DocumentCode :
2623652
Title :
Using fuzzy rule based economic models to measure the performance of state funded agencies
Author :
Ammar, Salwa ; Wright, Ronald ; Leathley, Jennifer ; McDonnell, Ian
Author_Institution :
Dept. of Bus. Adm., LeMoyne Coll., Syracuse, NY, USA
fYear :
1997
fDate :
21-24 Sep 1997
Firstpage :
418
Lastpage :
422
Abstract :
US state governments have been seeking analytical methods to show that taxpayer dollars devoted to economic development are utilized effectively. In New York, efforts to quantify the increase in value added as a result of technology development have involved the use of multiple regression to analyze client surveys. In this paper, we describe work with one group of agencies to develop a fuzzy rule-based system. Initial results show that fuzzy models can outperform multiple regression when used on even terms and have the potential to substantially outperform regression models when used to their full advantage
Keywords :
economics; fuzzy logic; government data processing; knowledge based systems; statistical analysis; New York, USA; US state governments; added value; client survey analysis; fuzzy rule-based economic models; multiple regression; state-funded agency performance measurement; technology development; Costs; Educational institutions; Fuzzy systems; Government; Information analysis; Keyboards; Knowledge based systems; Marketing and sales; Performance analysis; Statistical analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American
Conference_Location :
Syracuse, NY
Print_ISBN :
0-7803-4078-7
Type :
conf
DOI :
10.1109/NAFIPS.1997.624077
Filename :
624077
Link To Document :
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