAHP and Entropy Weigh Method

Cited by 2 publications

References 0 publications

Developing a Fuzzy Multi-Criteria Evaluation Model for Prefabrication Development Maturity of Construction Firms

Developing a Fuzzy Multi-Criteria Evaluation Model for Prefabrication Development Maturity of Construction Firms

Hilbert-Huang Transform based state recognition of bone milling with force sensing

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