nach oben

Quality & Quantity

Erschienen in:

17.03.2016

RETRACTED ARTICLE: Analyzing of innovations influence on economic growth by fuzzy system

verfasst von: Igor Mladenović, Miloš Milovančević, Svetlana Sokolov-Mladenović

Erschienen in: Quality & Quantity | Ausgabe 3/2017

Einloggen

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

search-config

KI-gestützte Suche

Aus

Abstract

Economic growth may be developed on the basis on combination of different factors. In this investigation was analyzed the economic growth prediction based on the innovations by field of technology. Gross domestic product (GDP) was used as economic growth indicator. The method of adaptive neuro fuzzy inference system (ANFIS) was applied to the data in order to detect the influential parameters for the GDP prediction. Five inputs are considered: number of granted patents in electrical engineering, number of granted patents as instruments, number of granted patents in chemistry, number of granted patents in mechanical engineering and the number of granted patents in other fields. Results shown that the innovations in electrical engineering has the highest influence on the GDP prediction.

Vorheriger Artikel Rhetorical manifestation of institutional transformation

Nächster Artikel Learning organization at higher education institutions in the EU: proposal for implementing philosophy of learning organization—results from research

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

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

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

Al-Ghandoor, A., Samhouri, M.: Electricity consumption in the industrial sector of Jordan: application of multivariate linear regression and adaptive neuro-fuzzy techniques. Jordan J. Mech. Ind. Eng. 3(1), 69–76 (2009)

Barsoum, F., Stankiewicz, S.: Forecasting GDP growth using mixed-frequency models with switching regimes. Int. J. Forecast. 31, 33–50 (2015)CrossRef

Dias, F., Pinheiro, M., Rua, A.: Forecasting Portuguese GDP with factor models: pre- and post-crisis evidence. Econ. Model. 44, 266–272 (2015)CrossRef

Ekici, B.B., Aksoy, U.T.: Prediction of building energy needs in early stage of design by using ANFIS. Expert Syst. Appl. 38, 5352 (2011)CrossRef

Feng, L., Zhang, J.: Application of artificial neural networks in tendency forecasting of economic growth. Econ. Model. 40, 76–80 (2014)CrossRef

Ferrarini, B., Scaramozzino, P.: Production complexity, adaptability and economic growth. Struct. Change Econ. Dyn. 37, 52–61 (2016)CrossRef

Inal, M.: Determination of dielectric properties of insulator materials by means of ANFIS: a comparative study. Expert Syst. Appl. 195, 34 (2008)

IPC-Technology Conordance Table. www.wipo.int/ipstats/en/statistics/patents/pdf/wipo_ipc_technology.pdf

Jang, J.-S.R.: ANFIS: adaptive-network-based fuzzy inference systems. IEEE Trans. Syst. Man Cybern. 23, 665–685 (1993)CrossRef

Jansen, W.J., Jin, X., De Winter, J.: Forecasting and nowcasting real GDP: comparing statistical models and subjective forecasts. Int. J. Forecast. 32, 411–436 (2016)CrossRef

Kapetanios, G., Marcellino, M., Papailias, F.: Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods. Comput. Stat. Data Anal. (2015). doi:10.1016/j.csda.2015.02.017 CrossRef

Khajeh, A., Modarress, H., Rezaee, B.: Application of adaptive neuro-fuzzy inference system for solubility prediction of carbon dioxide in polymers. Expert Syst. Appl. 36, 5728 (2009)CrossRef

Krkoska, L., Teksoz, U.: Accuracy of GDP growth forecasts for transition countries: ten years of forecasting assessed. Int. J. Forecast. 23, 29–45 (2007)CrossRef

Krkoska, L., Teksoz, U.: How reliable are forecasts of GDP growth and inflation for countries with limited coverage? Econ. Syst. 33, 376–388 (2009)CrossRef

Kurnaz, S., Cetin, O., Kaynak, O.: Adaptive neuro-fuzzy inference system based autonomous flight control of unmanned air vehicles. Expert Syst. Appl. 37, 1229–1234 (2010)CrossRef

Lo, S.P., Lin, Y.Y.: The prediction of wafer surface non-uniformity using FEM and ANFIS in the chemical mechanical polishing process. J. Mater. Process. Technol. 168, 250 (2005)CrossRef

Modis, T.: Long-term GDP forecasts and the prospects for growth. Technol. Forecast. Soc. Change 80, 1557–1562 (2013)CrossRef

