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基于贝叶斯网络的水源涵养服务空间格局优化(英文)
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作者 曾莉 李晶 《地理学报:英文版》 SCIE CSCD 2019年第6期1021-1038,共18页
Water conservation is one of the most important ecosystem services of terrestrial ecosystems. Identifying the optimization regions of water conservation using Bayesian belief networks not only helps develop a better u... Water conservation is one of the most important ecosystem services of terrestrial ecosystems. Identifying the optimization regions of water conservation using Bayesian belief networks not only helps develop a better understanding of water conservation processes but also increases the rationality of scenario design and pattern optimization. This study establishes a water conservation network model. The model, based on Bayesian belief networks, forecasts the distribution probability of the water conservation projected under different land use scenarios for the year 2050 with the CA-Markov model. A key variable subset method is proposed to optimize the spatial pattern of the water conservation. Three key findings were obtained. First, among the three scenarios, the probability of high water conservation value was the largest under the protection scenario, and the design of this scenario was conducive to the formulation of future land use policies. Second, the key influencing factors impacting the water conservation included precipitation, evapotranspiration and land use, and the state set corresponding to the highest state of water conservation was mainly distributed in areas with high annual average rainfall and evapotranspiration and high vegetation coverage. Third, the regions suitable for optimizing water conservation were mainly distributed in the southern part of Maiji District in Tianshui, southwest of Longxian and south of Weibin District in Baoji, northeast of Xunyi County and northwest of Yongshou County in Xianyang, and west of Yaozhou District in Tongchuan. 展开更多
关键词 water conservation ECOSYSTEM services BAYESIAN BELIEF network SCENARIO analysis spatial SUITABILITY land use
Estimating survival benefit of adjuvant therapy based on a Bayesian network prediction model in curatively resected advanced gallbladder adenocarcinoma 预览
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作者 Zhi-Min Geng Zhi-Qiang Cai +9 位作者 Zhen Zhang Zhao-Hui Tang Feng Xue Chen Chen Dong Zhang Qi Li Rui Zhang Wen-Zhi Li Lin Wang Shu-Bin Si 《世界胃肠病学杂志:英文版》 SCIE CAS 2019年第37期5655-5666,共12页
BACKGROUND The factors affecting the prognosis and role of adjuvant therapy in advanced gallbladder carcinoma(GBC)after curative resection remain unclear.AIM To provide a survival prediction model to patients with GBC... BACKGROUND The factors affecting the prognosis and role of adjuvant therapy in advanced gallbladder carcinoma(GBC)after curative resection remain unclear.AIM To provide a survival prediction model to patients with GBC as well as to identify the role of adjuvant therapy.METHODS Patients with curatively resected advanced gallbladder adenocarcinoma(T3 and T4)were selected from the Surveillance,Epidemiology,and End Results database between 2004 and 2015.A survival prediction model based on Bayesian network(BN)was constructed using the tree-augmented na?ve Bayes algorithm,and composite importance measures were applied to rank the influence of factors on survival.The dataset was divided into a training dataset to establish the BN model and a testing dataset to test the model randomly at a ratio of 7:3.The confusion matrix and receiver operating characteristic curve were used to evaluate the model accuracy.RESULTS A total of 818 patients met the inclusion criteria.The median