DocumentCode :
1799967
Title :
Estimating profitability using a neural classification tool
Author :
Nastac, Dumitru I. ; Dragan, Irina M. ; Isaic-Maniu, Alexandru
Author_Institution :
Dept. of Electron., Telecommun. & Inf. Technol., Politeh. Univ. of Bucharest, Bucharest, Romania
fYear :
2014
fDate :
25-27 Nov. 2014
Firstpage :
111
Lastpage :
114
Abstract :
The analysis of the private sector, mainly composed of micro, small and medium-sized business, briefly known as the SMEs sector, reveals many competitive aspects but also weaknesses, while the economic and social importance of the sector makes it imperative to elaborate specific development and consolidation strategies and policies. In order to establish such strategic directions, based on data on a significant volumes of Romanian SMEs (7902 entries) and on information provided by annual balance sheets, we established connections between results indicators (profit, measured as the rate of commercial profitability) and various causal variables by using a neural classification tool, which was built in accordance to testing and validation requirements in order to obtain consistent results.
Keywords :
economics; estimation theory; neural nets; profitability; small-to-medium enterprises; social sciences; SME; economic; microbusiness; neural classification tool; private sector; profitability; small and medium-sized business; social importance; Algorithm design and analysis; Artificial neural networks; Companies; Economics; Neurons; Training; SMEs; classification; neural networks; test; training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Network Applications in Electrical Engineering (NEUREL), 2014 12th Symposium on
Conference_Location :
Belgrade
Print_ISBN :
978-1-4799-5887-0
Type :
conf
DOI :
10.1109/NEUREL.2014.7011474
Filename :
7011474
Link To Document :
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