Petković, D.: Adaptive neuro-fuzzy fusion of sensor data. Infrared Phys. Technol. 67, 222–228 (2014). doi:10.1016/j.infrared.2014.07.031 CrossRef

Petković, D.: Adaptive neuro-fuzzy approach for estimation of wind speed distribution. Electr. Power Energy Syst. 73, 389–392 (2015a). doi:10.1016/j.ijepes.2015.05.039 CrossRef

Petković, D.: Adaptive neuro-fuzzy optimization of the net present value and internal rate of return of a wind farm project under wake effect. JCC Bus. Econ. Res. J. 8, 11–28 (2015b). doi:10.7835/jcc-berj-2015-0102 CrossRef

Petković, D., Ćojbašić, Ž.: Adaptive neuro-fuzzy estimation of automatic nervous system parameters effect on heart rate variability. Neural Comput. Appl. 21(8), 2065–2070 (2012)CrossRef

Petković, D., Pavlović, N.D.: Applications and adaptive neuro-fuzzy estimation of conductive silicone rubber properties. Strojarstvo: časopis za teoriju i praksu u strojarstvu 54(3), 197–203 (2013)

Petković, D., Issa, M., Pavlović, N.D., Pavlović, N.T., Zentner, L.:Adaptive neuro-fuzzy estimation of conductive silicone rubber mechanical properties. Expert Syst. Appl. 39, 9477–9482 (2012). ISSN:0957-4174

Petković, D., Issa, M., Pavlović, N.D., Zentner, L., Ćojbašić, Ž.:Adaptive neuro fuzzy controller for adaptive compliant robotic gripper. Expert Syst. Appl. 39, 13295–13304 (2012). ISSN: 0957-4174

Petković, D., Issa, M., Pavlović, N.D., Pavlović, T.N., Zentner, L.: Adaptive neuro-fuzzy estimation of conductive silicone rubber mechanical properties. Expert Syst. Appl. 39(10), 9477–9482 (2012a)CrossRef

Petković, D., Issa, M., Pavlović, N.D., Zentner, L., Ćojbašić, Ž.: Adaptive neuro fuzzy controller for adaptive compliant robotic gripper. Expert Syst. Appl. 39(18), 13295–13304 (2012b)CrossRef

Petković, D., Pavlović D, N.D., Ćojbašić, Ž., Pavlović, N.T.: Adaptive neuro fuzzy estimation of underactuated robotic gripper contact forces. Expert Syst. Appl. 40(1), 281–286 (2013a)CrossRef

Petković, D., Ćojbašić, Ž., Lukić, S.: Adaptive neuro fuzzy selection of heart rate variability parameters affected by autonomic nervous system. Expert Syst. Appl. 40(11), 4490–4495 (2013b)CrossRef

Petković, D., Ćojbašić, Ž., Nikolić, V.: Adaptive neuro-fuzzy approach for wind turbine power coefficient estimation. Renew. Sustain. Energy Rev. 28, 191–195 (2013c)CrossRef

Petković, D., Pavlović, N.T., Shamshirband, S., Kiah, M.L.M., Anuar, N.B., Idris, M.Y.I.: Adaptive neuro-fuzzy estimation of optimal lens system parameters. Opt. Lasers Eng. 55, 84–93 (2014a)CrossRef

Petković, D., Ćojbašić, Ž., Nikolić, V., Shamshirband, S., Kiah, M.L.M., Anuar, N.B., Wahab, A.W.A.: Adaptive neuro-fuzzy maximal power extraction of wind turbine with continuously variable transmission. Energy 64, 868–874 (2014b)CrossRef

Petković, D., Shamshirband, S., Pavlović, T.N., Anuar, N.B., Kiah, M.L.M.: Modulation transfer function estimation of optical lens system by adaptive neuro-fuzzy methodology. Opt. Spectrosc. 117(1), 121–131 (2014c). doi:10.7868/S0030403414070046 CrossRef

Petković, D., Shamshirband, S., Anuar, N.B., Nasir, M.H.N.M., Pavlović, N.T., Akib, S.: Adaptive neuro-fuzzy prediction of modulation transfer function of optical lens system. Infrared Phys. Technol. 65, 54–60 (2014d). doi:10.7868/S0030403414070046 CrossRef

Petković, D., Shamshirband, S., Ćojbašić, Ž., Nikolić, V., Anuar, N.B., Sabri, A.Q.M., Akib, S.: Adaptive neuro-fuzzy estimation of building augmentation of wind turbine power. Comput. Fluids 97, 188–194 (2014e)CrossRef