survival time was 9.0 mo.The accuracy of BN model was 69.67%,and the area under the curve value for the testing dataset was 77.72%.Adjuvant radiation,adjuvant chemotherapy(CTx),T stage,scope of regional lymph node surgery,and radiation sequence were ranked as the top five prognostic factors.A survival prediction table was established based on T stage,N stage,adjuvant radiotherapy(XRT),and CTx.The distribution of the survival time(>9.0 mo)was affected by different treatments with the order of adjuvant chemoradiotherapy(cXRT)>adjuvant radiation>adjuvant chemotherapy>surgery alone.For patients with node-positive disease,the larger benefit predicted by the model is adjuvant chemoradiotherapy.The survival analysis showed that there was a significant difference among the different adjuvant therapy groups(log rank,surgery alone vs CTx,P<0.001;surgery alone vs XRT,P=0.014;surgery alone vs cXRT,P<0.001).CONCLUSION The BN-based survival prediction model can be used as a decision-making support tool for advanced GBC patients.Adjuvant chemoradiotherapy is expec 展开更多
关键词 GALLBLADDER CARCINOMA BAYESIAN network Surgery ADJUVANT therapy Prediction model
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基于贝叶斯与生成式对抗网络的手写字文本识别算法 预览
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作者 王来兵 《黑龙江工业学院学报:综合版》 2019年第8期31-35,共5页
为了提高机器学习算法对手写字文本识别能力,克服个体手写字风格多变的干扰,设计了一种基于贝叶斯与生成式对抗网络的手写字文本识别算法。首先,建立10000个汉字的手写字数组头,每个汉字数组头后面依附100种手写体,构建起1000000帧汉字... 为了提高机器学习算法对手写字文本识别能力,克服个体手写字风格多变的干扰,设计了一种基于贝叶斯与生成式对抗网络的手写字文本识别算法。首先,建立10000个汉字的手写字数组头,每个汉字数组头后面依附100种手写体,构建起1000000帧汉字文本图像帧,作为后续学习训练的训练集数据输入。然后,利用贝叶斯线性模型,结合线性回归和先验分布,基于手写字图像样本数据库,进行有监督的机器学习训练,得到机器学习算子,完成针对手写字的粗识别。随后,根据生成式对抗网络原理,创建生成模型和判别模型,设计自适应潜在损失函数和迭代终止函数,解决深度学习普遍存在的过拟合问题,完成生成式对抗网络算子,完成针对手写字的深度识别。最后基于QTcreator开发的集成平台来实现所提算法的功能,其中,机器学习算子由OpenCV视觉函数实现,深度学习算子由TensorFlow框架实现。实验数据显示,相较于传统手写字识别算法而言,所提算法具有更高的手写字识别能力。 展开更多
关键词 文本识别 机器学习 贝叶斯 生成式对抗网络 先验分布 损失函数 TensorFlow
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Distributed adaptive Kalman filter based on variational Bayesian technique
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作者 Chen HU Xiaoming HU Yiguang HONG 《控制理论与技术:英文版》 EI CSCD 2019年第1期37-47,共11页
In this paper, distributed Kalman filter design is studied for linear dynamics with unknown measurement noise variance, which modeled by Wishart distribution. To solve the problem in a multi-agent network, a distribut... In this paper, distributed Kalman filter design is studied for linear dynamics with unknown measurement noise variance, which modeled by Wishart distribution. To solve the problem in a multi-agent network, a distributed adaptive Kalman filter is proposed with the help of variational Bayesian, where the posterior distribution of joint state and noise variance is approximated by a free-form distribution. The con vergence of the proposed algorithm is proved in two main steps: n oise statistics is estimated, where each age nt only use its local information in variational Bayesian expectation (VB-E) step, and state is estimated by a consensus algorithm in variational Bayesian maximum (VB-M) step. Finally, a distributed target tracking problem is investigated with simulations for illustration. 展开更多
关键词 DISTRIBUTED KALMAN FILTER adaptive FILTER MULTI-AGENT system VARIATIONAL BAYESIAN
An Overview and Perspectives On Bidirectional Intelligence:Lmser Duality,Double IA Harmony,and Causal Computation 预览
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作者 Lei Xu 《自动化学报:英文版》 CSCD 2019年第4期865-893,共29页
