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1. chinaXiv:202106.00009 [pdf]

Complex-valued Deng Entropy

Lipeng Pan; Yong Deng
Subjects: Computer Science >> Other Disciplines of Computer Science

Complex evidence theory has been applied to several fields due to its advantages in modeling and processing uncertain information. However,to measure the uncertainty of the complex mass function is still an open issue. The main contribution of this paper is to propose a complex-valued Deng entropy. The complex-valued Deng entropy can effectively measure the uncertainty of the mass function in the complex-valued framework. Meanwhile, the complex-valued Deng entropy is a generalization of the Deng entropy and Shannon entropy. That is, the complex-valued Deng entropy can degenerate to classical Deng entropy when the complex-valued mass function degenerates to a mass function in real space. In addition, the proposed complex-valued Deng entropy can also degenerates to Shannon entropy when the complex-valued mass function degenerates to a probability distribution in real space. Some numerical examples demonstrate the compatibility and effectiveness of the complex-valued Deng entropy.

submitted time 2021-06-03 Hits559Downloads143 Comment 0

2. chinaXiv:202106.00005 [pdf]

Complex-valued Renyi Entropy

Lipeng Pan; Yong Deng
Subjects: Computer Science >> Other Disciplines of Computer Science

Complex-valued expression models have been widely used in the application of intelligent decision systems. However, there is a lack of entropy to measure the uncertain information of the complex-valued probability distribution. Therefore, how to reasonably measure the uncertain information of the complex-valued probability distribution is a gap to be filled. In this paper, inspired by the Renyi entropy, we propose the Complex-valued Renyi entropy, which can measure uncertain information of the complex-valued probability distribution under the framework of complex numbers, and is also the first time to measure uncertain information in the complex space. The Complex-valued Renyi entropy contains the features of the classical Renyi entropy, i.e., the Complex-valued Renyi Entropy corresponds to different information functions with different parameters q. Meanwhile, the Complex-valued Renyi entropy has some properties, such as non-negativity, monotonicity, etc. Some numerical examples can demonstrate the flexibilities and reasonableness of the Complex-valued Renyi entropy.

submitted time 2021-05-31 Hits430Downloads88 Comment 0

3. chinaXiv:202105.00090 [pdf]

基于深度学习神经网络的电池分容阶段容量预测的方法

孙瑜
Subjects: Computer Science >> Computer Application Technology

本文提出了一个使用深度学习方法预测锂离子电池分容工序的容量的解决方案。该方案从化成和分容工序中提取部分工步的物理观测值记录作为特征,训练了一个深度神经网络(Deep Neural Network, DNN)实现了电池容量的精准预测。据测试,该模型预测的电池容量与真实值相比,平均百分比绝对误差(Mean Absolute Percentage Error, MAPE)仅为0.78%。将该模型与生产线结合,可以大大缩减生产时间与能耗,降低电池生产成本。

submitted time 2021-05-29 Hits439Downloads89 Comment 0

4. chinaXiv:202105.00077 [pdf]

二维光学刺激下的视觉感知定律

祝锐; 刘玉红; 王体春; 陈龙聪; 谢正祥
Subjects: Computer Science >> Computer Application Technology
Subjects: Engineering and technical science >> Optical Engineering

人类对刺激量的感知分为数量感知和质量感知。无论是韦伯-费克纳(Weber-Fechner)的对数感觉定律还是史蒂文斯(Stevens)的幂函数感觉定律,都是关于感觉量与一维亮度刺激之间定量关系的定律。图像属于具有二维亮度分布特征的刺激量。本文研究的是二维亮度刺激的质量的感知,即二维亮度刺激质量好坏程度的感知。好坏程度是一个模糊的心理学概念,因此我们需要用模糊数学的方法来量化图像视觉感知质量的好坏程度,即建立一个模糊隶属函数PQ来定量表示图像视觉质量的好与坏的程度。

submitted time 2021-05-24 Hits546Downloads131 Comment 0

5. chinaXiv:202105.00070 [pdf]

