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MULTI-SPECTRAL IMAGE ANALYSIS BASED ON DYNAMICAL EVOLUTIONARY PROJECTION PURSUIT
multi-spectral image projection pursuit dynamical evolutionary algorithm
2015/8/10
Principal component analysis (PCA) is usually used for compressing information in multivariate data sets by computing orthogonal projections that maximize the amount of data variance. PCA is effective...
ASYMPTOTICS OF GRAPHICAL PROJECTION PURSUIT
Mathematical tools high-dimensional data planning and design
2015/7/14
Mathematical tools are developed for describing low-dimensional projec-
tions of high-dimensional data. Theorems are given to show that under
suitable conditions, most projections are approximatel...
Projection Pursuit for Discrete Data。
Projection Pursuit Flood Disaster Classification Assessment Method Based on Multi-Swarm Cooperative Particle Swarm Optimization
Flood Classification Particle Swarm Optimization Projection Pursuit
2013/3/19
The indicators of flood damage assessment in the flood classification are often incompatible, and it is very difficult to use those indicators value directly for classification assessment. Projection ...
Projection Pursuit Dynamic Cluster Model and its Application to Water Resources Carrying Capacity Evaluation
Projection Pursuit Dynamic Cluster Genetic Algorithm Water Resources
2013/3/20
The research shows that projection pursuit cluster (PPC) model is able to form a suitable index for overcom-ing the difficulties in comprehensive evaluation, which can be used to analyze complex multi...
投影寻踪分类模型在作物补偿效应评价中的应用（Comprehensive Evaluation on Compensatory Effects of Water Recovery after Drought Based on Projection Pursuit Classification Model）
水分胁迫 补偿效应 投影寻踪分类
2010/1/28
为了解决作物旱后复水补偿效应评价和优选的不确定性，提高补偿效应评价模型的分辨率，提出了投影寻踪分类模型，并采用变异和动态信息素更新蚁群算法寻找最优的投影方向，用最佳投影方向信息研究各评价指标对补偿效应的贡献率，发现光合速率的大小直接反应了补偿生长的能力，是影响补偿效应的关键因子，与以往研究结论相符，且适度胁迫复水后第5天表现出的补偿效应最佳。
Classifiability-Based Optimal Discriminatory Projection Pursuit
Classifiability-Based Optimal Discriminatory Projection Pursuit
2013/7/17
Linear Discriminant Analysis (LDA) might be the most widely used linear feature extraction method in pattern recognition. Based on the analysis on the several limitations of traditional LDA, this pape...
Projection-Pursuit Based Principal Component Analysis: a Large Sample Theory
Dispersion matrices eigenvalues and eigenvectors empirical processes principal component analysis projection pursuit (PP)
2007/12/10
摘要 The principal component analysis (PCA) is one of the most celebrated methods in analysing multivariate data. An effort of extending PCA is projection pursuit (PP), a more general class of dimension...