As an important component of high-quality economic development,high-quality agricultural is the key and inevitable requirement for comprehensively promoting rural revitalization.As an important agricultural resource region in China,how to promote high-quality agricultural development in the western region with high-quality orientation is one of the important topics of current research.Firstly,based on the development perspective of agriculture,rural areas,and farmers,constructs an evaluation index system for high-quality agricultural development in the western region from three aspects:the quality of agricultural industry,the quality of farmers’ lives,and the quality of rural construction.In order to achieve objective modeling of high-dimensional data and fully explore the objective laws and information in the evaluation index data,uses the projection pursuit evaluation method for evaluation.Secondly,in order to achieve the solution of the optimal projection vector,an improved slime algorithm using.Iterative chaotic mapping and elite reverse learning strategy is adopted.The improved method has the advantages of solving the lack of population diversity and enhancing global search performance,which enhancing the optimization ability of the algorithm.Through comparison with different algorithms,the results show that the improved slime algorithm has high optimization accuracy and robustness.Finally,calculate the projection evaluation value through the optimal projection vector to conduct a analysis of the high quality development level of agriculture in the west region,and compare the differences in the high quality development level of agriculture in different provinces.The analysis results show that:(1)The improved slime algorithm optimizes the projection pursuit model better than the unimproved;(2)During the research period,the evaluation value of high-quality agricultural development level in various provinces in the western region has generally shown an upward trend,but there are significant differences among different provinces,and the influencing factors vary from region to region.Relevant suggestions are proposed. |