Path-Based Visibility Graph Kernel and Application for the Borsa Istanbul Stock Network

Akgüller, Ömer; Balcı, Mehmet Ali; Bătrâncea, Larissa; Găban, Lucian

doi:10.3390/math11061528

Cited by 11 publications

(5 citation statements)

References 38 publications

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“…As available in the literature, Soft mathematical methods with multilayer frameworks have been applied to solve several problems. For future investigation, these soft mathematical methods are applicable in solving new scientific problems [ [62] , [63] , [64] , [65] , [66] , [67] , [68] ]. These soft mathematical methods with complex networks are applicable in vast branches of science.…”

Section: Resultsmentioning

confidence: 99%

The use of polyurethane foam-sand mixtures in sandy embankment design- predicting seismic response using FEM, catastrophe theory, B-spline method, and artificial neural networks

Mughieda,

Namdar,

Nie

2024

Heliyon

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Section: Resultsmentioning

confidence: 99%

The use of polyurethane foam-sand mixtures in sandy embankment design- predicting seismic response using FEM, catastrophe theory, B-spline method, and artificial neural networks

Mughieda,

Namdar,

Nie

2024

Heliyon

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“…Horizontal visibility graphs (HVG) were introduced in [32] to simplify the previously described NVG. Visibility graphs (VG) reduce the complexity of calculations, which depends on time series, while preserving the accuracy of the results; see [36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Entropy-Based Classification of Time Series Using Visibility Graphs from Chaotic Maps

Conejero,

Velichko,

Garibo-i-Orts

et al. 2024

Mathematics

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The classification of time series using machine learning (ML) analysis and entropy-based features is an urgent task for the study of nonlinear signals in the fields of finance, biology and medicine, including EEG analysis and Brain–Computer Interfacing. As several entropy measures exist, the problem is assessing the effectiveness of entropies used as features for the ML classification of nonlinear dynamics of time series. We propose a method, called global efficiency (GEFMCC), for assessing the effectiveness of entropy features using several chaotic mappings. GEFMCC is a fitness function for optimizing the type and parameters of entropies for time series classification problems. We analyze fuzzy entropy (FuzzyEn) and neural network entropy (NNetEn) for four discrete mappings, the logistic map, the sine map, the Planck map, and the two-memristor-based map, with a base length time series of 300 elements. FuzzyEn has greater GEFMCC in the classification task compared to NNetEn. However, NNetEn classification efficiency is higher than FuzzyEn for some local areas of the time series dynamics. The results of using horizontal visibility graphs (HVG) instead of the raw time series demonstrate the GEFMCC decrease after HVG time series transformation. However, the GEFMCC increases after applying the HVG for some local areas of time series dynamics. The scientific community can use the results to explore the efficiency of the entropy-based classification of time series in “The Entropy Universe”. An implementation of the algorithms in Python is presented.

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“…The banking system is one of the most important economic sectors that play a very important role in the overall performance of economic systems in different countries [1][2][3][4][5][6][7][8][9][10][11]. The economic stability of a country is directly related to the stability and operational efficiency of a country's banking system, and the result of proper economic management is sustainable economic growth [12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Asset and Liability Management of Banks with Minimum Possible Changes

et al. 2023

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Asset-Liability Management (ALM) of banks is defined as simultaneous planning of all bank assets and liabilities under different conditions and its purpose is to maximize profits and minimize the risks in banks by optimizing the parameters in the balance sheet. Most of the studies `and proposed models in the ALM field are based on an objective function that maximizes bank profit. It is not easy to apply changes in these models in order to reach the optimal values of the parameters in the balance sheet. In this article, an attempt has been made to propose a linear model using constraints to achieve optimal values of balance sheet parameters using ALM objectives and considering balance sheet, system and regulatory constraints. It has also been tried to design the model according to the most possible mode and with the least changes and to minimize the size of the balance sheet. The analysis of the model presented in this article has been conducted using the parameters of the balance sheet and income statement of one of the famous Iranian banks. The results obtained from the proposed model show that the values of cash and receivables from banks and other credit institutions have decreased by 30% and increased by 200%, respectively, compared to the actual values of these parameters. Also, Total Income, Operating Income and Non-Operating Income have grown by 30% compared to the actual values of these parameters. Also, the values of a number of parameters are estimated to be zero after optimization. According to the results, it is obvious that the performance of bank managers, especially in the management of bank assets, is significantly different from the optimal values of the balance sheet, and the results obtained from the proposed model can help the management of banks as much as possible.

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Path-Based Visibility Graph Kernel and Application for the Borsa Istanbul Stock Network

Cited by 11 publications

References 38 publications

The use of polyurethane foam-sand mixtures in sandy embankment design- predicting seismic response using FEM, catastrophe theory, B-spline method, and artificial neural networks

The use of polyurethane foam-sand mixtures in sandy embankment design- predicting seismic response using FEM, catastrophe theory, B-spline method, and artificial neural networks

Exploring the Entropy-Based Classification of Time Series Using Visibility Graphs from Chaotic Maps

Optimization of Asset and Liability Management of Banks with Minimum Possible Changes

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