Analysis of resources distribution in economics based on entropy

Antoniou, Ioannis; Иванов, В. В.; Korolev, Yu.L; Kryanev, A. V.; Matokhin, Valentin V.; Suchanecki, Z.

doi:10.1016/s0378-4371(01)00575-1

Cited by 11 publications

(7 citation statements)

References 7 publications

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“…We apply a simplified method of constructing a Lorentz diagram for an arbitrary numerical series. Let us say, for example, the original number series (vector) has five elements (components) G′ = (3, 7, 10, 20, 60) and G′′ = (5,10,15,20,50). Calculate a number of accumulated partial sums {S n } using the following formulas:…”

Section: Lorentz's Diagram Of Arbitrary Numerical Seriesmentioning

confidence: 99%

Entropy approach to the analysis of banks’ balance sheets

Matokhin¹,

Sigal²

2023

Bus. Inform.

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Accounting ensures the collection and systematization of documented information about the facts of the economic life of enterprises and organizations. The information collected is systematized and formalized in various forms of reporting. One of the key forms of reporting is the balance sheet. The balance sheet is based on the principle of double entry, according to which each change in the financial resources of the organization is reflected in at least two accounts related assets and liabilities. Thus, the condition of the balance of the volumes of the generalized values of assets and liabilities is realized. The control element of the balance sheet is the equality of the values of assets and liabilities. However, this control element does not allow us to identify the systemic difference (diversity) of balance sheets with equality of distributed funds. Namely, the equality condition is integral in nature and its fulfillment is not related to the specific nature of item-by-item distributions, since, at a given size of the total cost of the balance sheet, the condition can be fulfilled by various options for the distribution of financial resources by assets and liabilities. Therefore, within the framework of this article, an attempt has been made to introduce a new control element of the balance sheet, taking into account the uneven distribution of financial resources by assets and liabilities of credit and financial organizations.

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Section: Lorentz's Diagram Of Arbitrary Numerical Seriesmentioning

confidence: 99%

Entropy approach to the analysis of banks’ balance sheets

Matokhin¹,

Sigal²

2023

Bus. Inform.

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“…Kåberger and Månsson (2001) provided a comparative analysis on the opposing views on the relationship between thermodynamics and economic theory i.e., whether the physical constraints have binding effects on economic growth or not. Antoniou et al, (2002) developed a novel approach to address the problem of efficient resource allocations in different types of economic systems and proposed that entropy should be an indicator of the efficiency of resource distribution. Zohrabian et al, (2003) applied a maximum entropy method to estimate the success probabilities of research on the economics of crop genetic diversity and gene bank management.…”

Section: Literature Reviewmentioning

confidence: 99%

Information entropy, continuous improvement, and US energy performance: a novel stochastic-entropic analysis for ideal solutions (SEA-IS)

2022

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Previous energy performance studies neglected the role of information entropy in feedback processes between input and output slacks. Superior energy performance may be achieved through the capability of learning from how increased outputs could yield reduced inputs and vice-versa. This paper focus on this gap, by presenting an assessment of US states for a 35-year period in lieu of relevant socio-economic and demographic variables. US is the world largest energy producer and consumer, being well-known not only for innovation in efficient energy use but also for managerial feedback mechanisms in the energy field which ensures continuous improvement in generation and consumption. First, a novel SEA-IS (Stochastic-Entropic Analysis for Ideal Solutions) model is developed to assess the potential information gains that may arise from energy slacks minimization given different optimal reduction quantiles in US states. This nonlinear stochastic optimization model not only relies on Beta distributed priors to model the odds-ratio of learning feedback but also takes advantages of numerous strengths present in DEA and TOPSIS approaches for performance management. Machine learning methods are also employed to predict information gains in terms of contextual variables. Results indicate that California is the only U.S. state that has indicate strong mutual information feedback and continuous improvements in efficiency. There is ample scope for harnessing the power of information gains in improving energy efficiency, particularly in 37 U.S. states, which indicates scope for a public-private partnership to achieve this goal.

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“…Amorocho further explained entropy as a measure of the degree of uncertainty of a particular outcome in a process. The entropy method has been widely applied in many fields, such as flood risk assessment and social economic analysis . In flood hazard studies, entropy can be used to assess the relative importance of model input indices (eigenvectors) by measuring the information contained in the indices.…”

Section: Framework Developmentmentioning

confidence: 99%

Integrating Entropy‐Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard

Chen

et al. 2016

Risk Analysis

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Regional flood risk caused by intensive rainfall under extreme climate conditions has increasingly attracted global attention. Mapping and evaluation of flood hazard are vital parts in flood risk assessment. This study develops an integrated framework for estimating spatial likelihood of flood hazard by coupling weighted naïve Bayes (WNB), geographic information system, and remote sensing. The north part of Fitzroy River Basin in Queensland, Australia, was selected as a case study site. The environmental indices, including extreme rainfall, evapotranspiration, net-water index, soil water retention, elevation, slope, drainage proximity, and density, were generated from spatial data representing climate, soil, vegetation, hydrology, and topography. These indices were weighted using the statistics-based entropy method. The weighted indices were input into the WNB-based model to delineate a regional flood risk map that indicates the likelihood of flood occurrence. The resultant map was validated by the maximum inundation extent extracted from moderate resolution imaging spectroradiometer (MODIS) imagery. The evaluation results, including mapping and evaluation of the distribution of flood hazard, are helpful in guiding flood inundation disaster responses for the region. The novel approach presented consists of weighted grid data, image-based sampling and validation, cell-by-cell probability inferring and spatial mapping. It is superior to an existing spatial naive Bayes (NB) method for regional flood hazard assessment. It can also be extended to other likelihood-related environmental hazard studies.

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Analysis of resources distribution in economics based on entropy

Cited by 11 publications

References 7 publications

Entropy approach to the analysis of banks’ balance sheets

Entropy approach to the analysis of banks’ balance sheets

Information entropy, continuous improvement, and US energy performance: a novel stochastic-entropic analysis for ideal solutions (SEA-IS)

Integrating Entropy‐Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard

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