'''Short-Term Processes Forecasting by Analogues Complexing GMDH Algorithm'''. Gregory Ivahnenko '''Abstract'''. ''In the report is described theoretical and practical results of complex systems forecasting by Analogues Complexing algorithm in the case of short data samples. Described structure and modifications of the algorithm. Shown that complex application of inductive parametric, non-parametric and data mining methods allows to make all-round analysis of the object, investigate relationships of variables and simulate future development of processes.'' '''Keywords'''. Inductive modeling, Forecasting, Clusterization, Data mining, Analogues complexing, Decision support. '''References'''. [[br]]1. Ивахненко А.Г., Степашко В.С. Помехоустойчивость моделирования. К.: Наукова думка, 215 с. 1985. - http://articles.gmdh.net. [[br]]2. Ashby D. An introduction to cybernetics. J. Wiley, New York, 1958. [[br]]3. Beer S. Cybernetics and Management, English Univ.Press, London, 1959. - 280p. [[br]]4. Madala H.R. and Ivakhnenko A.G. Inductive Learning Algorithms for Complex Systems Modeling, CRC Press Inc., 1994, p.384. [[br]]5. Mueller J.-A., Lemke F. Self-Organizing Data Mining. Extracting Knowledge From Data. Trafford Publishing, Canada, 2003. - http://knowledgeminer.com. [[br]]6. Ивахненко А.Г., Богаченко Н.Н., Ли Тянь Mин. Безмодельное прогнозирование случайных процессов при помощи комплексирования прогнозов по аналогам. Проблемы управления и информатики, 1997, no.4, pp.111-188.