多养分群落选址算法下的种子投放

依据经验的传统农业中，种子与耕地的匹配存在盲目性使得种子与耕地之间的特性不十分吻合，制约着产量的提高。针对这一问题，提出了多养分下群落选址算法的种子投放。利用唑染色方法对种子信息数据进行采集，通过灰色理论对种子信息数据进行空穴处理和分类等,同时基于3S技术对耕地信息实施采集；利用CLA匹配算法对种子与耕地进行匹配，通过量子化PSO对种子投放位置进行更新，实现作物与耕地的双向选择。实验演算表明，该设定不仅可以提升农作物产量，削弱耕地与农作物之间的制衡关系，而且为人们选取适宜种子提供了便利。

Seed delivery under multi nutrient community location algorithm

Traditional farming is based on experience and blindness of the matching between the seed and cultivated land, the characteristics between the seed and cultivated land show a lack of consistency, and then the yield is affected. In order to solve this problem, this paper presents a multi nutrient Community Location Algorithm（CLA） to solve the problem of seed delivery. Firstly, it collects characteristics data of seed through method of dyeing, then processes and classifies the data through grey theory, collects farmland data by 3S technologies. Secondly, it considers the need of several kinds of nutrients and suitable cultivated land for crop growth, to match the seed and cultivated land by CLA matching algorithm, updates the seeding location through quantization PSO. Finally, the experiments show that the multi nutrient CLA cannot only improve crop yields, and weaken the relationship of balance between farmland and crops, but also provide convenience for selecting suitable seeds.