资源列表
ase
- 基于遗传优化小波神经网络逆模型的油水测量Wavelet neural network based on genetic optimization of the inverse model of water measurement-Wavelet neural network based on genetic optimization of the inverse model of water measurement
spli
- 基于超熵和模糊集理论的带钢表面缺陷分割Based on entropy and fuzzy set theory over the strip surface defects split-Based on entropy and fuzzy set theory over the strip surface defects split
lanning
- 基于蝴蝶模型的星载嵌入式软件测试策划Butterfly model based on-board embedded software test planning-Butterfly model based on-board embedded software test planning
pots
- 加速的FastHessian多尺度斑点特征检测Accelerated FastHessian multi-scale feature detection spots-Accelerated FastHessian multi-scale feature detection spots
ation
- 电场作用下染料掺杂液晶器件的激光辐射Electric field of laser dye-doped liquid crystal device radiation-Electric field of laser dye-doped liquid crystal device radiation
ign
- 机载立体测绘相机滚转轴伺服系统的辨识与设计-Three-dimensional mapping camera onboard the roll axis servo system identification and design
jingdiansuanfa
- c语言算法云集于此，在程序设计时可随时查阅，方便您的设计工作-algorithm c language gathered here, in the program design can be readily available to facilitate your design work
ssl_survey
- 本文回顾了半监督学习领域的各种算法，并陈述了该领域中的最近进展。-we review the literature on semi-supervised learning,which is an area in machine learning and more generally,artificial intelligence.
Event-driven-bank-simulation-system
- 通过程序动态模拟银行顾客在一家有n>=2个窗口的银行的到达和离开情况。通过计算每位顾客的平均等待时间及每一窗口处于“繁忙”状态的百分比，来测试银行的服务效率。实现中，可以用时间代表银行活动的对象，用事件驱动来模拟这些活动，并以概率（随机数发生器）来描述预期的客户到达率和银行职员为一个顾客服务所需的时间-Bank customers through the process in a dynamic simulation with n> = 2 windows of the bank&#
Maximum-and-minimum-distance
- C语言实现最大最小距离的算法，需要的可以下哈-Maximum and minimum distance
ItemClusteringRecomAlg
- 针对传统推荐算法的数据稀疏性问题和推荐准确性问题，提出基于粒子群优化的项聚类推荐算法。采用粒子群优化算法产生聚类中心，在此基础上搜索目标项目的最近邻居，并产生推荐，从而提高了传统聚类算法的推荐准确性及响应速度。实验表明改进的项聚类协同过滤算法能有效提高推荐精度-Aiming at the problems that the data are sparse and the results are not accurate in traditional recommendation algorith
C-graph
- C算法 图算法 相当有用的电子书 适合入门的算法学习-C algorithm graph algorithms very useful book for entry-learning algorithm