Application of Immune Genetic Algorithm in Grain Storage Environment

摘要

在存储期间,谷物的温湿度监测是谷物监测的主要内容,同时也是保证谷物质量最重要的因素.由存储模式和昆虫导致的粮食变质依赖于环境条件的空气湿度或者相对湿度,以及粮食温度.粮食的湿度主要是通过对水分来控制的.限制粮食的含水量可以确保储存性能良好,因此成为了市场交易的主要因素.在确定粮食的价值的时候,含水量比较高的粮食往往会被打折扣,因此,维护粮食的最佳含水量是非常可取的.但是完善的控制粮食水分含量的方法总是难于实现的,通风温度控制是一种有效的降低粮食温度的方法,可以提供令人满意的粮食储存条件.相比较而言,温度控制比不上依靠周期性通入空气冷却粮食所实现的效果.应用神经网络方法将会实现谷物储藏温湿度的精确控制.%Grain moisture content and temperature were considered to be the most critical factors for maintaining grain quality during storage.Grain deterioration caused by insects and storage molds is dependent on the grain environmental conditions of interstitial air relative humidity,or equilibrium relative humidity,and grain temperature.Grain moisture is the primary source of water,which can change relative humidity and is thus critical to control.Limits on moisture content for delivered grain ensure good storage and thus becomes a marketing factor.High moisture grain is often discounted at receiving while over-dry grain has no added value and thus,maintaining grain at optimum moisture content levels is highly desirable.While perfect control over grain moisture content cannot always be achieved,temperature control with aeration is an effective method to lower grain temperatures to levels that provide acceptable storage conditions.Temperature control,however,cannot always be achieved as most aeration methods rely on seasonal ambient air conditions to cool grain.The use of neural network provides a method to moisture grain content and temperature.