The algorithm of bifurcation points forecasting in the analitical researches of complex agro-ecological systems

• Autorzy: Osypenko V.
• Języki publikacji: EN

Abstrakty

EN

An original development is described in this work of the forecasting of so-called rare events concerning the agro-ecological systems. Under defi nition "rare" it is necessary to understand events which take place during some observed process, time intervals between them are so great that it is possible to consider that they practically do not infl uence each other. The beginning of the rare events can be called as a "bifurcation point" of the observed process. Both the multistage procedure of the forecasting based on principles of inductive modeling and the selection criterion of the best forecasting models are described.

Słowa kluczowe

EN

inductive modeling; algorithm of modeling; criterion of models selection; agro-ecological system; forecasting; bifurcation points; rare events

PL

modelowanie indukcyjne; system agro-ekologiczny; prognozowanie; bifurkacja

• Wydawca: Polish Academy of Sciences, Branch in Lublin
• Czasopismo: ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes
• Rocznik: 2012
• Tom: Vol. 1, No 2
• Strony: 35--38
• Opis fizyczny: Bibliogr. 7 poz.

Twórcy

autor

Osypenko V.

• Automation and Robotics Systems Department of the National University of Life and Environmental Sciences of Ukraine, 03041, Kyiv, st. Geroiv Oborony 15, Ukraine,

Bibliografia

• 1. Ivakhnenko A.G. and Osypenko V.V. 1984. Prediction of Rare Events on the Basis of the GMDH Algorithm // Scripta Technica, Inc., U.S.A., Soviet Automatic Control, № 5, vol. 17, pp. 6-10.
• 2. Ivakhnenko A.G. 1982. Induktiwnyj metod samoorganizatsii modelej stozhnykh sistem. Kijev: Nauk. dumka. pp. 296.
• 3. Osypenko W.W. 1980. Prognozirowanije daty zamierzanija oz. Bajkał po garminicheskomu algorytmu MGUA. W kn: Camoorganizatsja kiberneticheskikh sistem. Kiev an Ukrainy. 34-39.
• 4. Ivakhnenko A.G. and Stepashkow S. 1985. Pomekhoustoichiwost modelirowanija – Kiev: Nauka dumka – pp. 216.
• 5. Madala H.R. and Ivakhnenko A.G. 1994. Inductive learning algorithms for complex systems modeling. – New York: Boca Raton, CRC Press – 384.
• 6. Stepashko W.S. 2003. Teoretychni aspekty MGUA jak metody induktiwnogo modelewannia. Uprawlajushekije sistiemy i maszyny. No 2. 31-44.
• 7. Battuk V., Basov M. and Dorundyak L. Matematic model of the process of dust catching inan apparatus with a movable separator ECOTECHMOD an International Quarterly Journal on Economics of Technology and Modelling Processes. Vol. 1. No 1. 2012. 13-16.