Advances on bidirectional intelligence are overviewed along three threads,with extensions and new perspectives.The first thread is about bidirectional learning architecture,exploring five dualities that enable Lmser s... Advances on bidirectional intelligence are overviewed along three threads,with extensions and new perspectives.The first thread is about bidirectional learning architecture,exploring five dualities that enable Lmser six cognitive functions and provide new perspectives on which a lot of extensions and particularlly flexible Lmser are proposed.Interestingly,either or two of these dualities actually takes an important role in recent models such as U-net,ResNet,and Dense Net.The second thread is about bidirectional learning principles unified by best yIng-yAng(IA)harmony in BYY system.After getting insights on deep bidirectional learning from a bird-viewing on existing typical learning principles from one or both of the inward and outward directions,maximum likelihood,variational principle,and several other learning principles are summarised as exemplars of the BYY learning,with new perspectives on advanced topics.The third thread further proceeds to deep bidirectional intelligence,driven by long term dynamics(LTD)for parameter learning and short term dynamics(STD)for image thinking and rational thinking in harmony.Image thinking deals with information flow of continuously valued arrays and especially image sequence,as if thinking was displayed in the real world,exemplified by the flow from inward encoding/cognition to outward reconstruction/transformation performed in Lmser learning and BYY learning.In contrast,rational thinking handles symbolic strings or discretely valued vectors,performing uncertainty reasoning and problem solving.In particular,a general thesis is proposed for bidirectional intelligence,featured by BYY intelligence potential theory(BYY-IPT)and nine essential dualities in architecture,fundamentals,and implementation,respectively.Then,problems of combinatorial solving and uncertainty reasoning are investigated from this BYY IPT perspective.First,variants and extensions are suggested for AlphaGoZero like searching tasks,such as traveling salesman problem(TSP)and attributed graph matching(AGM)that ar 展开更多
关键词 Autoencoder LMSER DUALITY outward attention associative recall concept formation imagining pattern transformation STD vs LTD RPCL skip connection feedback variational least redundancy Bayesian Ying Yang IA system best HARMONY best MATCHING image THINKING rational THINKING INTELLIGENCE potential theory Alpha-TSP Alpha-AGM graph MATCHING ME Player BYY Follower constraint satisfaction CAUSAL potential theory
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基于贝叶斯理论的多系统定位融合算法 预览
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作者 马欣鑫 邓平科 +2 位作者 陈威屹 张晓光 袁洪 《科学技术与工程》 北大核心 2019年第26期288-293,共6页
针对传统多系统融合定位中协作性较差,自适应性不足的问题,为多系统定位达到更好的效果,提高多系统协同定位算法中信息融合的高效性、场景间切换的适应性,对传统的多系统定位融合算法进行了改进。采用贝叶斯理论,多系统观测数据融合输入... 针对传统多系统融合定位中协作性较差,自适应性不足的问题,为多系统定位达到更好的效果,提高多系统协同定位算法中信息融合的高效性、场景间切换的适应性,对传统的多系统定位融合算法进行了改进。采用贝叶斯理论,多系统观测数据融合输入,建立贝叶斯概率观测模型,对多系统间定位信息直接交互,通过扩展卡尔曼滤波理论估计定位信息。在此基础上,利用各系统滤波新息和方差对场景间切换时系统概率进行实时更新,将估计结果以系统概率加权方式融合输出。仿真结果表明,在相同观测条件下,改进算法与传统定位算法相比,具有更好的稳定性及自适应性。 展开更多
关键词 贝叶斯 扩展卡尔曼滤波 多系统 跟踪定位
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基于本体和贝叶斯的知识共享系统设计
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作者 胡春美 《电子元器件与信息技术》 2019年第7期10-13,共4页
随着科学技术的飞速发展,对于很多专有领域来说,领域知识越加变得丰富,复杂性也越来越高。知识间复杂关系的表示以及多种知识的合理组织及共享也就成为了一项重要的研究课题。本文引入本体,贝叶斯理论和Lucene技术,提出一种设计思路,旨... 随着科学技术的飞速发展,对于很多专有领域来说,领域知识越加变得丰富,复杂性也越来越高。知识间复杂关系的表示以及多种知识的合理组织及共享也就成为了一项重要的研究课题。本文引入本体,贝叶斯理论和Lucene技术,提出一种设计思路,旨在对领域知识进行合理的组织和利用,发挥其应有的价值。该设计主要由三个大的模块组成:领域本体构建模块,知识文档检索模块,动态贝叶斯网推理决策模块。其适用于有大量文档和案例资料的领域知识共享系统。 展开更多
关键词 领域知识 本体 贝叶斯 检索 共享
基于HY-2A/SCAT数据极地海冰检测方法研究 预览
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作者 赵朝方 徐锐 赵可 《中国海洋大学学报:自然科学版》 CAS CSCD 北大核心 2019年第10期140-149,共10页
