nach oben

Neural Computing and Applications

Erschienen in:

01.11.2012 | Original Article

Integrated fuzzy-connective-based aggregation network with real-valued genetic algorithm for quality of life evaluation

verfasst von: Chao-Ton Su, Fang-Fang Wang

Erschienen in: Neural Computing and Applications | Ausgabe 8/2012

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Quality of life evaluation is important in national goal setting, program benefit evaluation, and priority ranking of resource allocation. However, the relationship between individual measures and overall evaluation of the quality of life is highly complex. The effectiveness of integrating fuzzy-connective-based aggregation network with real-valued genetic algorithm (GA) in quality of life evaluation is investigated. The fuzzy-connective-based aggregation network aggregates the relative status or achievement among states in quality of life-related variables through a hierarchical decision-making structure. The aggregation network then produces an overall quality of life evaluation from various aspects. Integration with real-valued GA helps avoid stopping at local solutions, as experienced by conventional fuzzy-connective-based aggregation networks. The drawbacks in binary GA are also prevented. The effectiveness and applicability of integrating fuzzy-connective-based aggregation networks with real-valued GA for quality of life evaluation is confirmed through statistical analysis.

Vorheriger Artikel Speech emotion recognition using FCBF feature selection method and GA-optimized fuzzy ARTMAP neural network

Nächster Artikel Semantic real-world image classification for image retrieval with fuzzy-ART neural network

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Chang CA, Su CT (1995) A comparison of statistical regression and neural network methods in modeling measurement errors for computer vision inspection systems. Comput Ind Eng 28:593–603CrossRef

Grabisch M, Marichal JL, Mesiar R, Pap E (1992) Aggregation functions. Cambridge University Press, New York

Chiang JH, Chen YC (2002) Incorporating fuzzy operators in the decision network to improve classification reliability. Comput Electr Eng 28:547–560MATHCrossRef

Krishnapuram R, Lee J (1992) Fuzzy-connective-based hierarchical aggregation networks for decision making. Fuzzy Set Syst 46:11–27MathSciNetCrossRef

Krishnapuram R, Lee J (1992) Fuzzy-set-based hierarchical networks for information fusion in computer vision. Neural Netw 5:335–350CrossRef

Torra V (2003) Information fusion in data mining. Springer, New YorkMATH

Sexton RS, Dorsey RE, Johnson JD (1998) Toward global optimization of neural networks: a comparison of the genetic algorithm and backpropagation. Decis Support Syst 22:171–185CrossRef

Venkatesan D, Kannan K, Saravanan R (2009) A genetic algorithm-based artificial neural network model for the optimization of machining processes. Neural Comput Appl 18:135–140CrossRef

Liang YH (2009) Combining seasonal time series ARIMA method and neural networks with genetic algorithms for predicting the production value of the mechanical industry in Taiwan. Neural Comput Appl 18:833–841CrossRef

10.

Leung KF, Leung FHF, Lam HK, Ling SH (2007) Application of a modified neural fuzzy network and an improved genetic algorithm to speech recognition. Neural Comput Appl 16:419–431CrossRef

11.

Wu CH, Tzeng GH, Goo YJ, Fang WC (2007) A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy. Expert Syst Appl 32:397–408CrossRef

12.

Pan WT (2009) Forecasting classification of operating performance of enterprises by ZSCORE combining ANFIS and genetic algorithm. Neural Comput Appl 18:1005–1011CrossRef

13.

Dyckhoff H, Pedrycz W (1984) Generalized means as a model of compensation connectives. Fuzzy Set Syst 14:143–154MathSciNetMATHCrossRef

14.

Zimmermann HJ, Zysno P (1980) Latent connectives in human decision making. Fuzzy Set Syst 4:37–51MATHCrossRef

15.

Rumelhart DE, McClelland JM, the PDP Research Group (1986) Parallel distributed processing. The MIT Press, Cambridge

16.

