Entropy (Basel, Switzerland)最新文献_第9页

Entropy as a High-Level Feature for XAI-Based Early Plant Stress Detection. 熵作为基于xai的植物早期胁迫检测的高级特征。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-03 DOI: 10.3390/e24111597

Maxim Lysov, Irina Maximova, Evgeny Vasiliev, Alexandra Getmanskaya, Vadim Turlapov

{"title":"Entropy as a High-Level Feature for XAI-Based Early Plant Stress Detection.","authors":"Maxim Lysov, Irina Maximova, Evgeny Vasiliev, Alexandra Getmanskaya, Vadim Turlapov","doi":"10.3390/e24111597","DOIUrl":"https://doi.org/10.3390/e24111597","url":null,"abstract":"This article is devoted to searching for high-level explainable features that can remain explainable for a wide class of objects or phenomena and become an integral part of explainable AI (XAI). The present study involved a 25-day experiment on early diagnosis of wheat stress using drought stress as an example. The state of the plants was periodically monitored via thermal infrared (TIR) and hyperspectral image (HSI) cameras. A single-layer perceptron (SLP)-based classifier was used as the main instrument in the XAI study. To provide explainability of the SLP input, the direct HSI was replaced by images of six popular vegetation indices and three HSI channels (R630, G550, and B480; referred to as indices), along with the TIR image. Furthermore, in the explainability analysis, each of the 10 images was replaced by its 6 statistical features: min, max, mean, std, max-min, and the entropy. For the SLP output explainability, seven output neurons corresponding to the key states of the plants were chosen. The inner layer of the SLP was constructed using 15 neurons, including 10 corresponding to the indices and 5 reserved neurons. The classification possibilities of all 60 features and 10 indices of the SLP classifier were studied. Study result: Entropy is the earliest high-level stress feature for all indices; entropy and an entropy-like feature (max-min) paired with one of the other statistical features can provide, for most indices, 100% accuracy (or near 100%), serving as an integral part of XAI.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689005/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40457704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Pruning Decision Rules by Reduct-Based Weighting and Ranking of Features. 基于约简的特征加权和排序的剪枝决策规则。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-03 DOI: 10.3390/e24111602

Urszula Stańczyk

{"title":"Pruning Decision Rules by Reduct-Based Weighting and Ranking of Features.","authors":"Urszula Stańczyk","doi":"10.3390/e24111602","DOIUrl":"https://doi.org/10.3390/e24111602","url":null,"abstract":"Methods and techniques of feature selection support expert domain knowledge in the search for attributes, which are the most important for a task. These approaches can also be used in the process of closer tailoring of the obtained solutions when dimensionality reduction is aimed not only at variables but also at learners. The paper reports on research where attribute rankings were employed to filter induced decision rules. The rankings were constructed through the proposed weighting factor based on the concept of decision reducts-a feature reduction mechanism embedded in the rough set theory. Classical rough sets operate only in discrete input space by indiscernibility relation. Replacing it with dominance enables processing real-valued data. Decision reducts were found for both numeric and discrete attributes, transformed by selected discretisation approaches. The calculated ranking scores were used to control the selection of decision rules. The performance of the resulting rule classifiers was observed for the entire range of rejected variables, for decision rules with conditions on continuous values, discretised conditions, and also inferred from discrete data. The predictive powers were analysed and compared to detect existing trends. The experiments show that for all variants of the rule sets, not only was dimensionality reduction possible, but also predictions were improved, which validated the proposed methodology.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689530/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40457709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Mather β-Function for Ellipses and Rigidity. 椭圆和刚性的Mather β函数。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-03 DOI: 10.3390/e24111600

Michael Bialy

引用次数: 1

Configurations of Proto-Cell Aggregates with Anisotropy: Gravity Promotes Complexity in Theoretical Biology. 具有各向异性的原细胞聚集体的构型:重力促进理论生物学的复杂性。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-03 DOI: 10.3390/e24111598

Juan César Flores

引用次数: 0

Discrete Fourier Transform with Denoise Model Based Least Square Wiener Channel Estimator for Channel Estimation in MIMO-OFDM. 基于离散傅立叶变换带噪模型的最小二乘维纳信道估计在MIMO-OFDM中的信道估计。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-03 DOI: 10.3390/e24111601

Dhanasekaran S, SatheeshKumar Palanisamy, Fahima Hajjej, Osamah Ibrahim Khalaf, Ghaida Muttashar Abdulsahib, Ramalingam S

