基于大数据的兵力编组智能推荐算法研究
Research on Intelligent Recommendation Algorithm for Troop Formation Based on Big Data
况贶 1杨静2
作者信息
- 1. 武汉市武昌区张之洞路2号 武汉 430060
- 2. 武汉数字工程研究所 武汉 430205
- 折叠
摘要
针对海上作战中兵力推荐准确度不高的难题,提出一种基于历史案例挖掘的智能推荐方法.该方法使用激活函数,将当前可用兵力与基于历史案例挖掘的相似兵力编组进行有机结合,得到各个推荐编组的可用度,最后给出目前最高效的兵力推荐.实验与传统协同过滤的方法比较,速度更快、准确度更高,具有较强的鲁棒性.
Abstract
A smart recommendation method based on historical case mining is proposed to address the problem of low accura-cy in military force recommendation in maritime operations.This method uses an activation function to organically combine the cur-rent available forces with similar force groups based on historical case mining,obtaining the availability of each recommended group.Finally,the algorithm provides the most efficient force recommendation currently available.Compared with traditional collab-orative filtering methods,the experiment has faster speed,higher accuracy,and stronger robustness.
关键词
协同过滤/兵力推荐/数据挖掘Key words
collaborative filtering/force recommendation/data mining引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据