EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 398 (2023) E3S Web Conf., 398 (2023) 01002 References
Open Access
Issue
E3S Web Conf.
Volume 398, 2023
International Conference on Advances in Agrobusiness and Biotechnology Research (ABR 2023)
Article Number 01002
Number of page(s) 7
DOI https://doi.org/10.1051/e3sconf/202339801002
Published online 22 June 2023
  1. Zadeh, L. Knowledge representation in fuzzy logic // An Introduction to Fuzzy Logic Applications in Intelligent Systems, The Springer International Series in Engineering and Computer Science. New York: Springer, 1992. vol. 165. P. 1–27. [Google Scholar]
  2. Averkin A. N. Nechetkie mnojestva v modelyah upravleniya i iskusstvennogo intellekta (Fuzzy sets in the models of management and artificial intelligence). Book on demand, Moscow. 2021. 312 p. (in Russ.) [Google Scholar]
  3. Piegat, A.: Nechetkoe modelirovanie i upravlenie (Fuzzy modeling and control). Translate from English. BINOM. Laboratoriya znanij Moscow. 2013; 798 p. (in Russ.) [Google Scholar]
  4. Dubey, S., Pandey, R.K., Gautam, S.S.: Literature review on fuzzy expert system in agriculture. International Journal of Soft Computing and Engineering (IJSCE) Vol. 2(6), pp. 289–291, 2013. [Google Scholar]
  5. Papageorgious, E.I., Kokkinos, K., Dikopoulou, Z. Fuzzy Sets in Agriculture. In: Kahraman, C., Kaymak, U., Yazici, A. (eds) Fuzzy Logic in Its 50th Year. Studies in Fuzziness and Soft Computing, vol 341, pp. 211–233, 2016. Springer, Cham. https://doi.org/10.1007/978-3-319-31093-010 [CrossRef] [Google Scholar]
  6. Parfenova, V.E., Bulgakova G.G., Amagaeva Yu.V., Evdokimov K.V. Fuzzy modelling for tasks of management of the agricultural-industrial complex. Quality Management and Reliability of Technical Systems IOP Conf. Series: Materials Science and Engineering 666 (2019) 012067 IOP Publishing DOI: 10.1088/1757-899X666/1/012067. [Google Scholar]
  7. Sujaritha M., Annadura S., Satheeshkuma J., Sharan S.K., Mahesh L., Weed detecting robot in sugarcane fields using fuzzy real time classifier.// Computers and Electronics in Agriculture. 2017; 134: 160–171. [CrossRef] [Google Scholar]
  8. Turan I.D., Dengiz O., Ozkan B. Spatial assessment and mapping of soil quality index for desertification in the semi-arid terrestrial ecosystem using MCDM in interval type-2 fuzzy environment. // Computers and Electronics in Agriculture. 2019. Vol. 164, 104933. DOI: 10.1016/j.compag.2019.104933 [CrossRef] [Google Scholar]
  9. Prabakaran G., Vaithiyathan D., Ganesan M. Fuzzy decision support system for improving the crop productivity and efficient use of fertilizers. // Computers and Electronics in Agriculture. 2018. Vol. 150, p. 88–89. DOI: 10.1016/j.compag/2018.03.030 [CrossRef] [Google Scholar]
  10. Omid M., Lashgar M., Mobli H., Alimardani R., Mohtasebi S., Hesamifard R. Design of fuzzy logic control system incorporating human expert knowledge for combine harvester// Expert Systems with Applications. 2010; 37: 7080–7085. [CrossRef] [Google Scholar]
  11. Craessaerts G., De Baerdemaeker J., Missotten B., Saeys W. Fuzzy control of the cleaning process on a combine harvester// Biosystems Engineering. 2010; 106: 103–111. [CrossRef] [Google Scholar]
  12. Borisova L., Dimitrov V., Nurutdinova I. Intelligent System for Technological Adjustment of the Harvesting Machines Parameters // Advances in Intelligent Systems and Computing. 2018; 680: 96–105. [CrossRef] [Google Scholar]
  13. Borisova L.V., Dimitrov V.P., Tugengol’d A.K., Nurutdinova I.N. A technological adjustment of the agricultural machines based on fuzzy logic. // Vestnik mordovskogo universiteta = Mordovia university bulletin. 2018; 28-2: 239–254. Available at: [Google Scholar]
  14. Processing of fuzzy information in decision-making systems / A.N. Borisov, A.V. Alekseev, G.V. Merkuriev and others - M .: Radio and communication, 1989. - 394 p. [Google Scholar]
  15. Malyshev N.G., Bernstein L.S., Bozhenyuk A.V. Fuzzy models for expert systems in CAD. Enegoatomizdat, Moscow. 1991. 136 p. [Google Scholar]
  16. Borisova L.V., Nurutdinova I.N., Dimitrov V. P.: Fuzzy Logic Inference of Technological Parameters of the Combine-Harvester. WSEAS TRANSACTION on SYSTEMS. 2015. Vol. 14. p. 278–285. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.