Application of Spearman’s Method for the Analysis of the Causes of Long-Term Post-Failure Downtime of City Buses

Rymarz, Joanna; Niewczas, Andrzej; Hołyszko, Piotr; Dębicka, Ewa

doi:10.3390/app12062921

Cited by 10 publications

(5 citation statements)

References 21 publications

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“…The closer the value of this measure is to −1, the stronger the negative correlation between the studied characteristics, while the closer it is to +1, the stronger the positive correlation. Values close to zero indicate a weak relationship between the variables [57].…”

Section: Methodsmentioning

confidence: 99%

Do Regional Smart Specialization Strategies Affect Innovation in Enterprises?

Kogut-Jaworska,

Ociepa-Kicińska

2023

Sustainability

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According to the European Commission, the smart specialization strategy is intended as a response to complex development challenges and a tool for stimulating innovation at the regional level. At the same time, it is known that the conditions in which businesses operate, including institutional framework, socio-economic aspects, infrastructure and forms of business support, do not always meet their needs. The research and analyses carried out in this study were aimed at testing the relationships mainly between the external activities that most create/develop innovation in enterprises, networking within the innovation ecosystem, and barriers inhibiting innovation development. For this purpose, 250 survey interviews were conducted with representatives of innovative enterprises from five regions in Poland. Our research and analyses have shown that regions make considerable efforts to comprehensively define rather complex RIS3 (Research and Innovation Smart Specialization Strategy) policy priorities, while in reality these priorities often do not coincide with the expectations of entrepreneurs.

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Section: Methodsmentioning

confidence: 99%

Do Regional Smart Specialization Strategies Affect Innovation in Enterprises?

Kogut-Jaworska,

Ociepa-Kicińska

2023

Sustainability

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“…The Spearman correlation coefficient has low computational complexity and a high sensitivity to data, and can effectively calculate the correlation between variables with different delay times. We use the Spearman correlation coefficient to find the time delay between each input parameter and the main steam temperature and main steam flow [32]. The Spearman correlation coefficient between the input variables and the output variables at different delay times is calculated, and the time with the highest value of the correlation coefficient is noted as the delay time between this input parameter and the output parameter.…”

Section: Calculation Of Delay Timementioning

confidence: 99%

Prediction of Main Parameters of Steam in Waste Incinerators Based on BAS-SVM

Chen¹,

Wang²,

Zhong³

et al. 2023

Sustainability

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The main steam parameters of a waste-to-energy plant are the key indicator of the safety and stability of its combustion process. Accurate prediction of the main steam parameters can help the control system to reasonably analyze the combustion conditions and, thus, to greatly improve the combustion efficiency. In this paper, we propose an optimized method for predicting the main steam parameters of waste incinerators. Firstly, a grey relational analysis (GRA) is used to obtain the ranking of the correlation degree between 114 characteristic variables in the furnace and the main steam parameters, and 13 characteristic variables are selected as model inputs. A Spearman-based time delay compensation method is proposed to effectively overcome the influence of time asynchrony on the prediction accuracy. At last, the beetle antennae search (BAS) optimized support vector machine (SVM) model is proposed. Taking advantage of the fast iteration of the beetle antennae search algorithm to find the key hyperparameters of the support vector machine, the optimized main steam parameter prediction model is finally obtained. The simulation results show that the prediction accuracy of this model is greatly improved compared with traditional neural network models, such as long short-term memory neural networks (LSTMs) and convolutional neural networks (CNNs), as well as a single SVM.

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“…For the unknown distribution of chemical composition ratio data, we need to do nonparametric tests on chemical composition and glass type separately according to glass weathering condition to make the identification results more precise [15]. The glass type is a nominal categorical variable and the chemical composition is a continuous data, so we mainly analyze Spearman correlation coefficient [16]. Spearman correlation coefficient for any chemical component in n samples is defined as [17]:…”

Section: Non-parametric Testsmentioning

confidence: 99%

Sub-Classification and Type Identification of Weathering Silicate Glasses Based on Spectral Clustering

Xie,

Tang,

et al. 2023

J. Phys.: Conf. Ser.

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Ancient glass products are often weathered to varying degrees after excavation. Detection and analysis of their chemical composition will help to study the ancient glass making process. In this paper, we take a group of ancient glass products as samples, and study the sub-classification and type identification of weathered silicate glasses. Firstly, we identify the main factor of glass weathering through chi-squared test and Fisher’s exact test, then conduct a significance test on the basis of preprocessing various data of glass cultural relics. Secondly, the glass samples are classified into high potassium glass and lead barium glass by spectral clustering method, and further sub-classified into eight classes. The sub-classes are named based on feature extraction, and the clustering quality is tested by contour coefficient. Finally, we analyze the chemical composition affecting the glass types by combining the non-parametric tests to identify the types of glass cultural relics by multiple linear regression with significance testing. In addition, correlation test, spectral clustering and multiple linear regression are used to study the sub-classification and type identification of weathered silicate glasses, which provides a reference for further study of ancient glass making process and weathering process.

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Application of Spearman’s Method for the Analysis of the Causes of Long-Term Post-Failure Downtime of City Buses

Cited by 10 publications

References 21 publications

Do Regional Smart Specialization Strategies Affect Innovation in Enterprises?

Do Regional Smart Specialization Strategies Affect Innovation in Enterprises?

Prediction of Main Parameters of Steam in Waste Incinerators Based on BAS-SVM

Sub-Classification and Type Identification of Weathering Silicate Glasses Based on Spectral Clustering

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