Multiagent Models for Forecasting and Identifying Production Processes
Evgeny Anatolevich Nazoykin1, Ivan Germanovich Blagoveshchensky2
1Evgeny Anatolevich Nazoykin, Moscow State University of Food Production, Moscow, Russia.
2Ivan Germanovich Blagoveshchensky, Moscow State University of Food Production, Moscow, Russia.
Manuscript received on September 17, 2019. | Revised Manuscript received on 22 September, 2019. | Manuscript published on October 10, 2019. | PP: 3807-3809 | Volume-8 Issue-12, October 2019. | Retrieval Number: L3831081219/2019©BEIESP | DOI: 10.35940/ijitee.L3831.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The article is devoted to the method for creating multiagent models for forecasting and identifying production processes using a structural parametric approach. Using multiagent simulation allows reflecting the state and dynamics of complex active systems of production processes with analysis and forecasting of the quality of the finished product. The methods and algorithms of the structural parametric approach to the implementation of an agent-based simulation model based on the system self-diagnosis are described.
Keywords: Agent Modeling, Multiagent Technologies, Identification, Forecasting, Food Production, Production Process, Modeling, Mathematical Model, Structural Parametric Modeling, Active System, Grand System.
Scope of the Article: Production