本文基于HY-2A/SCAT数据,采用贝叶斯算法、线性判别算法、支持向量机算法、基于主成分分析(Principal component Analysis,PCA)的BP神经网络算法对极地地区的海冰进行检测,并将检测结果与SSMIS海冰密集度数据进行比较。结果表明:四种检... 本文基于HY-2A/SCAT数据,采用贝叶斯算法、线性判别算法、支持向量机算法、基于主成分分析(Principal component Analysis,PCA)的BP神经网络算法对极地地区的海冰进行检测,并将检测结果与SSMIS海冰密集度数据进行比较。结果表明:四种检测算法得到的海冰边界介于SSMIS 0%~30%海冰密集度边界之间。在高风速条件下,海冰和海水的后向散射特征区分不明显可能造成冰水误判,以2013年9月16日北极海冰检测为例,贝叶斯算法检测结果误判最少,其次为基于PCA的BP神经网络算法,线性判别和支持向量机两种算法误判率较高。考虑到检测算法的运行效率和冰水误判率,选择贝叶斯算法和支持向量机算法进行海冰面积的季节趋势分析,两种算法得到的海冰面积变化趋势都能反映季节性变化,且在海冰生长季支持向量机算法探测的海冰面积与SSMIS 15%密集度海冰范围保持较好的一致性。 展开更多
关键词 HY-2A/SCAT 海冰检测 贝叶斯 线性判别 支持向量机 神经网络
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Clustering in the Wireless Channel with a Power Weighted Statistical Mixture Model in Indoor Scenario 预览
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作者 Yupeng Li Jianhua Zhang +1 位作者 Pan Tang Lei Tian 《中国通信:英文版》 SCIE CSCD 2019年第7期83-95,共13页
Cluster-based channel model is the main stream of fifth generation mobile communications, thus the accuracy of clustering algorithm is important. Traditional Gaussian mixture model (GMM) does not consider the power in... Cluster-based channel model is the main stream of fifth generation mobile communications, thus the accuracy of clustering algorithm is important. Traditional Gaussian mixture model (GMM) does not consider the power information which is important for the channel multipath clustering. In this paper, a normalized power weighted GMM (PGMM) is introduced to model the channel multipath components (MPCs). With MPC power as a weighted factor, the PGMM can fit the MPCs in accordance with the cluster-based channel models. Firstly, expectation maximization (EM) algorithm is employed to optimize the PGMM parameters. Then, to further increase the searching ability of EM and choose the optimal number of components without resort to cross-validation, the variational Bayesian (VB) inference is employed. Finally, 28 GHz indoor channel measurement data is used to demonstrate the effectiveness of the PGMM clustering algorithm. 展开更多
关键词 channel MULTIPATH CLUSTERING mmWave Gaussian mixture model EXPECTATION MAXIMIZATION VARIATIONAL Bayesian INFERENCE
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基于互信息熵-近红外光谱的过程模式故障检测 预览
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作者 高爽 栾小丽 刘飞 《光谱学与光谱分析》 SCIE EI CAS CSCD 北大核心 2019年第6期1736-1741,共6页
近红外光谱分析在工业过程故障检测方面具有独特的优势,是一种准确且高效的方法。结合互信息熵和传统的主成分分析,对近红外光谱特征信息进行提取,通过构建过程的模式来刻画工业过程的运行状态。利用近红外光谱数据,从有机分子含氢基团... 近红外光谱分析在工业过程故障检测方面具有独特的优势,是一种准确且高效的方法。结合互信息熵和传统的主成分分析,对近红外光谱特征信息进行提取,通过构建过程的模式来刻画工业过程的运行状态。利用近红外光谱数据,从有机分子含氢基团振动信息中获取工业系统的过程模式,从微观分子层面探索提高工业过程故障检测准确率的有效方法,结合贝叶斯统计学习技术,提出了基于近红外光谱数据的工业过程故障检测技术。针对近红外光谱信息量丰富,谱带较宽,特征性不强的特点,首先对工业过程不同运行状态下的近红外光谱吸光度数据进行一阶导数预处理,采用主成分分析法(principal component analysis,PCA)压缩光谱数据量,扩大不同运行状态下光谱特征信息的差异性,提取光谱的内部特征信息。然后采用互信息熵(mutual information entropy,MIE)作为光谱特征信息相关性度量函数,基于最小冗余最大相关算法进一步减少光谱特征信息间的冗余并最大化光谱特征信息与类别的相关性,弥补了PCA无监督特征波长选择的不足,提出一种基于PCA-MIE的过程模式构建方法,获得的过程模式子集更紧凑更具类别表现力。再利用贝叶斯统计学习算法,根据后验概率对构建的模式子集进行决策,判别生产过程的正常状态和故障状态。由于过程模式子集结合了PCA浓聚方差的优势和互信息熵相关性测度的特征信息选择方法,蕴含了更多的近红外光谱的本质信息与内在规律,从而更能刻画工业过程的运行状态。接着,设置测试准确率TA作为评估标准,用以评价故障检测方法的性能效果。最后利用某化工厂提供的原油脱盐脱水过程近红外光谱数据对所提方法进行验证,并与传统近红外光谱特征信息提取方法PCA和MIE方法性能进行对比分析,结果表明基于PCA-MIE的过程模式故障检测方法几乎在所有维 展开更多
关键词 近红外光谱 互信息熵 过程模式 故障检测 贝叶斯
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Time-course data prediction for repeatedly measured gene expression
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作者 Atanu Bhattacharjee Gajendra K.Vishwakarma 《生物数学学报:英文版》 2019年第4期39-54,共16页