Petković, D., Shamshirband, S., Iqbal, J., Anuar, N.B., Pavlović, N.D., Kiah, M.L.M.: Adaptive neuro-fuzzy prediction of grasping object weight for passively compliant gripper. Appl. Soft Comput. 22, 424–431 (2014f)CrossRef

Petković, D., Issa, M., Pavlović, N.D., Zentner, L., Nor Ridzuan Daud, M., Shamshirband, S.: Contact positions estimation of sensing structure using adaptive neuro-fuzzy inference system. Kybernetes 43(5), 783–796 (2014g)CrossRef

Petković, D., Shamshirband, S., Pavlović, N.D., Saboohi, H., Altameem, T.A., Gani, A.: Determining the joints most strained in an underactuated robotic finger by adaptive neuro-fuzzy methodology. Adv. Eng. Softw. 77, 28–34 (2014h)CrossRef

Petković, D., Shamshirband, S., Anuar, N.B., Naji, S., Kiah, M.L.M., Gani, A.: Adaptive neuro-fuzzy evaluation of wind farm power production as function of wind speed and direction. Stoch. Environ. Res. Risk Assess. 29(3), 793–802 (2015a). doi:10.1007/s00477-014-0901-8 CrossRef

Petković, D., Issa, M., Pavlović, N.D., Zentner, L.: Potential of adaptive neuro-fuzzy inference system for contact positions detection of sensing structure. Measurement 61, 234–242 (2015b). doi:10.1016/j.measurement.2014.10.040 CrossRef

Petković, D., Shamshirband, S., Anuar, N.B., Sabri, A.Q.M., Rahman, Z.B.A., Pavlović, N.D.: Input displacement neuro-fuzzy control and object recognition by compliant multi-fingered passively adaptive robotic gripper. J. Intell. Robot. Syst. (2015c). doi:10.1007/s10846-015-0182-6 CrossRef

Petković, D., Shamshirband, S., Tong, C.W., Al-Shammari, E.T.: Generalized adaptive neuro-fuzzy based method for wind speed distribution prediction. Flow Meas. Instrum. 43, 47–52 (2015d). doi:10.1016/j.flowmeasinst.2015.03.003 CrossRef

Petković, D., Gocić, M., Trajković, S., Shamshirband, S., Motamedi, S., Hashim, R., Bonakdari, H.: Determination of the most influential weather parameters on reference evapotranspiration by adaptive neuro-fuzzy methodology. Comput. Electron. Agric. 114, 277–284 (2015e). doi:10.1016/j.compag.2015.04.012 CrossRef

Petković, D., Shamshirband, S., Abbasi, A., Kiani, K., Al-Shammari, E.T.: Prediction of contact forces of underactuated finger by adaptive neuro fuzzy approach. Mech. Syst. Signal Process. 64–65, 520–527 (2015f). doi:10.1016/j.ymssp.2015.03.013 CrossRef

Singh, R., Kianthola, A., Singh, T.N.: Estimation of elastic constant of rocks using an ANFIS approach. Appl. Soft Comput. 12, 40–45 (2012)CrossRef

Tian, L., Collins, C.: Adaptive neuro-fuzzy control of a flexible manipulator. Mechatronics 15, 1305–1320 (2005)CrossRef

Zeira, J., Zoabi, H.: Economic growth and sector dynamics. Eur. Econ. Rev. 79, 1–15 (2015)CrossRef

Titel: RETRACTED ARTICLE: Analyzing of innovations influence on economic growth by fuzzy system
verfasst von: Igor Mladenović
Miloš Milovančević
Svetlana Sokolov-Mladenović
Publikationsdatum: 17.03.2016
Verlag: Springer Netherlands
Erschienen in: Quality & Quantity / Ausgabe 3/2017
Print ISSN: 0033-5177
Elektronische ISSN: 1573-7845
DOI: https://doi.org/10.1007/s11135-016-0331-4

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+Technik"

Springer Professional "Wirtschaft"

Weitere Artikel der Ausgabe 3/2017

The dynamic of the gender gap in the European labour market in the years of economic crisis

Quantifying the economic cost of children: a note on intertemporal equivalence scales

A semantic annotation framework for scientific publications

Estimation of the most influential science and technology factors for economic growth forecasting by soft computing technique

Rhetorical manifestation of institutional transformation

Triple helix dynamics of South Korea’s innovation system: a network analysis of inter-regional technological collaborations