A cloud model-based multi-level fuzzy comprehensive evaluation approach for financing credit of scientific &amp; technological small-medium enterprises

Li, Jie; Zhang, Qiuwen; Yan, Fei; Zhong, Ming

doi:10.1080/10236198.2016.1250751

Cited by 16 publications

(10 citation statements)

References 3 publications

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“…In this paper, interval number [ CL , CR ] was used to define indices under various evaluation grades, where a boundary value is a transition point between two adjacent grades and belongs to the two grades at the same time. That is, the boundary value corresponding to two adjacent grades has a membership of 0.5 [ 27 ]. We deduced the formula for the characteristic parameters of the cloud model (see Formula ( 1 )) to convert qualitative concepts into three numerical characteristics.…”

Section: Evaluation Methodsmentioning

confidence: 99%

“…The cloud model, proposed by Li et al [26] and based on probability statistics and fuzzy mathematics, is a model for converting between qualitative concepts and quantitative values. It describes the randomness and fuzziness of fuzzy concepts and overcomes the deficiencies of traditional evaluation methods in dealing with randomness and fuzziness, which has been extensively used in the fields of multi-criteria group decision making, risk evaluation, and so forth [19,27]. Assuming that U is a universe of discourse expressed by an exact numerical magnitude and that C is a qualitative concept within U, then, for element x within any universe of discourse, there is a random number u(x)2[0,1] with stabilization bias, which is referred to as the membership of x relative to C. In this case, the distribution of x within U is called a cloud, and each x value is referred to as a cloud droplet, or a quantitative description of qualitative concepts.…”

Section: Cloud Modelmentioning

confidence: 99%

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Cloud model-based evaluation of landslide dam development feasibility

Luo

et al. 2021

PLoS ONE

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As natural backwater structures, landslide dams both threaten downstream human settlement or infrastructure and contain abundant hydro-energy and tourism resources, so research on their development feasibility is of great significance for permanently remedying them and effectively turning disasters into benefits. Through an analysis of the factors influencing landslide dam development and utilization, an index system (consisting of target, rule, and index layers) for evaluating development feasibility was constructed in this paper. Considering uncertainty and randomness in development feasibility evaluation, a cloud model-improved evaluation method was proposed to determine membership and score clouds based on the uncertainty reasoning of cloud model, and a cloud model-improved analytic hierarchy process (AHP-Cloud Model) was introduced to obtain weights. Final evaluation results were obtained using a hierarchical weighted summary. The improved method was applied to evaluate the Hongshiyan and Tangjiashan landslide dams and the results were compared with the maximum membership principle results. The results showed that the cloud model depicted the fuzziness and uncertainty in the evaluation process. The improved method proposed in this paper overcame the loss of fuzziness in the maximum membership principle evaluation results, and was capable of more directly presenting evaluation results. The development feasibility of the Hongshiyan landslide dam was relatively high, while that of the Tangjiashan landslide dam was relatively low. As suggested by these results, the evaluation model proposed in this paper has great significance for preparing a long-term management scheme for landslide dams.

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Section: Evaluation Methodsmentioning

confidence: 99%

Section: Cloud Modelmentioning

confidence: 99%

Cloud model-based evaluation of landslide dam development feasibility

Luo

et al. 2021

PLoS ONE

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“…To date, various methods have been developed and introduced to construct the credit evaluation models, such as AHP [25,26,[42][43][44][45][46][47], fuzzy AHP (FAHP) [48,49], DEA [25], [44,45], LR analysis [27,35,50,51], artificial neural network (ANN) [52,53], and SVM [54]. However, AHP can be used to evaluate the subjective and objective attributes of multi-criteria decision making, which is capable of guiding DMs to make the best and optimal judgment.…”

Section: Previous Research On Credit Evaluation Of Enterprisesmentioning

confidence: 99%

“…Step 4: Calculate the full credit score and rating The full credit score was calculated by adding up the score of the basic-score items and plus-score items. Besides, the credit level of TSMEs was divided into nine grades based on the full credit score, including AAA (more than 90), AA (85-90), A (80-85), BBB (7-80), BB (70-75), B (60-70), CCC (50-60), CC (40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50) and C (less than 40).…”

Section: Empirical Analysismentioning

confidence: 99%

A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods

Jia

Zhang

et al. 2020

Sustainability

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A high-quality credit index system is essential for technological small and medium-sized enterprises (TSMEs) to obtain financing from various institutions, such as banks, venture capital. Some attempts have made to construct the credit index system for TSMEs. However, the current credit index systems for TSMEs have placed too much emphasis on their financial ability with few prominent technological and talent indicators. Therefore, this study has proposed a dynamic credit index system for TSMEs in China using the Delphi and the Analytic Hierarchy Process (AHP) methods. This credit index system covers a wide range of indicators to measure the enterprises’ controller ability, operation and management ability, financial ability, and innovation capacity. This study made some contributions in the following aspects: (1) This study proposed a credit index system for TSMEs that highlights the main characteristics of technological innovation and talents of enterprises in China. (2) The credit index system is also highly adaptable as it can dynamically adjust the index weight according to the life cycles of TSMEs. (3) A case study of evaluating the credit of three TSMEs in China was selected to verify the feasibility and the effectiveness of this system. The results show that the credit index system constructed in this study provides a comprehensive and systematic model for evaluating the credit of TSMEs in China.

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“…Based on the theory of the APH model, we propose a hybrid AHP-Fuzzy Comprehensive Evaluation Model to assess the atmospheric environmental quality [34,17]. In the proposed hybrid model, AHP is able to estimate the weight coefficient of the index system, and fuzzy comprehensive evaluation [12,11] approach can tackle the vagueness of remark in evaluation process.…”

mentioning

confidence: 99%

Atmospheric environmental quality assessment method based on analytic hierarchy process

Lv¹,

Ji²

2019

Discrete &Amp; Continuous Dynamical Systems - S

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Atmospheric environmental quality significantly influences the environment of people's life and the development of modern society. Therefore, in this paper, we aim to accurately assess atmospheric environmental quality. Firstly, we propose and analyze two indicator systems for atmospheric environmental quality assessment, that is, 1) the standard air pollution index, and 2) an index system which covers different types of influencing factors related to air quality. In particular, the proposed index system is made up of seven parts, that is, 1) Climate and meteorology, 2) Economic and social development, 3) Industrial structure, 4) Energy consumption, 5) Industrial pollutant discharge, 6) The greening of the city, and 7) Environmental protection construction. Secondly, we propose a hybrid AHP-Fuzzy Comprehensive Evaluation Model to evaluate the atmospheric environmental quality. In the hybrid model, AHP is used to calculate the weight coefficient of the index system, and fuzzy comprehensive evaluation model is exploited to describe the vagueness of remark in the evaluation process. Finally, experimental results demonstrate that using the proposed index system, the hybrid AHP-Fuzzy comprehensive evaluation model is able to assess air quality more accurately than the modified API.

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A cloud model-based multi-level fuzzy comprehensive evaluation approach for financing credit of scientific & technological small-medium enterprises

Cited by 16 publications

References 3 publications

Cloud model-based evaluation of landslide dam development feasibility

Cloud model-based evaluation of landslide dam development feasibility

A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods

Atmospheric environmental quality assessment method based on analytic hierarchy process

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