Variability in time course gene expression data is a natural phenomenon. The intention of this work is to predict the future time point data through observed sample data point. The Bayesian inference is carried to ser... Variability in time course gene expression data is a natural phenomenon. The intention of this work is to predict the future time point data through observed sample data point. The Bayesian inference is carried to serve the objective. A total of 6 replicates 3 time point's data of 218 genes expression is adopted to illustrate the method. The estimates are found consistent with HPD interval to predict the future time point gene expression value. This proposed method can be adopted in other gene expression data setup to predict the future time course data. 展开更多
关键词 CROSSOVER trial BAYESIAN algorithm multiple IMPUTATION three ARMS threeperiods
Technology Importation and Domestic Technology Acquisition in China from the Perspective of Innovation 预览
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作者 俞立平 袁胜军 +1 位作者 彭长生 钟昌标 《中国经济学人:英文版》 2019年第3期66-81,共16页
Foreign and domestic technologies play different roles in a country’s innovation. In recent years, Chinese firms have spent less on importing foreign technology and more on acquiring domestic technology. Based on the... Foreign and domestic technologies play different roles in a country’s innovation. In recent years, Chinese firms have spent less on importing foreign technology and more on acquiring domestic technology. Based on the panel data model, state space model (SSM) and the Bayesian vector autoregressive model, this paper finds that the purchase of domestic technology plays a critical role in the innovation of high-tech firms with an elasticity coefficient higher than that of technology importation before 2010. China’s high-tech firms can effectively absorb purchased domestic technology, which also brings about an increase in their independent R&D input and contributes more to innovation output than imported technology. Performance of technology importation is lackluster but shows an improving trend. Technology importation is not correlated with innovation output and has a substitutive effect with independent R&D input. China is yet to enhance its absorption of imported technology. Elasticity coefficient of technology importation turned positive in 2007 and increased year by year. China should promote synergy between technology importation and domestic technology acquisition. 展开更多
关键词 TECHNOLOGY IMPORTATION ACQUISITION of domestic TECHNOLOGY innovationdriven development state space MODEL (SSM) Bayesian vector AUTOREGRESSIVE MODEL
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GPA:A Microbial Genetic Polymorphisms Assignments Tool in Metagenomic Analysis by Bayesian Estimation
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作者 Jiarui Li Pengcheng Du +4 位作者 Adam Yongxin Ye Yuanyuan Zhang Chuan Song Hui Zeng Chen Chen 《基因组蛋白质组与生物信息学报:英文版》 CAS CSCD 2019年第1期106-117,共12页
Identifying antimicrobial resistant(AMR)bacteria in metagenomics samples is essential for public health and food safety.Next-generation sequencing(NGS)technology has provided a powerful tool in identifying the genetic... Identifying antimicrobial resistant(AMR)bacteria in metagenomics samples is essential for public health and food safety.Next-generation sequencing(NGS)technology has provided a powerful tool in identifying the genetic variation and constructing the correlations between genotype and phenotype in humans and other species.However,for complex bacterial samples,there lacks a powerful bioinformatic tool to identify genetic polymorphisms or copy number variations(CNVs)for given genes.Here we provide a Bayesian framework for genotype estimation for mixtures of multiple bacteria,named as Genetic Polymorphisms Assignments(GPA).Simulation results showed that GPA has reduced the false discovery