{"title":"Discrete Fourier Transform with Denoise Model Based Least Square Wiener Channel Estimator for Channel Estimation in MIMO-OFDM.","authors":"Dhanasekaran S, SatheeshKumar Palanisamy, Fahima Hajjej, Osamah Ibrahim Khalaf, Ghaida Muttashar Abdulsahib, Ramalingam S","doi":"10.3390/e24111601","DOIUrl":"https://doi.org/10.3390/e24111601","url":null,"abstract":"Multiple-input Multiple-Output (MIMO) systems require orthogonal frequency division multiplexing to operate efficiently in multipath communication (OFDM). Channel estimation (C.E.) is used in channel conditions where time-varying features are required. The existing channel estimation techniques are highly complicated. A channel estimation algorithm is needed to estimate the received signal's correctness. In order to resolve this complexity in C.E. methodologies, this paper developed an Improved Channel Estimation Algorithm integrated with DFT-LS-WIENER (ICEA-DA). The Least Square (L.S.) and Minimum Mean Square Error (MMSE) algorithms also use the Discrete Fourier Transform (DFT)-based channel estimation method. The DFT-LS-WIENER channel estimation approach is recommended for better BER performance. The input signal is modulated in the transmitter module using the Quadrature Phase Shift Keying (QPSK) technique, pulse modeling, and least squares concepts. The L.S. Estimation technique needs the channel consistent throughout the estimation period. DFT joined with L.S. gives higher estimation precision and limits M.S.E. and BER. Experimental analysis of the proposed state-of-the-art method shows that DFT-LS-WIENER provides superior performance in terms of symbol error rate (S.E.R.), bit error rate (BER), channel capacity (CC), and peak signal-to-noise (PSNR). At 15 dB SNR, the proposed DFT-LS-WIENER techniques reduce the BER of 48.19%, 38.19%, 14.8%, and 14.03% compared to L.S., LS-DFT, MMSE, and MMSE-DFT. Compared to the conventional algorithm, the proposed DFT-LS-WIENER outperform them.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689103/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40457708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Bearing Fault Diagnosis Method Based on Convolutional Neural Network and Knowledge Graph. 基于卷积神经网络和知识图的轴承故障诊断方法。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-02 DOI: 10.3390/e24111589

Zhibo Li, Yuanyuan Li, Qichun Sun, Bowei Qi

{"title":"Bearing Fault Diagnosis Method Based on Convolutional Neural Network and Knowledge Graph.","authors":"Zhibo Li, Yuanyuan Li, Qichun Sun, Bowei Qi","doi":"10.3390/e24111589","DOIUrl":"https://doi.org/10.3390/e24111589","url":null,"abstract":"An effective fault diagnosis method of bearing is the key to predictive maintenance of modern industrial equipment. With the single use of equipment failure mechanism or operation of data, it is hard to resolve multiple complex variable working conditions, multiple types of fault and equipment malfunctions and failures related to knowledge and data. In order to solve these problems, a fault diagnosis method based on the fusion of deep learning with a knowledge graph is proposed in this paper. Firstly, the knowledge rules of bearing data is used for entity extraction. Next, the multiscale optimized convolutional neural network (MOCNN) proposed in this paper is used for fault classification to achieve relationship extraction. Finally, the fault diagnosis graph of the bearing is constructed for fault-assisted decision-making as well as the detailed display of fault information. According to experiment analysis, the fault diagnosis model based on MOCNN proposed in this paper, which integrates the end-to-end convolutional neural network and the attention mechanism, still achieves an accuracy of 97.86% under the data set of 160 types of faults. Compared with the deep learning models such as Resnet and Inception in the noise environment of multiple working conditions and variable working conditions, the model proposed in this paper not only shows a faster convergence speed and stable performance, but also a higher accuracy in evaluation indicators, which is beneficial to practical use.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689069/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40694571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Testing the Intercept of a Balanced Predictive Regression Model. 检验平衡预测回归模型的截距。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-02 DOI: 10.3390/e24111594

Qijun Wang, Xiaohui Liu, Yawen Fan, Ling Peng

引用次数: 1

Research on Insulator Defect Detection Based on an Improved MobilenetV1-YOLOv4. 基于改进MobilenetV1-YOLOv4的绝缘子缺陷检测研究。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-02 DOI: 10.3390/e24111588

Shanyong Xu, Jicheng Deng, Yourui Huang, Liuyi Ling, Tao Han

{"title":"Research on Insulator Defect Detection Based on an Improved MobilenetV1-YOLOv4.","authors":"Shanyong Xu, Jicheng Deng, Yourui Huang, Liuyi Ling, Tao Han","doi":"10.3390/e24111588","DOIUrl":"https://doi.org/10.3390/e24111588","url":null,"abstract":"Insulator devices are important for transmission lines, and defects such as insulator bursting and string loss affect the safety of transmission lines. In this study, we aim to investigate the problems of slow detection speed and low efficiency of traditional insulator defect detection algorithms, and to improve the accuracy of insulator fault identification and the convenience of daily work; therefore, we propose an insulator defect detection algorithm based on an improved MobilenetV1-YOLOv4. First, the backbone feature extraction network of YOLOv4 'Backbone' is replaced with the lightweight module Mobilenet-V1. Second, the scSE attention mechanism is introduced in stages of preliminary feature extraction and enhanced feature extraction, sequentially. Finally, the depthwise separable convolution substitutes the 3 × 3 convolution of the enhanced feature extraction network to reduce the overall number of network parameters. The experimental results show that the weight of the improved algorithm is 57.9 MB, which is 62.6% less than that obtained by the MobilenetV1-YOLOv4 model; the average accuracy of insulator defect detection is improved by 0.26% and reaches 98.81%; and the detection speed reaches 190 frames per second with an increase of 37 frames per second.","PeriodicalId":520609,"journal":{"name":"Entropy (Basel, Switzerland)","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9689300/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40694570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Demonstration of the Holonomically Controlled Non-Abelian Geometric Phase in a Three-Qubit System of a Nitrogen Vacancy Center. 氮空位中心三量子位系统中完整控制非阿贝尔几何相位的证明。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-02 DOI: 10.3390/e24111593

Shaman Bhattacharyya, Somnath Bhattacharyya

引用次数: 1

Gaussian Multiuser Wiretap Channels in the Presence of a Jammer-Aided Eavesdropper. 干扰辅助窃听器存在下的高斯多用户窃听信道。

IF 2.7

Entropy (Basel, Switzerland) Pub Date : 2022-11-02 DOI: 10.3390/e24111595

Rémi A Chou, Aylin Yener

引用次数: 2