1.
The Information Forecast Research Based on the Quotient Granular Computing;
基于商空间粒度计算的信息预测研究
2.
A Product Function Model Based on Granularity Computing of Quotient Space Theory
基于商空间粒度计算的产品功能模型
3.
Application of Granular Computing Based on Quotient Space Theory in Time Series Forecasting;
商空间粒度计算理论在时间序列预测中的应用
4.
The wavelet transform and granularity technique being combined, a segmentation algorithm in texture image was presented, and the algorithm was verified by experimental results.
将商空间粒度计算理论与小波变换相结合并应用于纹理图像分割中，取得了成功。
5.
Research of Granular Computing, Rough Sets, Pansystems and Quotient Space Theory;
粒度计算与粗集、泛系和商空间理论的研究
6.
The Research of Heuristic Search Algorithm Based on Quotient Space of Granular Computing;
基于商空间的粒度计算在启发式搜索中的应用与研究
7.
Research on Models of Granular Computing Based on Quotient Space Theory and Rough Set Theory;
基于商空间理论和粗糙集理论的粒计算模型研究
8.
Fuzzy Clustering Analysis Based on Quotient Spaceand Information Granularity;
基于商空间和信息粒度的Fuzzy聚类分析
9.
Dynamic spatial scheduling approach based on improved particle swarm optimization algorithm
改进粒子群算法的动态空间调度方法
10.
Granularity-adjustable Parallel Kriging Interpolation for Stratified Stratum
粒度可调的并行Kriging地层空间插值算法
11.
Research on the Model of Quotient Fractal Based on the Theory of Quotient Space and Its Application;
基于商空间粒度理论的商分形模型及其应用
12.
Particle Swarm Optimization with Contracted Ranges of Both Search Space and Velocity
压缩搜索空间与速度范围粒子群优化算法
13.
Space Angle and Point Coordinate Calculation for Combined Fixtures
组合夹具空间角度及空间点坐标的计算
14.
Elastic buckling analysis of large span reticulated shell structures
大跨度空间网壳结构弹性稳定性计算
15.
Spatial Analysis of Long-Span Continuous Steel Truss Beam Arch Bridges
大跨度连续钢桁梁拱桥空间计算分析
16.
Calculation method for image motion speed of space camera and DSP-based implementation
空间相机像移速度计算方法及DSP实现
17.
Object tracking using the trust-region method in scale-space with probability distribution images generated by kernel density estimation
基于核密度估计尺度空间的目标跟踪算法
18.
The space of similarity measurement is N dimensions and the calculation is very large.
因此，相似性度量空间是N维的，计算量相当巨大。