rate(FDR)and mean absolute error(MAE)in CNV and single nucleotide variant(SNV)identification.This framework was validated by whole-genome sequencing and Pool-seq data from Klebsiella pneumoniae with multiple bacteria mixture models,and showed the high accuracy in the allele fraction detections of CNVs and SNVs in AMR genes between two populations.The quantitative study on the changes of AMR genes fraction between two samples showed a good consistency with the AMR pattern observed in the individual strains.Also,the framework together with the genome annotation and population comparison tools has been integrated into an application,which could provide a complete solution for AMR gene identification and quantification in unculturable clinical samples.The GPA package is available at https://github.com/IID-DTH/GPA-package. 展开更多
关键词 Next-generation sequencing Pool-seq Bayesian model METAGENOMICS Genetic polymorphisms
云计算环境下图书馆位置感知服务研究 预览
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作者 王能辉 《计算机与数字工程》 2019年第4期778-784,共7页
针对采用基于WLAN的位置指纹算法的图书馆位置感知服务器在处理大规模定位数据时计算时间太长,结合云计算技术的快速发展,提出一种基于MapReduce架构的并行朴素贝叶斯概率计算方法。此方法通过MapReduce框架对指纹数据库可快速计算出定... 针对采用基于WLAN的位置指纹算法的图书馆位置感知服务器在处理大规模定位数据时计算时间太长,结合云计算技术的快速发展,提出一种基于MapReduce架构的并行朴素贝叶斯概率计算方法。此方法通过MapReduce框架对指纹数据库可快速计算出定位目标在每个记录的后验概率值,以后验概率为权重来确定位置坐标,使定位在准确性和时间响应性方面获得更好的性能,以提升图书馆位置感知服务质量。文章将并行朴素贝叶斯概率算法进行图书馆室内定位实验,并将其与串行朴素贝叶斯概率算法对比测试。实验结果表明,改进后的定位算法有效减短了定位过程的计算时间,而且还能保证定位精度,完全满足定位服务需求。 展开更多
关键词 云计算 MAPREDUCE 贝叶斯 图书馆 位置感知服务
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基于贝叶斯框架的显著物体检测 预览
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作者 黄炜亮 段先华 《计算机与数字工程》 2019年第8期2044-2049,共6页
传统显著性方法仅能检测出目标物体的边缘或角点等方面信息,无法完整分割出显著物体整体。为解决以上问题,论文考虑以超像素为基本处理单元,而不是仅仅计算单个像素点信息,通过综合考虑相邻超像素之间的紧致性及颜色关系等因素,优化得... 传统显著性方法仅能检测出目标物体的边缘或角点等方面信息,无法完整分割出显著物体整体。为解决以上问题,论文考虑以超像素为基本处理单元,而不是仅仅计算单个像素点信息,通过综合考虑相邻超像素之间的紧致性及颜色关系等因素,优化得到超像素级显著图。其次,通过似物性计算目标物体粗糙检测区域作为位置信息。最后通过贝叶斯框架融合各部分先验信息,计算得到最终的显著物体后验概率,并以此为优化后的似物性方法评分标准,最终检测出显著物体。在标准公开数据集MSRA上的实验结果表明论文超像素级显著图精度明显高于其他8种传统显著性算法,最终在显著图上的搜索能够完整检测出显著物体。 展开更多
关键词 显著性 贝叶斯 自信息 超像素
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Application of Bayesian model and discriminant function analysis to the estimation of sediment source contributions 预览
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作者 Pengfei Du Donghao Huang +4 位作者 Duihu Ning Yuehong Chen Bing Liu Jian Wang Jingjing Xu 《国际泥沙研究:英文版》 SCIE 2019年第6期577-590,共14页
Bayesian and discriminant function analysis(DFA)models have recently been used as tools to estimate sediment source contributions.Unlike existing multivariate mixing models,the accuracy of these two models remains unc... Bayesian and discriminant function analysis(DFA)models have recently been used as tools to estimate sediment source contributions.Unlike existing multivariate mixing models,the accuracy of these two models remains unclear.In the current study,four well-distinguished source samples were used to create artificial mixtures to test the performance of Bayesian and DFA models.These models were tested against the Walling-Collins model,a credible model used in estimation of sediment source contributions estimation,as a reference.The artificial mixtures were divided into five groups,with each group consisting of five samples with known source percentages.The relative contributions of the sediment sources to the individual and grouped samples were calculated using each of the models.The mean absolute error(MAE)and standard error of(SE)MAE were used to test the accuracy of each model and the robustness of the optimized solutions.For the individual sediment samples,the calculated source contributions obtained with the Bayesian(MAE?7.4%,SE?0.6%)and