当前甘蔗机械收获阶段人工与AI相结合扣杂方式的探讨

2020年受疫情影响,甘蔗砍收劳动力流动性受到限制,甘蔗砍收劳动成本上涨,糖厂和蔗农以甘蔗机械化收割需求明显增加,长期以来甘蔗的扣杂政策主要是由糖厂单方面来制定,测杂的程序要求各糖厂不同,主要是以进厂甘蔗或地头收获甘蔗取样测杂为主,随着机收量的增加,测杂的人力、物力成本增加,效率比较低下,同时受取样代表性的影响,测杂的数值常常引发争议,如何找到一种各方都参与,测杂的结果相对信服,且效率较高的测杂方式成为迫切需求,本文从影响机收的主要因素出发,通过对各因素之间的关联,建立测算模型,并得出预估值,结合AI的相关技术。分析结果表明人工预测杂系统与AI机结合的扣杂方式,为解决当前的扣杂方式,协调平衡各方利益,指导蔗农、服务队降低含杂量等方面具有一定的指导意义。

The Discussion on the Combination of Artificial and AI in the Current Sugarcane Mechanical Harvest Stage

Affected by the epidemic in 2020,the mobility of sugarcane harvesting labor had been restricted,and the labor cost of sugarcane harvesting had risen.Sugar mills and sugarcane farmers had significantly increased the demand for sugarcane mechanical harvesting.For a long time,sugarcane deduction policies had been unilaterally formulated by sugar factories.The procedures for measuring impurities were different from sugar factories.The main focus was on the sugarcane entering the factory or harvesting sugarcane from the ground.The sampling and testing of impurities was the main method.With the increase of machine harvesting,the manpower and material costs of testing impurities increased,and the efficiency was relatively low.The impact of such representativeness,the value of impurity measurement often triggered controversy.How to find a way that all parties participate in the impurity test,the result of the impurity test was relatively convincing,and the efficiency of the impurity test method had become an urgent need.This article started from the main factors affecting machine receipt,analyzed the correlation between the various factors to set up the establishment of a measurement model and the estimated value,combined with AI related technology.We believed that the artificial prediction system combined with the AI machine deduction method was solving the current methods of impuritydeduction,coordinating and balancing the interests of all parties,and guiding sugarcane farmers and service teams to reduce impurity content had certain guiding significance.