Grazing Yak Population In Three Rivers Source Region Optimization Model And Sustainable Development Decision Support System

With the continuous development of evolutionary algorithms,people's lives have been continuously improved.In this information age,how to use evolutionary algorithms to solve problems in people's lives and coordinate the development of industry,agriculture and animal husbandry has become very popular.Meaningful things.The Sanjiangyuan is located in the southern part of Qinghai Province,China,and belongs to high altitude areas.Due to the unique geographical advantages of Sanjiangyuan,the region has rich species and has become the largest nature reserve in the country.Among the many species resources of Sanjiangyuan,grassland resources are the most abundant.The local herdsmen used the gift of nature,grassland,to develop animal husbandry.Because calves have strong cold tolerance and can live in high altitudes,yak has become the main breeding target of animal husbandry.However,due to the lack of scientific and sustainable development guiodance in the process of breeding yak,most of the herdsmen have led to a slow development of the yak industry and a loss of balance in the development of the ecological environment.In view of the above problems,firstly,this paper conducts on-the-spot investigation and research on the yak breeding base in Sanjiangyuan area to understand the details of yak breeding and the local ecological environment,and uses mathematical modeling to model yak breeding in Sanjiangyuan area.The income currency is the objective function;then,the evolutionary algorithm is used to solve the model;finally,the IDEA development tool is used to develop the sustainable development decision support system for grazing yak population in Sanjiangyuan area,and the effectiveness of the algorithm is verified by simulation experiments.In terms of model establishment,the influencing factors considered in this paper are more comprehensive.The proposed scheme is in line with the habits of herders.The established model can realistically simulate the breeding situation of herders.The model is scientific and effective.In terms of evolutionary algorithms,this paper adopts the evolutionary algorithm is improved on the basis of the cloud genetic algorithm.The selection operator is improved on the basis of the optimal preservation strategy.The crossover rate and the mutation rate are adaptively generated based on the evolutionary algebra and the individual fitness value.The improved algorithm is called cloud adaptive genetic algorithm.The improved algorithm is superior to cloud genetic method in algorithm quality and algorithm efficiency when solving this model.Therefore,the algorithm selected in this paper is also efficient and feasible.In terms of platform,the system developed in this paper is simple and fast,and can guide the herders' scientific sustainable breeding of yak,and the system is also effectively used,the simulation results show that the selected algorithm is efficient and feasible.The simulation results show that the selected algorithm is efficient and feasible.In terms of system platform,the system developed in this paper is simple and fast,which can guide herdsmen to scientifically and sustainably breed yaks.The simulation results show that the model and algorithm are feasible.