Implementation & Simulation of Fuzzy Logic Controllers for Productivity and Fertility of Soil and Performance Evaluation of Triangular Membership Function

Authors

  • Mawale MV Department of Computer Science & IT, Adarsha Science J.B. Arts and Birla Commerce Mahavidyalaya, Dhamangaon Rly-444709 (India) M.S
  • Chavan V Associate prof. Dept. Of Computer Science and IT, Seth Kesarimal Porwal College, Kamptee, Nagpur M.S.

Keywords:

Fuzzy logic control, Mamdani model, Simulink model, soil productivity

Abstract

As soil is complex system and soil fertility represents crop productivity and soil productivity hence MIMO system is a necessity of fuzzy logic controller model design using simulation technique. Same model gives prediction of lots of problem and save development time. Modelling and simulation tools made a dynamic evolution in the design and control of prediction system. The basic requirements of prediction system are accuracy in result. The objective of this paper is to investigate the effect of triangular membership functions in the developed Simulink model of Mamdani model based fuzzy control for prediction of soil productivity. The built in membership functions of Matlab is selected for evaluation. The evaluation is done using the developed 207 fuzzy rules through the implementation in Matlab/Simulink model. The results of all soil parameter are analysed. The performances of triangular membership functions on mamdani model based fuzzy control starting currents are concerned for the developed model.

References

Xin-she Yanga,SlawomirKozielb and LeifurLeifssonb Computational Optimization, Modelling andSimulation:Recent Trends and Challenges, Procedia Computer Science, 18,855 – 860.

J. C. Ascough, H.R. Maier, J.K. Ravalico, M.W. Strudley Future research challenges for incorporation of uncertainty ecological modeling, 219, pp 383–399, 2008.

Kailan Shang, ZakirHossen, Applying Fuzzy Logic to Risk Assessment and Decision-Making, November 2013.

Xin-she Yanga,SlawomirKozielb and LeifurLeifssonb Computational Optimization, Modelling andSimulation:Recent Trends and Challenges, Procedia Computer Science, 18,855 – 860.

Dr. David A. Cook, New trends, technologies and tools inModeling Simulation

Xin-she Yanga,SlawomirKozielb and LeifurLeifssonbComputational Optimization, Modelling and Simulation Recent Trends and Challenges, Procedia Computer Science 18 (2013) 855 – 860.

SandeepKaur, GurpreetBharti, Two Inputs Two Output Fuzzy Controller System Design using MATLAB, IJAEST Vol. 2 No. 3 Aug-Oct 2012 Vol. 2 No. 3, Aug-Oct 2012.

Feng Qi, A-Xing Zhu, Mark Harrower,James E. Bur, Fuzzy soil mapping based on prototype category theory.

http://www.ncagr.gov/cyber/kidswrld/plant/nutrient.ht m

Rizwan Khalid, Tariq Mahmood, RiffatBibi, Muhammad Tariq Siddique, SaroshAlvi and ShahidYaqubNaz, Distribution and indexation of plant available nutrients of rainfed calcareous soils of Pakistan, Soil Environ. 31(2): 146-151, 2012.

Nevcihan Duru, a Funda D¨okmen, bMM, ucella Canbayc and Cengiz Kurtulus¸c, Soil productivity analysis based on a fuzzy logic system J Sci Food Agric 2010; 90: 2220–2227.

Downloads

Published

2024-02-26

How to Cite

Mawale, M. V., & Chavan, V. (2024). Implementation & Simulation of Fuzzy Logic Controllers for Productivity and Fertility of Soil and Performance Evaluation of Triangular Membership Function. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(09), 1098–1102. Retrieved from https://ijact.in/index.php/j/article/view/194

Issue

Section

Original Research Article

Similar Articles

<< < 14 15 16 17 18 19 

You may also start an advanced similarity search for this article.