Provider: - Institution: - Data provided by Europeana Collections- Vrednovanje poduzeća naftne i plinske industrije po mnogim je čimbenicima specifično i teško izvedivo postojećom metodologijom i trenutno korištenim pristupima vrednovanju. Identifikacija i ocjena čimbenika koji stvaraju i pokreću vrijednost poduzeća naftne i plinske industrije temelji se na složenim izračunima koji uključuju mnoge varijable. Međuovisnost tih varijabli prekompleksna je da bi se izrazila jednostavnom formulom. Iz tih se razloga kod vrednovanja ovakvih poduzeća postojeće metode vrednovanja moraju prilagođavati čime se u konačnici brojni kvalitativni, pa čak i kvantitativni čimbenici uopće ne uzimaju u obzir. Pred ekonomske stručnjake i znanstvenike s područja vrednovanja postavljaju se tako novi izazovi u determiniranju odgovarajuće metodologije i pristupa kojima će se moći otkloniti navedeni nedostaci. U ovom doktorskom radu predložen je suvremeni pristup vrednovanju poduzeća naftne i plinske industrije na osnovi računalne inteligencije. Takav pristup temeljen je na korištenju i prilagodbi brojnih financijskih i nefinancijskih pokazatelja pomoću umjetnih neuronskih mreža i neizrazite logike.- Business valuation of oil and gas companies can be described as specific and difficult in many aspects within existing methodology and currently used approaches in appraisal process. Identification and evaluation of the significant factors that create and determine enterprise value in oil and gas industry is based on complex calculations involving many variables. Regardless of this reason, existing business valuation methods for such companies have to be improved with taking into account a numerous qualitative and even additional quantitative factors. Therefore, economic experts and scientists in the field of business valuation are confronted with new challenges in determination of appropriate approaches that should be able to eliminate the disadvantages of existing valuation methods. In this doctoral thesis, a modern approach to business valuation of oil and gas companies based on computational intelligence has been suggested. This approach includes application and adaption of selected financial and non-financial indicators by means of artificial neural networks and fuzzy logic- All metadata published by Europeana are available free of restriction under the Creative Commons CC0 1.0 Universal Public Domain Dedication. However, Europeana requests that you actively acknowledge and give attribution to all metadata sources including Europeana