1.
Tarski s Definition of Truth in the Calculus of Classes;
塔斯基关于类演算语言的真句子定义
2.
On Inversion and Non-calculation of Four Basic Types of Logical Inference
对逻辑推理四大基础类型的反演算和非演算
3.
It can be classified into different categories, such as text demonstration, phenomenon reappearing, procedure simulation, principle illustration, calculating and drawing, etc.
它可分文本演示类、象再现类、程模拟类、理示意类、算绘图类等。
4.
A Higher-Order Potential Vorticity Inversion Algorithm and Its Application, PartⅠ: Potential Vorticity Inversion
一类高阶位涡反演的算法及其应用Ⅰ:位涡反演
5.
A Class of Evolutionary Algorithm and Its Application Based on Domain Decomposition;
一类基于区域分裂的演化算法及应用
6.
A New Fuzzy Clustering Algorithm Based-on Adaptive Differential Evolution
基于自适应差异演化的模糊聚类算法
7.
Application of Typed Pi Calculus in Web Service Choreography
类型化Pi演算在Web服务组合中的应用
8.
Study on the Typological Theory and Its Simple Calculus Classes;
基于类型化理论及其简单类型演算的研究
9.
A Higher-order Potential Vorticity Inversion Algorithm and Its Application, PartⅡ: Piecewise Inversion
一类高阶位涡反演的算法及其应用Ⅱ:分部位涡反演
10.
Clustering Based on Evolutionary Algorithm in the Presence of Obstacles
基于演化算法的带故障约束空间聚类分析
11.
Antisite defect types and temporal evolution characteristics of D0_(22)-Ni_3V structure:Studied by the microscopic phase field
微观相场计算D0_(22)-Ni_3V结构反位缺陷类型及演化
12.
Novel particle dynamical evolutionary algorithm for spatial data clustering
一种求解空间数据聚类的粒子动力学演化算法
13.
Advances in Studies on Atmospheric Correction Algorithm in Remote Sensing Retrieval for Case Ⅱ Waters
Ⅱ类水体遥感反演中的大气校正算法研究进展
14.
Algorithms on Inversion Chlorophyll Concentration by Remote Sensing in Near Shore Case Ⅱ Waters
近岸Ⅱ类水体叶绿素浓度遥感反演的算法综述
15.
Applications on AAE include: algorithm animation engine, JVDSCL and code library.
一个基于算法演示引擎的应用包括:算法演示引擎,代码库和数据结构可视化类库。
16.
Asynchronous Hierarchical Parallel Evolutionary Algorithm and its Application in Fuzzy Clustering Analysis;
异步分层并行演化算法及其在模糊聚类分析中的应用
17.
An algorithm of aerosol properties based on remote sensing by MODIS imagery over case Ⅱ waters in Taihu Lake
一种基于MODIS影像反演太湖Ⅱ类水体上空气溶胶参数的算法
18.
Our results suggest that GA based neural classifiers are robust and effective in finding optimal subsets of features from large data sets.
结果显示，基因演算法结合类神经分类器筛选特征值法是有效且稳健的。