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Data preprocessing and its influence on the adsorption capacity of calculated shale. Comparison of selected methods: A case study

100%

Waszczuk P.

Mineralogia

2017

tom Vol. 48, iss. 1/4

157--165

This article discusses the impact of choosing a data preprocessing method for the calculated gas density necessary to determine the sorption capacity of a material. The sample of gas-bearing shale was subjected to a volumetric sorption test. The obtained data, pressure and temperature were preprocessed by three methods: moving average, polynomial regression and locally weighted scatterplot smoothing. The results include the excess and absolute sorption calculated from data that were filtered, and data without pre-treatment and Langmuir isotherms’ coefficients for every case.

Analysis of data pre-processing methods for sentiment analysis of reviews

80%

Parlar T. , Ozel S. , Song F.

tom Vol. 20 (1)

123--141

The goals of this study are to analyze the effects of data pre-processing methods for sentiment analysis and determine which of these pre-processing methods (and their combinations) are effective for English as well as for an agglutinative language like Turkish. We also try to answer the research question of whether there are any differences between agglutinative and non-agglutinative languages in terms of pre-processing methods for sentiment analysis. We find that the performance results for the English reviews are generally higher than those for the Turkish reviews due to the differences between the two languages in terms of vocabularies, writing styles, and agglutinative property of the Turkish language.

Data mining-generation and visualisation of decision trees

51%

Kwaśnicka H. , Doczekalski M.

Systems Science

2002

tom Vol. 28, nr 3

63-84

A computer system presented in the paper is developed as a data mining tool-it allows using large databases as a source for the process of decision tree generation and visualisation. The designed system (DTB&V-Decision Tree Builder and Visualiser) is able to perform data preprocessing, generation of decision trees followed by their post-processing and visualisation. DTB&V was tested using a number of databases commonly employed for such tasks.

Wstępne przetwarzanie danych rzeczywistych na przykładzie analizy rezygnacji

51%

Sulikowski P.

2009

tom nr 1 (18)

99-106

Customer churn is a grave problem for contemporary businesses. Rough sets method can be applied to build a model of the phenomenon. While analysing real-world data obtained directly from an interested company, the need for data pre-processing arises. For that reason, this paper introduces a procedure combining certain useful analytical activities. They can help improve credibility and interpretability of the final results.

Neural networks for the analysis of mine-induced building vibrations

41%

Kuźniar K.

Computer Assisted Mechanics and Engineering Sciences

2011

tom Vol. 18, no. 3

147-159

A study of the capabilities of arti?cial neural networks in respect of selected problems of the analysis of mine-induced building vibrations is presented. Neural network technique was used for the prediction of building fundamental natural period, mapping of mining tremors parameters into response spectra from ground vibrations, soil-structure interaction analysis, simulation of building response to seismictype excitation. On the basis of the experimental data obtained from the measurements of kinematic excitations and dynamic responses of actual structures, training and testing patterns of neural networks were formulated. The obtained results lead to a conclusion that the neural technique gives possibility of e?cient, accurate enough for engineering, analysis of structural dynamics problems related to mineinduced excitations.