Research And Application Of Environmental Regulation Rules Reasoning Technology Oriented To Plant Factory

With the rapid development and widespread application of computer technologies such as Internet of Things and machine learning,more and more experts and scholars have realized that the combination of computer technology and traditional experience of agricultural planting experts will create a sophisticated crop growth control environment.This paper designs and implements the environmental regulation rule reasoning technology for plant factories.By collecting efficient planting experience data of planting experts,using the expert system theoretical knowledge to analyze and construct the corresponding database of crop growth control rules,and then using the existing material Networking technology and Internet technology design and development of plants for the plant environmental regulation rule reasoning control system,and finally with the actual plant factory,test the growth of crop environment automation control experiments.This article first introduces the relevant research background and research status,and makes a brief introduction of the main work.Then the existing pattern matching algorithms based on expert rules are summarized,including the pattern matching algorithms such as Rete,Treat and Leaps.The algorithm is compared with the algorithms in terms of execution efficiency,memory utilization and so on.Finally,Rete algorithm is more suitable for the theoretical basis of the research needs.On the basis of the existing theory,this paper designs the core module part of the research project,that is,the reasoning method of plant environmental regulation rules.Finally,based on the rule-based reasoning method,we design and implement a plant-oriented environmental control expert system.Through this system,we can collect,import and import expert planting experience data into the system.The rules of data structure are reasoned and constructed by computer.Finally,real-time data monitoring and control of crop growth based on environmental regulatory rules reasoning is realized.