Copula熵:理论和应用

马健
Subjects: Statistics >> Mathematical Statistics
Subjects: Computer Science >> Computer Application Technology
Subjects: Information Science and Systems Science >> Basic Disciplines of Information Science and Systems Science

统计独立性是统计学和机器学习领域的基础性概念,如何表示和度量统计独立性是该领域的基本问题。Copula理论提供了统计相关性表示的理论工具,而Copula熵理论则给出了度量统计独立性的概念工具。本文综述了Copula熵的理论和应用,概述了其基本概念和定理,以及估计方法。介绍了Copula熵研究的最新进展,包括其在统计学四个基本问题(结构学习、关联发现、变量选择和时序因果发现等)上的理论应用。讨论了四个理论应用之间的关系,以及其对应的深层次的相关性和因果性概念之间的联系,并将Copula熵的(条件)独立性度量框架与基于核函数和距离的相关性度量框架进行了对比。简述了Copula熵在水文学、环境气象学、认知神经学、系统生物学、老年医学和能源工程等领域的实际应用。

submitted time 2021-05-21 Hits889Downloads218 Comment 0

6. chinaXiv:202104.00004 [pdf]

QZNs: Quantum Z-numbers

Deng, Jixiang; Deng, Yong
Subjects: Computer Science >> Integration Theory of Computer Science

Because of the efficiency of modeling fuzziness and vagueness, Z-number plays an important role in real practice. However, Z-numbers, defined in the real number field, lack the ability to process the quantum information in quantum environment. It is reasonable to generalize Z-number into its quantum counterpart. In this paper, we propose quantum Z-numbers (QZNs), which are the quantum generalization of Z-numbers. In addition, seven basic quantum fuzzy operations of QZNs and their corresponding quantum circuits are presented and illustrated by numerical examples. Moreover, based on QZNs, a novel quantum multi-attributes decision making (MADM) algorithm is proposed and applied in medical diagnosis. The results show that, with the help of quantum computation, the proposed algorithm can make diagnoses correctly and efficiently.

submitted time 2021-04-12 Hits690Downloads336 Comment 0

7. chinaXiv:202103.00068 [pdf]

自监督图像增强及去噪

张雨
Subjects: Computer Science >> Computer Software

This paper proposes a self-supervised low light image enhancement method based on deep learning, which can improve the image contrast and reduce noise at the same time to avoid the blur caused by pre-/post-denoising. The method contains two deep sub-networks, an Image Contrast Enhancement Network (ICE-Net) and a Re-Enhancement and Denoising Network (RED-Net). The ICE-Net takes the low light image as input and produces a contrast enhanced image. The RED-Net takes the result of ICE-Net and the low light image as input, and can re-enhance the low light image and denoise at the same time. Both of the networks can be trained with low light images only, which is achieved by a Maximum Entropy based Retinex (ME-Retinex) model and an assumption that noises are independently distributed. In the ME-Retinex model, a new constraint on the reflectance image is introduced that the maximum channel of the reflectance image conforms to the maximum channel of the low light image and its entropy should be the largest, which converts the decomposition of reflectance and illumination in Retinex model to a non-ill-conditioned problem and allows the ICE-Net to be trained with a self-supervised way. The loss functions of RED-Net are carefully formulated to separate the noises and details during training, and they are based on the idea that, if noises are independently distributed, after the processing of smoothing filters (\eg mean filter), the gradient of the noise part should be smaller than the gradient of the detail part. It can be proved qualitatively and quantitatively through experiments that the proposed method is efficient.

submitted time 2021-03-01 Hits1836Downloads324 Comment 0

8. chinaXiv:202010.00060 [pdf]

一种基于BERT和文本相似度的先进的ICD9术语标准化方法

刘宜佳; 纪斌; 余杰; 谭郁松; 马俊; 吴庆波
Subjects: Computer Science >> Natural Language Understanding and Machine Translation