Zimmermann HJ, Zysno P (1983) Decision and evaluations by hierarchical aggregation of information. Fuzzy Set Syst 10:243–260MATHCrossRef

17.

Zimmermann HJ (1991) Fuzzy set theory and its applications, 2nd edn. Maw Chang Book Company, TaipeiMATH

18.

Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, New YorkMATH

19.

Holland JH (1975) Adaption in natural and artificial systems. The University of Michigan Press, Ann ArborMATH

20.

Herrera F, Lozano M, Verdegay JL (1998) Tackling real-coded genetic algorithms: operators and tools for behavioral analysis. Artif Intell Rev 12:265–319MATHCrossRef

21.

Dorsey RE, Mayer WJ (1995) Genetic algorithms for estimation problems with multiple optima, nondifferentiability, and other irregular features. J Bus Econ Stat 13(1):53–66

22.

Su MC, Chang HT (2000) Application of neural networks incorporated with real-valued genetic algorithms in knowledge acquisition. Fuzzy Set Syst 112:85–97CrossRef

23.

Haupt RL, Haupt SE (2004) Practical genetic algorithms, 2nd edn. Wiley, New JerseyMATH

24.

Sivanandam SN, Deepa SN (2008) Introduction to genetic algorithms. Springer, New YorkMATH

25.

Wright AH (1991) Genetic algorithms for real parameter optimization. In: Rawlin GJE (ed) Foundations of genetic algorithms. Morgan Kaufmann, San Mateo, pp 205–218

26.

Michalewicz Z (1992) Genetic algorithms + data structures = evolution programs. Springer, New YorkMATH

27.

De Jong KA (1975) An analysis of the behavior of a class of genetic adaptive systems. Dissertation, University of Michigan

28.

Liu BC (1988) Energy, income, and quality of life management in USA: an information systems approach to decision analysis. Tamkang University, Taipei

29.

Herrera EW, Islam G, Hamilton M (2009) Subjective well-being in cities: a multidimensional concept of individual, social and cultural variables. Appl Res Qual Life 4:201–221CrossRef

30.

Cracolici MF, Giambona F, Cuffaro M (2011) The determinants of subjective economic well-being: an analysis on Italian–Silc data. Appl Res Qual Life. doi:10.1007/s11482-011-9140-z

31.

Yonk RM, Reilly S (2011) Citizen involvement & quality of life: exit, voice and loyalty in a time of direct democracy. Appl Res Qual Life. doi:10.1007/s11482-011-9142-x

32.

Nzeadibe TC, Ajaero CK (2010) Assessment of socio-economic characteristics and quality of life expectations of rural communities in Enugu State, Nigeria. Appl Res Qual Life 5:353–371CrossRef

33.

Farooq U, Guo X, Chuang LH, Fang H, Zhuang G, Xia C (2011) Measuring health-related quality of life in Kashin–Beck disease using EQ-5D. Qual Life Res 20:425–429CrossRef

34.

Liu Z, Liu A, Wang C, Niu Z (2004) Evolving neural network using real coded genetic algorithm (GA) for multispectral image classification. Future Gener Comput Syst 20:1119–1129CrossRef

Titel: Integrated fuzzy-connective-based aggregation network with real-valued genetic algorithm for quality of life evaluation
verfasst von: Chao-Ton Su
Fang-Fang Wang
Publikationsdatum: 01.11.2012
Verlag: Springer-Verlag
Erschienen in: Neural Computing and Applications / Ausgabe 8/2012
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-011-0644-0

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 8/2012

Construction of gene regulatory networks with colored noise

A novel data preprocessing method to estimate the air pollution (SO2): neighbor-based feature scaling (NBFS)

Hypervolume-based multi-objective local search

Usage of output-dependent data scaling in modeling and prediction of air pollution daily concentration values (PM10) in the city of Konya

A novel approach to accelerate the convergence speed of a stochastic multi-agent system using recurrent neural nets

Comparison of stochastic optimization methods for design optimization of permanent magnet synchronous motor

Premium Partner