Model and algorithmic support for forecasting and planning the forage harvesting process

Abstract

Harvesting of grass forage is considered as a complex technical and technological process. The final product, in this case a silage billet, can be obtained using different variants of feed production technologies. An approach to choosing the most acceptable variant of technologies and plans for the production of grass feed based on logicaldynamic and fuzzy-probability models is presented. The developed set of models and algorithms makes it possible to describe and investigate the existing interconnected multi-stage processes of grass feed production from a systemcybernetic standpoint when transferring a management object (an agricultural enterprise producing feed) from a given initial state to a given final state, depending on specific scenarios of changing external conditions. Factors related to agrobiological, temporal, climatic, economic and organizational constraints are considered as the main external conditions. To solve the problems, fuzzy-probability models for estimating the yield of forage lands and the quality of the grown fodder mass are proposed. When analyzing the effectiveness of feed production processes, an important issue is the multi-criteria assessment of quality, as well as the corresponding programs for proactive management of the silage harvesting process, taking into account the following indicators: the timing of operations under various conditions, the degree of uniformity of resource use and the total time of harvesting grass feed. An original mathematical analysis of the processes under consideration and algorithms for solving problems of forecasting and planning forage harvesting are proposed.