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Top1. Introduction
Agricultural mechanization as an important part of the whole management, whether the agricultural machinery is complete or not is directly related to the economic benefits of China's mechanization. Therefore, Tiechuang et al. (2018) only by setting up agricultural machinery reasonably and reducing the cost input as much as possible, can we realize the maximization of economic benefits. At present, there are many calculation methods about agricultural machinery. With the development of science and technology in China, the related engineering technology is widely used in the field of agricultural machinery. The advent of the Internet era has promoted the application of computer in the mathematical planning model of agricultural machinery. Lang et al. (2018) in order to improve the economic benefits of agricultural machinery allocation, the working time and workload of the whole project stage should be considered in the mathematical programming model of agricultural machinery allocation.
The accessibility of resources in the region plays a significant role in the organization of the farm. Crop type, crop density, crop distribution, crop diversity, and crop combinations are necessary decisions for adjustment during growth. An analysis of crop distribution and other management methods is proposed for the statistical model. Planning of farms and its management are related to many controlled factors and some of factors which are uncontrollable. To gain understanding from these boundaries of farms Martin et al. (2015) creates a farm model that combines yield in a multi-time space. The approach of Linear Programming is used for determining the practicability of decision-making.
In developing season farmers need to dispense their fields under an alternate collection of crops relying upon past seasons, crop yield and cost of market. Likewise, they need to anticipate the crop production of the coming season as well. Such a choice is very testing and basic. On the other hand, to help the farmers and to allot the resource optimally the decision support approach is discussed by Prišenk et al. (2014). The model depends on two ideas; crop allocation and decision of crop rotation. The crop allocation and its planning are the foundation decision of crop management framework. Such choices concentrate all the complexities engaged with a framework and choices accessible at the farm level due to their contribution at various phases of crop production.
Therefore, planning of crop is critically important step in crop production and thereby presents a huge impact on farm income. The crop system framework must provide a connection among the farm parameters in this regard, sustaining all the conflicting objectives. Most of the models deal with plant system selection which is represented by crop selection or includes rotation of crop as a perception. A combined farm model was developed by Lanfranchi et al. (2015) for the purpose of increasing farm income. It is challenging to achieve the potential for such a dynamic decision-making process due to the huge amount of constraints involved and their difficult connections or interfaces. In the farming scheme the choices of the crop system are very important. Therefore, a knowledge-based method is implemented to create a combined farm plan. Such a combined state of the farm delivers insight into determining the shortage of constraints to adjust according to the availability and accessibility of assets in the region.