Sustainability Performance Indicators Construction with Using Neural Networks in Maple

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F15%3A43907324" target="_blank" >RIV/62156489:43110/15:43907324 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216305:26510/15:PU117620

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Sustainability Performance Indicators Construction with Using Neural Networks in Maple

Popis výsledku v původním jazyce

The construction of sustainability performance indicators with using neural networks is an appropriate path to measuring and optimizing sustainable corporate performance. It is described in the paper as a modern method of implementation of artificial intelligence methods. The potential of neural networks is presented in the field of the adaptation of the various company characteristics. There are discussed two nontrivially calculated indicators: the Economic Value Added (EVA) and the Cash Flow Return on Investment (CFROI). It is known that is sufficient to have the basis of knowledge of several samples, without the knowledge of the internal links, for neural network modelling. The user friendly mathematical software Maple is introduced for the solution of those tasks. Maple has become the strong computational tool of mathematical, financial and economic modelling in education, research and practice. It allows implementing the appropriate neural network, which would be used by company managers while maintaining the complexity of values and meaningful indicators of economic performance to remove their discovered disadvantage

Název v anglickém jazyce

Sustainability Performance Indicators Construction with Using Neural Networks in Maple

Popis výsledku anglicky

The construction of sustainability performance indicators with using neural networks is an appropriate path to measuring and optimizing sustainable corporate performance. It is described in the paper as a modern method of implementation of artificial intelligence methods. The potential of neural networks is presented in the field of the adaptation of the various company characteristics. There are discussed two nontrivially calculated indicators: the Economic Value Added (EVA) and the Cash Flow Return on Investment (CFROI). It is known that is sufficient to have the basis of knowledge of several samples, without the knowledge of the internal links, for neural network modelling. The user friendly mathematical software Maple is introduced for the solution of those tasks. Maple has become the strong computational tool of mathematical, financial and economic modelling in education, research and practice. It allows implementing the appropriate neural network, which would be used by company managers while maintaining the complexity of values and meaningful indicators of economic performance to remove their discovered disadvantage

Druh

D - Stať ve sborníku

CEP obor

AE - Řízení, správa a administrativa

OECD FORD obor

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Projekt

<a href="/cs/project/GA14-23079S" target="_blank" >GA14-23079S: Měření podnikové udržitelosti ve vybraných odvětvích</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Innovation Management and Sustainable Economic Competitive Advantage: From Regional Development to Global Growth

ISBN

978-0-9860419-5-2

ISSN

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e-ISSN

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Počet stran výsledku

11

Strana od-do

2035-2045

Název nakladatele

International Business Information Management Association (IBIMA)

Místo vydání

Norristown

Místo konání akce

Madrid

Datum konání akce

11. 11. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000366872700203