Potential prediction of enhanced oil recovery based on statistical learning theory;
基于统计学习理论的提高采收率潜力预测
Theoretical foundations of statistical learning theory of birandom samples;
基于双重随机样本的统计学习理论的理论基础
Outline and application of statistical learning theory;
统计学习理论的原理与应用
The support vector machine(SVM),put forward by some researchers and Vapnik,is a new machine learning algorithm,based theoretically on statistic learning theory.
支持向量机(Support Vector Machine,SVM)是由Vapnik等人提出的一种基于统计学习理论的新型机器学习算法;而人工神经网络(Artificial Neural Network,ANN)已经成功用于解决模式识别和任意非线性函数回归估计问题中。
For the first time,least squares support vector machine based on statistic learning theory was used to do this work Experiments based on this method.
指出了用叶绿素a的浓度估计海洋初级生产力的重要作用;分析了目前采用的浓度反演方法的不足;尝试将基于统计学习理论的最小二乘支持向量机用于浓度反演,SeaBAM的数据实验结果表明该方法可以获得更高的反演精度;可以有效避免过学习的情况出现;不像神经网络那样需要确定网络结构。
Support vector machine is a new machine learning algorith m, based theoretically on statistic learning theory created by Vapnik.
支持向量机是一种新的机器学习算法 ,它的理论基础是 Vapnik创建的统计学习理论。
Support vector machine is a new learning machine, and it is based on the statistics learning theory.
支持向量机是最近发展起来的一种新的通用的机器学习方法 ,其理论基础是统计学习理论 ,支持向量机无论在模式识别还是在函数拟合方面均显示了其优越性 ,并越来越受到国内外研究者的广泛关注 。
Statistics Learning Theory (SLT) is a machine learning method based on solid theory, which is developed from traditional statistics and turns to be sophisticated system info ---- Statistics Learning Theory since 90’s in 20 century.
统计学习理论是在传统统计学基础上发展起来的一种具有坚实理论基础的机器学习方法,自20世纪90年代以来,自身形成了一个较完善的理论体系——统计学习理论,提出了新的模式识别方法——支持向量机(SVM)。
Based on Statistics Learning Theory, the method seeks for optimal learning effect under limited information by actual risk minimization with structure risk minimization.
支持向量机(Support Vector Machine,SVM)是由Vladimir Naumovich Vapnik等学者于1992年提出的一类新型机器学习方法,该方法以统计学习理论为理论体系,通过寻求结构风险最小化实现学习的真实风险最小化,追求在有限信息条件下得到最佳的学习效果,具有全局最优、结构简单、推广能力强等优点。
The basic statistical learning theory (SLT) and its corresponding algorithms, support vector machines (SVMs), are surveyed, and especially, its latest research results are summarized and studied.
为了系统地归纳统计学习理论与支持向量机的基本思想和算法,总结目前该领域的最新研究成果。
The highlights of statistical learning theory (SLT), the principle and the crucial elements of support vector machine (SVM) were introduced, and the method for flood forecast modeling based on support vector machine was discussed.
对统计学习理论和支持向量机的基本内容和核心思想进行了简要的介绍,探讨了基于支持向量机的洪水预报模型的建模方法。
The Traditional Statistics is a gradual theory which the amount of specimen is tending to infinite, while Statistical Learning Theory (SLT) is a theory at the condition of small specimen amount.
传统统计学研究的是样本数目趋于无穷大时的渐进理论,而统计学习理论研究的是小样本条件下的学习理论。
The Foundation of Statistical Learning Theory with Rough Samples;
基于粗糙样本的统计学习理论的基础
The Theoretical Foundations of Statistical Learning Theory of Birough Samples
基于双重粗糙样本的统计学习理论的理论基础
The Key Theorem of Statistical Learning Theory on Sugeno Measure Spaces;
SUGENO测度空间上统计学习理论的关键定理
The Key Theorem of Statistical Learning Theory on Possibility Measure Spaces;
可能性空间上统计学习理论的关键定理
The Key Theirem of Statistical Learning Theory about Fuzzy Examples;
基于模糊样本的统计学习理论关键定理
Study on Statistical Learning Theory and Their Applications in Geoscience;
统计学习理论及其在地学中的应用研究
Study of Support Vector Machines Algorithm Based on Statistical Learning Theory;
基于统计学习理论的支持向量机算法研究
Tourism demand forecast and analysis to Yunnan based onstatistical learning theory;
基于统计学习理论的云南旅游需求预测与分析
Identification of operational bridge structure responses using statistical learn theory
基于统计学习理论的运营桥梁结构的响应辨识
Statistical learning theory of complex samples on Sugeno measure space
Sugeno测度空间基于复样本的统计学习理论
An Adaptive Method of Online Handwritten Signature Verification Based on Statistical Learning Theory;
统计学习理论框架下联机手写签名识别问题的自适应方法
Key Technologies of Failure Analysis and Reliability Prediction Based on Statistical Learning Theory;
基于统计学习理论的故障分析与可靠度预测技术研究
The Research of Designing Web-based Learning System with Knowledge Management Theory;
运用知识管理理论设计网络学习系统的研究
The Theory of Self-regulated Learning and Its Inspiration for Systematic Instructional Design;
自我调节学习理论对系统化教学设计的启示
The Principle of Design for CAI System is Founded on Constructivism;
基于建构主义学习理论的CAI系统设计原则
An Inquiry into the Relationship between Learning Theory and Teaching Design Theory;
学习理论与教学设计理论关系的探讨
Inspiring the Students Study Interest Improving Educational Teaching Effect;
激发学生学习兴趣 提高教育教学效果——《概率论与数理统计》教学体会
Applying Psychological Theories to Design Multi-media Learning Environment;
整合心理学理论设计多媒体学习环境
