Multi-Attribute Technological Modeling of Coal Deposits Based on the Fuzzy TOPSIS and C-Mean Clustering Algorithms

Gligorić, Miloš; Gligorić, Zoran; Beljić, Čedomir; Torbica, Slavko; Savić, Svetlana Štrbac; Ostojić, Jasmina

doi:10.3390/en9121059

Cited by 5 publications

(4 citation statements)

References 32 publications

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“…As a common multi-objective decision analysis method [21,22], TOPSIS sorts the evaluation samples based on their proximity to the ideal effect. The algorithm constructs the virtual best solution and the worst solution, namely the positive ideal solution and the negative ideal solution, and calculates the relative Euclidean distance of the evaluation sample and the positive and negative ideal solutions, which is close to the positive ideal solution and far from the negative ideal solution as the optimal solution, and then sorts the evaluation samples in order.…”

Section: Improved Topsis Methodsmentioning

confidence: 99%

Comprehensive Evaluation of Power Quality Based on an Improved TOPSIS Method Considering the Correlation between Indices

2019

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In order to improve the scientific and rationality of power quality (PQ) comprehensive evaluation, an improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) strategy in consideration of the correlation between indices is proposed to evaluate PQ. The strategy overcomes the shortcomings of the traditional methods that ignore the correlation between PQ performance parameters. Firstly, the AHP-entropy weight (EW) method is obtained by combining the improved analytic hierarchy process (AHP) and the EW method, and the combined weights of the PQ indices are calculated. Secondly, the Mahalanobis distance is used to replace the Euclidean distance in the traditional TOPSIS method, and the PQ samples that need to be evaluated are sorted. The Mahalanobis distance nonlinearly correlates the components inside the evaluation matrix through its own covariance matrix, which solves the problem that the dimensions of each index are not uniform and eliminates the correlation interference between the indices. The example shows that the improved TOPSIS method effectively avoids the misjudgment caused by the correlation between the indices, and the evaluation results are more reasonable and scientific, with greater superiority and effectiveness.

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Section: Improved Topsis Methodsmentioning

confidence: 99%

Comprehensive Evaluation of Power Quality Based on an Improved TOPSIS Method Considering the Correlation between Indices

2019

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“…It has great advantages in avoiding subjective factors, simplifying algorithms and reducing errors. Hence we chose it instead of other alternative assessment methods, such as Analytic Hierarchy Process (AHP) [55][56][57][58], Principal Components Analysis (PCA) [59,60], and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) [61][62][63], etc. In recent years, the DEA model has been widely used in the study of industrial wastewater control efficiency.…”

Section: The Dea Modelmentioning

confidence: 99%

Efficiency Evaluation and Policy Analysis of Industrial Wastewater Control in China

Yang

2017

Energies

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With increasing emissions of industrial wastewater and poor control measures, environmental pollution has become a serious issue haunting China's economic development. Meanwhile, the current pollution management policy system in China is mainly under the supervision of the central government and executed by local governments. Under the current economic growth model of China, the industrial sector remains the dominant segment of our economy, which makes the Total Factor Efficiency (TFE) evaluation and policy analysis of industrial wastewater control decisive factors concerning China's future economic growth and sustainable development. Based on existing studies of China and abroad, and with the help of a Data Envelope Analysis (DEA) model, this paper used 39 industrial sectors and their input-output data from 2003 to 2014 of China as Decision Making Units to calculate the TFE of wastewater control in different industrial sectors of China. Moreover, we have designed and adopted our own MATLAB programming for optimization solutions of multi-variable constrained nonlinear functions in order to obtain a more accurate estimation of the TFE of wastewater control. Based on our calculation results, this paper further explained the difference in TFE and policy implications across typical industries in China, and offered policy recommendations accordingly.

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“…In global methods, the interpolation depends on all sample points, while the local interpolation methods depend only on the data in its neighborhood [4]. Additionally, artificial neural networks [14], fuzzy methodology [15,16], evolutionary algorithms [17], support vector machines [18], and fractal models [19] have also been used to estimate the grade of the mineralized deposits.…”

Section: Introductionmentioning

confidence: 99%

Grade Distribution Modeling within the Bauxite Seams of the Wachangping Mine, China, Using a Multi-Step Interpolation Algorithm

Wang

2017

Minerals

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Abstract:Mineral reserve estimation and mining design depend on a precise modeling of the mineralized deposit. A multi-step interpolation algorithm, including 1D biharmonic spline estimator for interpolating floor altitudes, 2D nearest neighbor, linear, natural neighbor, cubic, biharmonic spline, inverse distance weighted, simple kriging, and ordinary kriging interpolations for grade distribution on the two vertical sections at roadways, and 3D linear interpolation for grade distribution between sections, was proposed to build a 3D grade distribution model of the mineralized seam in a longwall mining panel with a U-shaped layout having two roadways at both sides. Compared to field data from exploratory boreholes, this multi-step interpolation using a natural neighbor method shows an optimal stability and a minimal difference between interpolation and field data. Using this method, the 97,576 m 3 of bauxite, in which the mass fraction of Al 2 O 3 (W a ) and the mass ratio of Al 2 O 3 to SiO 2 (W a/s ) are 61.68% and 27.72, respectively, was delimited from the 189,260 m 3 mineralized deposit in the 1102 longwall mining panel in the Wachangping mine, Southwest China. The mean absolute errors, the root mean squared errors and the relative standard deviations of errors between interpolated data and exploratory grade data at six boreholes are 2.544, 2.674, and 32.37% of W a ; and 1.761, 1.974, and 67.37% of W a/s , respectively. The proposed method can be used for characterizing the grade distribution in a mineralized seam between two roadways at both sides of a longwall mining panel.

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Multi-Attribute Technological Modeling of Coal Deposits Based on the Fuzzy TOPSIS and C-Mean Clustering Algorithms

Cited by 5 publications

References 32 publications

Comprehensive Evaluation of Power Quality Based on an Improved TOPSIS Method Considering the Correlation between Indices

Comprehensive Evaluation of Power Quality Based on an Improved TOPSIS Method Considering the Correlation between Indices

Efficiency Evaluation and Policy Analysis of Industrial Wastewater Control in China

Grade Distribution Modeling within the Bauxite Seams of the Wachangping Mine, China, Using a Multi-Step Interpolation Algorithm

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