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Mathematical Models, Methods and Applications pp 31–40Cite as

Soft Computing Techniques and Their Applications

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Part of the book series: Industrial and Applied Mathematics ((INAMA))

Abstract

The modern science is still striving to develop consciousness-based machine. The forecasting is an intuition-based or consciousness-based problem. It is an important problem for planning, decision-making and designing of an appropriate controller for the systems. The paper deals with the synergism of soft computing techniques mainly artificial neural network, fuzzy logic systems, and genetic algorithms and their applications in forecasting.

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References

  1. Chaturvedi DK (2008) Soft computing techniques and applications to electrical engineering. Springer

    Google Scholar 

  2. Chaturvedi DK, Satsangi PS, Kalra PK (1999) New neuron model for simulating rotating electrical machines and load forecasting problems. Int J Elect Power Syst Res Elsevier Science, Ireland 52:123–131

    Google Scholar 

  3. Chaturvedi DK, Satsangi PS, Kalra PK (2001) Fuzzified neural network approach for load forecasting problems. Int J Eng Intell Syst CRL Publishing, UK 9(1):3–9

    Google Scholar 

  4. Chaturvedi DK, Kumar R, Mohan M, Kalra PK (2001) Artificial neural network learning using improved genetic algorithm. J IE(I), EL, 82

    Google Scholar 

  5. Chaturvedi DK, Mohan M, Singh RK, Kalra PK (2004) Improved generalized neuron model for short term load forecasting. Int J Soft Computing—A Fusion of Foundations, Methodologies and Applications, Springer-Verlag Heidelberg 8(1):10–18

    Google Scholar 

  6. Chaturvedi DK, Satsangi PS, Kalra PK (1997) Short term load forecasting using generalized neural network (GNN) approach. J Inst Eng (India) 78:83–87

    Google Scholar 

  7. Chaturvedi DK (2009) Modeling and simulation of systems using MATLAB® and Simulink®. CRC Press (2009)

    Google Scholar 

  8. Chaturvedi DK, Premdayal SA, Chandiok A (2010) Load forecasting using soft computing. Int J Commun Netw Syst Sci 3:273–279

    Google Scholar 

  9. Chaturvedi DK, Singh AP (2011) Evapotranspiration model for irrigation scheduling. Int J Math Sci Appl 2(1):393–399

    Google Scholar 

  10. Chaturvedi DK, Premdayal SA (2012) Neural-wavelet based hybrid model for shortterm load forecasting. In: Proceedings of national conference on emerging trends in electrical, instrumentation and communication engineering (ETEIC—2012), Agra, 6th and 7th April 2012, pp 359–362

    Google Scholar 

  11. Chaturvedi DK, Chandiok A, Kamaruddin M (2009) Fuzzy system model of internet system exploitation and usage in society. IEEE Int Conf Innov Technol (IEEE- IMS/EMBS2009), New Delhi, 18–19th June 2009

    Google Scholar 

  12. Chaturvedi DK, Chandiok A, Siddiqui AH (2009) Prediction for the time series of annual rainfall using wavelets and neuro-fuzzy approach. Int workshop on Wavelets, Istanbul, Turkey, 4–7th June 2009

    Google Scholar 

  13. Chaturvedi DK, Siddiqi AH, Chandiok A, Agarwal S (2009) Annual rainfall forecasting using soft computing techniques. In: Proceedings of joint international conference on applied systems research and national systems conference, (NSC) Nov. 27–29, 2009 organized by D.E.I. (Deemed Univ.) Dayalbagh, Agra, India, TMH-2009:103–106

    Google Scholar 

  14. Banakar MFAA (2008) Artificial wavelet neural network and its application in Neurofuzzy models. Elsevier Appl Soft Comput

    Google Scholar 

  15. Sinha N, Lai LL, Ghosh PK, Yingnan M (2007) Wavelet-GA-ANN based hybrid model for accurate prediction of short-term load forecast. In: Proceedings international conference on intelligent systems applications to power systems (ISAP), 5–8 Nov, pp 1–8

    Google Scholar 

  16. Minsky M, Papert S (1968) Perceptions. The MIT Press, Cambridge, MA

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, D.E.I. (Deemed University), Dayalbagh, Agra, India

    D. K. Chaturvedi

Authors
  1. D. K. Chaturvedi
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Correspondence to D. K. Chaturvedi .

Editor information

Editors and Affiliations

  1. School of Basic Sciences and Research, Sharda University, Greater Noida, Uttar Pradesh, India

    Abul Hasan Siddiqi

  2. Guru Nanak Dev University, Amritsar, Punjab, India

    Pammy Manchanda

  3. University, Guru Gobind Singh Indraprastha, Dwarka, India

    Rashmi Bhardwaj

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© 2015 Springer Science+Business Media Singapore

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Chaturvedi, D.K. (2015). Soft Computing Techniques and Their Applications. In: Siddiqi, A., Manchanda, P., Bhardwaj, R. (eds) Mathematical Models, Methods and Applications. Industrial and Applied Mathematics. Springer, Singapore. https://doi.org/10.1007/978-981-287-973-8_2

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