Journal of Engineering Sciences / Журнал інженерних наук
Permanent URI for this collectionhttps://devessuir.sumdu.edu.ua/handle/123456789/34326
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Item Optimization of graphene oxide’s characteristics with TOPSIS using an automated decision-making process(Sumy State University, 2023) Javanbakht, T.The present study focuses on a new application of TOPSIS to predict and optimize graphene oxide’s characteristics. Although this carbon-based material has been investigated previously, its optimization with this method using an automated decision-making process has not been performed yet. The major problem in the design and analysis of this nanomaterial is the lack of information on comparing its characteristics, which has led to the use of diverse methods that have not been appropriately compared. Moreover, their advantages and inconveniences could be investigated better once this investigation provides information on optimizing its candidates. In the current research work, a novel automated decision-making process was used with the TOPSIS algorithm using the Łukasiewicz disjunction, which helped detect the confusion of properties and determine its impact on the rank of candidates. Several characteristics of graphene oxide, such as its antibiofilm activity, hemocompatibility, activity with ferrous ions in hydrogen peroxide, rheological properties, and the cost of its preparation, have been considered in its analysis with TOPSIS. The results of this study revealed that the consideration of the criteria of this nanomaterial as profit or cost criteria would impact the distances of candidates from the alternatives. Moreover, the ranks of the candidates changed when the rheological properties were considered differently in the data analysis. This investigation can help improve the use of this nanomaterial in academic and industrial investigations.Item Automated decision-making with TOPSIS for water analysis(Sumy State University, 2022) Javanbakht, T.This paper aims to present a new application of TOPSIS with an automated decision-making process for the analysis of drinking water. For this purpose, the algorithm was modified with a fuzzy disjunction, and the maximal output values were set to one. The properties of drinking water, such as total dissolved solids, hardness, electrical conductivity, and cost, were the criteria analyzed in this study. These criteria were analyzed with unmodified and modified algorithms. Therefore, the modified TOPSIS was also used to optimize the parameters of the candidates. The appearance of the value of 1.0 in the algorithm’s output was due to the confusion of an individual’s categories of drinking water and undrinkable water. The advantage of this investigation was that, for the first time, it allowed automated decision-making to detect the drinking water in different samples and analyze them according to their characteristics. This would be important in developing new technologies for detecting and analyzing drinking water in the environment. The results of this paper can be applied in materials sciences and engineering.