The study of shallow-sea-shoal identification is a part of a great project supported by agricultural department in Zhejiang.
基于图像声纳技术的浅海鱼群分类识别算法研究这一课题,是浙江省农口重大攻关项目“浙江浑水区深水网箱水下检测设备开发”的一部分,主要针对浅海养殖技术的迫切需要而展开工作。
An optimization approach to the location of oilfield multistage stations by fish-swarm algorithm;
基于鱼群算法的油田多级站定位优化方法研究
An optimization method of multistage stations locating in oil transportation based on fish-swarm algorithm;
用鱼群算法求解石油运输系统多级站定位优化问题
Optimization of multilevel hierarchical transshipment system in logistics transportation based on fish-swarm algorithm;
用鱼群算法求解多级递阶物流中转运输系统优化问题
So the paper put forward artificial fish swarm algorithm(AFSA) for Optimization of complex system reliability.
针对这一问题,提出了基于群体智能-人工鱼群算法(Artificial Fish School Algorithm,AFSA)的优化方法。
Comparative biological characteristics of skipjack tuna Katsuwonus pelamis between free school catch and log school catch;
中西太平洋金枪鱼围网起水鱼群与流木鱼群渔获物中鲣生物学特性的比较