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1)  pseudo-entropy
拟熵
1.
The cross-entropy of neural network’s actual output and target output and the pseudo-entropy of the hidden node’s output are used as cost function, and entropy cycle strategy is used to opimize the parameters of the network, and a simple neural network structure can be obtained by deleting and merging the hidden layer neurons at last.
其实质是依据Shannon熵原理,定义神经网络隐层节点输出的拟熵,该熵与Shannon熵对不确定性的描述具有相同的效果,但克服了Shannon熵固有的缺点。
2.
The pseudo-entropy of hidden layer node output is defined on the principle of the shannon entropy,and these two different definitions of entropy have approximately the same effectiveness on the description of uncertainty,but the new definition of entropy avoids the undefinition on zero values of information.
文章依据Shannon熵原理定义了神经网络隐层节点输出的拟熵,该熵与Shannon熵对不确定性的描述具有相同的效果,但克服了Shannon熵中无定义和零值的缺点。
2)  pseudo-entropy of weights
权值拟熵
1.
Based on pseudo-entropy of weights,a new method is proposed to integrate pruning algorithm with sensitivity weights.
提出了一种基于权值拟熵的“剪枝算法”与权值敏感度相结合的新方法,在“剪枝算法”中将权值拟熵作为惩罚项加入目标函数中,使多层前向神经网络在学习过程中自动约束权值分布,并以权值敏感度作为简化标准,避免了单纯依赖权值大小剪枝的随机性。
3)  quasi-fuzzy entropy
拟模糊熵
4)  quasi-entropy weight
拟熵权
1.
For the problem to select the best book supplier in procurement bidding,this paper sets up a satisfaction evaluation index of the supplier by presenting the fuzzy comprehensive evaluation method of the supplier\'s quasi-entropy weight.
针对中文图书采购招标供应商优选问题,在建立一套评价指标体系的基础上,提出采购招标的拟熵权模糊综合评价法。
2.
A relatively perfect and scientific evaluation index system for evaluation factor of quantitative fuzziness has been set up by applying the method of quasi-entropy weight fuzzy evaluation to comprehensively evaluate librarians.
拟熵权模糊评判法应用于图书馆员综合素质评价之中,建立了一个对于量化模糊性评价因素来说相对完善的评价体系,并结合实例利用Matlab编程实现计算机求解,为图书馆的管理与人力资源开发提供更加科学和实用的技术依据。
3.
Based on the study of the existing literatures,this paper uses a new function to improve the entropy weight and proposes a fuzzy comprehensive evaluation method of library Website with quasi-entropy weight.
本文在研究现有文献的基础上,利用一个新的函数对熵权加以改进,提出了图书馆网站拟熵权模糊综合评判法。
5)  characteristic e
特征拟熵与紊流拟熵
6)  b-quasi fuzzy entropy
b-拟模糊熵
1.
Results Some asymptotic bound for b-quasi fuzzy entropy,b-quasi conditional fuzzy entropy,b-quasi mutual information and some meaning results are obtained.
结果得到b-拟模糊熵、b-拟条件模糊熵、b-拟互信息的渐近界的定义和一些良好的性质及定理。
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