模糊积分是一种多分类器联合算法。
Fuzzy integral is a valid algorithm for combining classifiers.
多分类器组合是对决策层的数据进行融合。
The multiple classifiers combination fuses the decision level data.
多分类器组合是提高识别效果的一条有效途径。
The combination of multiple classifiers is one of the effective ways to improve the recognition performance.
然后，利用证据组合规则对多分类器进行集成。
Then, all the classification results are integrated by the use of D-S combination rule.
多分类器联合是解决复杂模式识别问题的有效办法。
A combination of multiple classifiers is a powerful solution to the difficult pattern recognition problem.
多分类器联合是解决复杂模式识别问题的有效办法。
A combination of multiple classifiers is a powerful solution to difficult pattern recognition problem.
多分类器组合是解决复杂模式识别问题的有效办法。
Multiple classifiers ensemble is an effective method to solve complex classification problems in pattern recognition field.
将三个或更多分类器之间的关联添加到静态结构图中。
Adds an association among three or more classifiers to your Static Structure diagram.
重点探索了以不同特征作为输入的组合多分类器方法。
This article has summarized current methods of combining multiple classifiers, and investigated on embodying different features as input vectors.
本文对多分类器融合模式识别的设计方法进行了研究。
This paper studies the design of pattern recognition system based multiple classifiers combination.
在车牌字符识别中引入了误识模型和多分类器集成技术。
The techniques of mis-recognition model and multiple classifier combination are proposed and used in the system.
多分类器集成系统是当前机器学习领域的一个研究热点。
Integration of multiple classifier machine learning system is currently a hot research field.
多分类器组合策略有两类：多分类器融合和多分类器选择。
There are two strategies for multiple classifiers combination: multiple classifiers fusion and multiple classifiers selection.
提出了一种基于子带处理多分类器融合的说话人识别方法。
A method of speaker recognition based on sub-band processing and multi-classifier combination is presented.
本文提出一种联机识别自然手写体汉字的多分类器集成模型。
In the paper, a new multiple classifiers integrated model of online recognizing natural handwritten Chinese character is presented.
第三章，研究了基于不同模式特征的多分类器联合方法问题。
In chapter 3, the method of multi classifier combination based on different pattern features is studied.
组合多分类器可以看作是一种用于获得较高识别效果的混合系统。
Combining Multiple Classifiers can be viewed as a novel hybrid system to achieve high recognition accuracy for Text Independent Speaker Identification.
多分类器结合后，总体分类精度有一定的提高，但提高幅度不大。
The accuracy had been improved by combining classifiers, although the improvement was not as obvious as expected previously.
提出将多分类器组合算法应用于蛋白质-蛋白质相互作用位点预测。
The methods of multiple classifiers combination are proposed to classify protein-protein interaction sites.
为改善多分类器系统的分类性能，提出了基于广义粗集的集成特征选择方法。
For improving the performance of multiple classifier system, a novel method of ensemble feature selection is proposed based on generalized rough set.
针对空战目标识别中机型识别这一问题，提出了基于多分类器融合的识别方法。
Aiming at aircraft type recognition in the field of automatic target recognition, a method based on combining classifiers is proposed.
实验结果表明，该方法能够用可理解性好的模糊系统实现低错误率的多分类器融合。
The experimental results show that the proposed method can fuse multiple classifiers with low classification error rate based on comprehensible fuzzy systems.
多分类器组合利用不同分类器、不同特征之间的互补性，提高了组合分类器的识别率。
Multiple classifiers combination makes use of the complementarities of different classifiers and different characters to improve recognition correctness.
在统计建模中，有很多分类器构建算法，每个算法构造一组不同的关于数据的假设集合。
In statistical modeling, there are various algorithms to build a classifier, and each algorithm makes a different set of assumptions about the data.
为了提高语音情感的正确识别率，提出一种基于多分类器投票组合的语音情感识别新方法。
A new method of speech emotion recognition via voting combination of multiple classifiers is proposed for improving speech emotion classification rate.
为了提高遥感影像分类精度，从抽象级和测量级的两个层次出发，提出混合多分类器结合算法。
To enhance the accuracy of image classification, proposed hybrid multiple classifier combination method from abstract level and measurement level.
多分类器系统能够在一定程度上弥补单个分类器的缺陷，因此它在模式识别中得到了广泛的应用。
Since multiple classifier systems can to some extent improve the performance of classification, the technique has been widely used in various fields of pattern recognition.
针对标准数据集在评估多分类器系统的组合方法时存在的不足，设计了一种新的分类器模拟算法。
Aiming at the deficiency of evaluating classifier combination methods with standard data sets, a new classifier simulation algorithm was proposed.
针对标准数据集在评估多分类器系统的组合方法时存在的不足，设计了一种新的分类器模拟算法。
Aiming at the deficiency of evaluating classifier combination methods with standard data sets, a new classifier simulation algorithm was proposed.
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