Application of Relevance Maps in Multidimensional Classification of Coal Types / Zastosowanie Map Odniesienia W Wielowymiarowej Klasyfikacji Typów Węgla

Niedoba, Tomasz

doi:10.1515/amsc-2015-0007

Cited by 8 publications

(6 citation statements)

References 26 publications

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“…Relevance maps method on plane serving for data visualization is based on placing special points called relevance points which represent individual features of considered object [22,29,44]. For each feature (coordinate) the relevance point representing this feature is assigned.…”

Section: Description Of the Methodsmentioning

confidence: 99%

Application Of Relevance Maps Method To Evaluate The Suitability Of Coal Samples For Fluidal Gasification Process

2016

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Abstract. The coal gasification process is one of the technologies which gain more and more attention among technologists dealing with processing and utilization of coal. In case of ground gasification, one of such technologies is fluidized bed gasification. For such gasification the guidelines were elaborated within the scientific project of NCBiR no. 23.23.100.8498/R34 Authors chose main of these guidelines, concerning the required levels of certain coal features. In purpose of investigating coal for its suitability to gasification, samples were collected from two Polish mines: ZG Janina and ZG Wieczorek and processed properly. The methods being used to visualization of multidimensional data through transformation of multidimensional space into two-dimensional space allow to present multidimensional data on computer screen. Among such methods, relevance maps method can be found which was used in this paper to present and analyze set of seven-dimensional data describing coal samples originating from both mines. It was decided to check whether this method of visualization of multidimensional data allows to divide the samples space into subspaces of various usefulness to the process of fluidal gasification or not. The method enables the visualisation of the optimal subspace containing the set requirements concerning the properties of coals intended for this process.

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Section: Description Of the Methodsmentioning

confidence: 99%

Application Of Relevance Maps Method To Evaluate The Suitability Of Coal Samples For Fluidal Gasification Process

2016

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“…Figures 21 and 22 present views obtained using the relevance maps method [14,24,25]. Figure 21 shows that the curve separating areas occupied by samples with different susceptibility to fluidal gasification has one inflection point.…”

Section: Discussionmentioning

confidence: 99%

“…Multidimensional scaling [12,[21][22][23] constitutes such a representation that distance between each two images of points in the two-dimensional output space representing the screen is as close as possible to the distance between points in the input space corresponding to them. In the method of relevance maps [14,24,25], special points representing axes of the coordinate system are additionally used. These points and points representing vectors belonging to the analyzed set are distributed on the plane in such a way that the distance of each point representing a data vector to a point representing a given axis of the coordinate system is as close as possible to the value of this coordinate of a given data vector.…”

Section: Introductionmentioning

confidence: 99%

The experimental study of the effectiveness of Kohonen maps and autoassociative neural networks in the qualitative analysis of multidimensional data by the example of real data describing coal susceptibility to fluidal gasification

Jamroz

2020

Neural Comput & Applic

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The qualitative analysis of multidimensional data using their visualization allows to observe some characteristics of data in a way which is the most natural for a human, through the sense of sight. Thanks to such an approach, some characteristics of the analyzed data are simply visible. This allows to avoid using often complex algorithms allowing to examine specific data properties. Visualization of multidimensional data consists in using the representation transforming a multidimensional space into a two-dimensional space representing a computer screen. The important information which can be obtained in this way is the possibility to separate points belonging to different classes in the multidimensional space. Such information can be directly obtained if images of points belonging to different classes occupy other areas of the picture presenting these data. The paper presents the effectiveness of the qualitative analysis of multidimensional data conducted in this way through their visualization with the application of Kohonen maps and autoassociative neural networks. The obtained results were compared with results obtained using the perspective-based observational tunnels method, PCA, multidimensional scaling and relevance maps. Effectiveness tests of the above methods were performed using real sevendimensional data describing coal samples in terms of their susceptibility to fluidal gasification. The methods' effectiveness was compared using the criterion for the readability of the multidimensional visualization results, introduced in earlier papers. Keywords Multidimensional visualization Á Multidimensional data analysis Á Data mining Á Self-organized neural network Á Autoassociative neural network Á Kohonen maps & Dariusz Jamróz

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“…Multidimensional methods can also be used to assess the effectiveness of beneficiation processes. In Energies 2023, 16, 1600 2 of 17 this regard, the following methods were applied for a number of research works: observational tunnels method [11], principal component analysis [12,13], relevance maps [14], self-organizing Kohonen maps [15], multidimensional scaling [16] and autoassociative neural networks [17]. A comparison of these methods and their effectiveness was presented in detail elsewhere [18].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Effects of Coal Jigging by Means of Kruskal–Wallis and Friedman Tests

et al. 2023

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Coal beneficiation processes are often based on gravitational enrichment techniques. Therefore, various types of jigs are often used in this area. A number of factors determine the quality of the final product. Therefore, proper and systematic monitoring of such a process is necessary. The present work examined the effect of the hutch water amount and the amount of processed coal (system capacity) on the yield and ash grade in individual density–size fractions. A statistical method in the form of the Kruskal–Wallis test and the Friedman test was used to evaluate the process. These tests were proposed as universal and reliable alternatives to classical analysis of variance (ANOVA) analysis. The performed analysis allowed for the determination of what process conditions should be selected in order to obtain certain effects. Therefore, it allowed us to apply certain combinations of hutch water amount, system capacity and particle characteristics to maximize the expected effects. The application of statistical analysis methods in the form of Kruskal–Wallis and Friedman tests to evaluate process efficiency creates new possibilities to monitor and optimize the jigging process in both context of amount and quality of final product and is very important not only for mining enterprise but also from an environmental point of view.

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Application of Relevance Maps in Multidimensional Classification of Coal Types / Zastosowanie Map Odniesienia W Wielowymiarowej Klasyfikacji Typów Węgla

Cited by 8 publications

References 26 publications

Application Of Relevance Maps Method To Evaluate The Suitability Of Coal Samples For Fluidal Gasification Process

Application Of Relevance Maps Method To Evaluate The Suitability Of Coal Samples For Fluidal Gasification Process

The experimental study of the effectiveness of Kohonen maps and autoassociative neural networks in the qualitative analysis of multidimensional data by the example of real data describing coal susceptibility to fluidal gasification

Evaluation of the Effects of Coal Jigging by Means of Kruskal–Wallis and Friedman Tests

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