Core Competitiveness Evaluation of Clean Energy Incubators Based on Matter-Element Extension Combined with TOPSIS and KPCA-NSGA-II-LSSVM

Liang, Guangqi; Niu, Dongxiao; Liang, Yi

doi:10.3390/su12229570

Cited by 11 publications

(7 citation statements)

References 28 publications

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“…The number in equation ( 6) is only used for support vectors, and 𝑏 * is the threshold distribution, which can be obtained by using all the support vectors (satisfied with the signs multiplication in equation (3) or by taking the average of a pair of support vectors in both models.…”

Section: ∥𝜔∥mentioning

confidence: 99%

“…Economic entities in the world have been gradually influenced by the concept of corporate social responsibility, enterprises have begun to attach importance to the necessity of corporate social responsibility and regard it as an important source to improve their competitiveness. Therefore, enterprises should shift the focus of development from profit maximization to the society closely related to enterprises [3]. At present, more and more enterprises actively undertake social responsibility and actively pass various social responsibility certifications, such as the world's first international standard for social responsibility (SA8000), which requires that the products provided by suppliers must meet the standards of social responsibility, that is to say, it aims to constrain the behavior of suppliers.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Corporate Social Responsibility and Core Competitiveness Based on GA-SVM Model

Guo

Wong

2023

Applied Mathematics and Nonlinear Sciences

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The author proposes a model evaluation based on the GA-SVM model to better understand the evaluation of the company’s relationship and core competitiveness. The system index is reduced by relative gray analysis, the support vector machine model is optimized by a genetic algorithm, and the specific algorithm steps are introduced. Select models from the top 100 enterprises in China’s construction industry in 2020 published by China Construction Industry Market, using relative gray to reduce the measure, and then use the genetic algorithm support vector machine (GA-SVM) model for the training model to achieve the evaluation of the core competencies of the target construction technique business. The experimental results show that the relative error of prediction of the GA-SVM(Genetic algorithm-support vector machine) model for the evaluation of the competitive core of the business is not more than 5, which meets the should be made of accurate predictions. Therefore, choosing the Gaussian radial basis kernel function (RBF) as the kernel function of the GA-SVM intelligent evaluation model is good. It proves that the GA-SVM model can analyze the relationship between the role and the important competition.

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Section: ∥𝜔∥mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of Corporate Social Responsibility and Core Competitiveness Based on GA-SVM Model

Guo

Wong

2023

Applied Mathematics and Nonlinear Sciences

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“…e level of the evaluated target depends on the grade of the data interval with the highest membership degree [20]. A matter element is the basic unit of this method and is a logical structure described by the names, characteristics, and quantities of an object.…”

Section: Eory Of Matter Element Extension Matter Element Extension Th...mentioning

confidence: 99%

Durability Evaluation of Concrete Bridges Based on the Theory of Matter Element Extension—Entropy Weight Method—Unascertained Measure

2021

Mathematical Problems in Engineering

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To accurately evaluate the durability of reinforced concrete girder bridges, a durability evaluation model was developed based on the matter element extension theory, entropy weight method, and unascertained measure theory. A total of seven indicators were selected for durability evaluation: the concrete presumed strength uniformity coefficient, reinforcement corrosion potential level, chloride ion content, average value of concrete relative carbonation depth, crack width, resistivity, and characteristic value of the reinforcement protective layer thickness. The weights of the durability evaluation indices were assigned using matter element extension combined with the entropy weight method, and the multi-indicator comprehensive evaluation vector was obtained by combining the single-indicator measurement matrix. The evaluation results were analyzed by applying the confidence criterion. The results showed that the evaluation results of this model matched with the actual conditions of the girder bridges, which indicates that this durability evaluation model has good applicability and is reasonable. Finally, a comparative study proved that the model could accurately evaluate the bridge durability.

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“…This method combined the nonlinear kernel function with PCA, performed linear PCA on the data in the high‐dimensional feature space of the mapping and selected the principal components (PCs) of the feature space for data dimensionality reduction. Compared with other nonlinear methods, the advantage of KPCA method is not only suitable for nonlinear optimization through a kernel function as simple as PCA, but also KPCA can use different kernel functions and parameters adjustment which is more suitable for nonlinear problems in a wider range of applications 36–38 …”

Section: Introductionmentioning

confidence: 99%

“…Compared with other nonlinear methods, the advantage of KPCA method is not only suitable for nonlinear optimization through a kernel function as simple as PCA, but also KPCA can use different kernel functions and parameters adjustment which is more suitable for nonlinear problems in a wider range of applications. [36][37][38] In real life, when an emergency occurs suddenly, decisions need to be made in a short period of time. IVPFLs can accurately and clearly express the preferences of DMs, and it described the decision information in combination with qualitative and quantitative aspects in accordance with the actual situation.…”

Section: Introductionmentioning

confidence: 99%

Interval‐valued Pythagorean fuzzy linguistic KPCA model based on TOPSIS and its application for emergency group decision making

Zeng

Zhou

et al. 2022

Int J of Intelligent Sys

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This paper investigates the emergency group decision‐making problem based on interval‐valued Pythagorean fuzzy language sets (IVPFLSs). The frequent occurrence of emergency events can bring huge economic damage to human beings. To reduce the loss, it is very important to make reasonable emergency decisions effectively and timely. In the emergency decision making (EDM), these problems are few studied, such as high dimension problem, data nonlinearity, and correlation. For EDM problems, the advantage of IVPFLSs is that it can reasonably express the evaluation information given by decision makers (DMs) through both qualitative and quantitative aspects. However, if the dimension and nonlinear relationship of the decision data keep growing, and the traditional decision‐making methods will fail. The distance measure between decision data is necessary to calculate in the process of dimensionality reduction, and the current research does not propose the definition of IVPFLSs distance measure. On the basis of this, this paper first uses the attributes and DMs as variables to define the standard Euclidean distance measure between IVPFLSs. For nonlinear features, we construct the interval‐valued Pythagorean fuzzy language kernel principal component analysis (IVPFL‐KPCA) model to reduce the dimensionality. What is more, we also obtain the reasonable weight vectors of the attribute and DMs from cumulative contribution rate. For low‐dimensional decision data, according to the technique for order performance by similarity to ideal solution method, the best emergency plan is selected for the information variables after dimensionality reduction. In sum, the IVPFL‐KPCA model not only avoids multicollinearity and nonlinear separability between decision data, but also obtains reasonable weights. It further improves the efficiency of decision‐making operations and reduces the difficulty of the algorithm. Finally, an example of earthquake emergency plan is shown to demonstrate the feasibility and practicability of the proposed method. Besides, we also compare it with the existing methods, which proves the effectiveness of the method.

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Core Competitiveness Evaluation of Clean Energy Incubators Based on Matter-Element Extension Combined with TOPSIS and KPCA-NSGA-II-LSSVM

Cited by 11 publications

References 28 publications

Evaluation of Corporate Social Responsibility and Core Competitiveness Based on GA-SVM Model

Evaluation of Corporate Social Responsibility and Core Competitiveness Based on GA-SVM Model

Durability Evaluation of Concrete Bridges Based on the Theory of Matter Element Extension—Entropy Weight Method—Unascertained Measure

Interval‐valued Pythagorean fuzzy linguistic KPCA model based on TOPSIS and its application for emergency group decision making

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