ICD-9术语标准化任务旨在将医生在病历中记录的口语术语标准化为《国际疾病分类》(ICD-9)第九版中定义的标准术语。在本文中,我们首先提出一种基于BERT和文本相似度的方法(BTSBM),该方法将BERT分类模型与文本相似度计算算法相结合:1)使用N-gram算法为每种口语术语生成候选标准术语集(CSTS) ,用作下一步的训练数据集和测试数据集; 2)使用BERT分类模型对正确的标准术语进行分类。在这种BTSBM方法中,如果采用较大规模的CSTS作为测试数据集,则训练数据集也需要保持较大规模。但是,每个CSTS中只有一个正样本。因此,扩大规模将导致正负样本比例的严重失衡,这将严重降低系统性能。如果我们将测试数据集保持相对较小,则CSTS准确性(CSTSA)将大大降低,这将导致非常低的系统性能上限。为了解决上述问题,我们然后提出了一种优化的术语标准化方法,称为先进的BERT和基于文本相似性方法(ABTSBM),其中1)使用大规模初始CSTS来维持较高的CSTSA以确保较高的系统性能上限; 2)根据身体结构对CSTS进行降噪,以减轻正负样本的不平衡而不降低CSTSA; 3)引入focal loss损失函数以进一步促进正负样本的平衡。实验表明,ABTSBM方法的精度高达83.5%,比BTSBM高0.6%,而ABTSBM的计算成本比BTSBM低26.7%。

submitted time 2020-10-27 Hits6690Downloads911 Comment 0

9. chinaXiv:202010.00061 [pdf]

基于span分类模型的医学概念抽取方法

汤勇韬; 余杰; 李莎莎; 纪斌; 谭郁松; 吴庆波
Subjects: Computer Science >> Natural Language Understanding and Machine Translation

最近,如何构造电子病历(EMR)引起了研究人员的极大关注。从EMR中提取临床概念是EMR结构化的关键部分。临床概念提取的性能将直接影响与EMR结构化相关的下游任务的性能。但是,主流方法中,序列标记模型有一些缺点。基于序列标记的临床概念提取方法不符合人类的语言认知模型。同时,这种方法产生的提取结果很难与下游任务耦合,这将导致错误传播并影响下游任务的性能。为了解决这些问题,我们提出了一种基于span分类的方法,通过考虑字符序列的整体语义而不是每个字符的语义来提高临床概念提取任务的性能。我们将此模型称为span分类模型。实验表明,span分类模型在2012年i2b2 NLP挑战赛的语料库中获得了最佳的微观平均F1得分(81.22%),并获得了与2010年i2b2 NLP挑战赛的SOTA相当的F1得分(89.25%)。此外,我们的方法的性能始终优于序列标记模型,例如BiLSTM-CRF模型和softmax分类器。

submitted time 2020-10-27 Hits6388Downloads798 Comment 0

10. chinaXiv:202010.00067 [pdf]

融合基于注意力机制的span特定和上下文语义表示的基于span的实体和关系联合抽取

Bin Ji
Subjects: Computer Science >> Natural Language Understanding and Machine Translation

基于span的联合提取模型已显示出它们在实体识别和关系提取上的效率。 这些模型将文本span视为候选实体,并将span元组视为候选关系元组。 span语义表示在实体识别和关系提取中都是共享的,而现有模型无法很好地捕获这些候选实体和关系的语义。 为了解决这些问题,我们引入了基于span的联合提取框架和基于注意的语义表示。 特别地,注意力用于计算语义表示,包括span特定和上下文表示。 我们将进一步研究四种注意变量在生成上下文语义表示中的作用。 实验表明,我们的模型优于以前的系统,并在ACE2005,CoNLL2004和ADE上达到了最优的结果。

submitted time 2020-10-26 Hits5291Downloads714 Comment 0

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