Walling-Collins(MAE?7.5%,SE?0.7%)models produced results which were closest to the actual percentages of the source contributions to the sediment mixtures.The DFA model produced the worst estimates(MAE?18.4%,SE?1.4%).For the grouped sediment samples,the Walling-Collins model(MAE?5.4%)was the best predictor,closely followed by the Bayesian model(MAE?5.9%).The results obtained with the DFA model were similar to the values for the individual sediment samples,with the accuracy of the source contribution value being the poorest obtained with any of the models(MAE?18.5%).An increase in sample size improved the accuracies of the Walling-Collins and Bayesian models,but the DFA model produced similarly inaccurate results for both the individual and grouped sediment samples.Generally,the accuracy of the Walling-Collins and Bayesian models was similar(p>0.01),while there were significant differences(p<0.01)between the DFA model and the other models.This study demonstrated that the Bayesian mo 展开更多
关键词 SEDIMENT fingerprinting SEDIMENT source contribution Walling-Collins MODEL BAYESIAN MODEL DISCRIMINANT function analysis
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一种基于蓝牙室内指纹定位的贝叶斯改进算法
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作者 郭英 冯茗杨 +2 位作者 孙玉曦 姬现磊 刘清华 《测绘通报》 CSCD 北大核心 2019年第5期1-6,共6页
贝叶斯估计是重要的位置指纹定位算法,但传统的等值贝叶斯先验概率在动态定位中不适用。针对该问题,本文提出了一种基于贝叶斯指纹定位的改进算法。首先,借助陀螺仪获取的航向信息和高斯核函数模型建立概率投票算法,计算先验概率;然后,... 贝叶斯估计是重要的位置指纹定位算法,但传统的等值贝叶斯先验概率在动态定位中不适用。针对该问题,本文提出了一种基于贝叶斯指纹定位的改进算法。首先,借助陀螺仪获取的航向信息和高斯核函数模型建立概率投票算法,计算先验概率;然后,结合先验概率和信号强度计算待测点位于参考点上的后验概率;最后,选取概率最高的参考点,以概率为权重计算待测点的最或然值。以智能手机为试验对象,在规则路径试验中,改进算法的平均定位误差为1.15 m,定位误差小于2 m的概率为96.1%,不规则路径试验中,平均定位误差为0.50 m,定位误差在1 m的可信度为94.8%;并且改进算法对定位中位置跳变的现象有明显改善,具有较好的稳健性。 展开更多
关键词 室内定位 低功耗蓝牙 贝叶斯 陀螺仪航向 高斯核函数 概率投票算法
Artificial intelligence on diabetic retinopathy diagnosis: an automatic classification method based on grey level co-occurrence matrix and naive Bayesian model
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作者 Kai Cao Jie Xu Wei-Qi Zhao 《国际眼科杂志:英文版》 SCIE CAS 2019年第7期1158-1162,共5页
AIM: To develop an automatic tool on screening diabetic retinopathy(DR) from diabetic patients.METHODS: We extracted textures from eye fundus images of each diabetes subject using grey level co-occurrence matrix metho... AIM: To develop an automatic tool on screening diabetic retinopathy(DR) from diabetic patients.METHODS: We extracted textures from eye fundus images of each diabetes subject using grey level co-occurrence matrix method and trained a Bayesian model based on these textures. The receiver operating characteristic(ROC) curve was used to estimate the sensitivity and specificity of the Bayesian model.RESULTS: A total of 1000 eyes fundus images from diabetic patients in which 298 eyes were diagnosed as DR by two ophthalmologists. The Bayesian model was trained using four extracted textures including contrast, entropy, angular second moment and correlation using a training dataset. The Bayesian model achieved a sensitivity of 0.949 and a specificity of 0.928 in the validation dataset. The area under the ROC curve was 0.938, and the 10-fold cross validation method showed that the average accuracy rate is 93.5%.CONCLUSION: Textures extracted by grey level cooccurrence can be useful information for DR diagnosis, and a trained Bayesian model based on these textures can be an effective tool for DR screening among diabetic patients. 展开更多
关键词 GREY level CO-OCCURRENCE matrix BAYESIAN textures artificial INTELLIGENCE receiver operating characteristiccurve diabetic RETINOPATHY
Nonlinear joint PP-PS AVO inversion based on improved Bayesian inference and LSSVM 预览
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作者 Xie Wei Wang Yan-Chun +4 位作者 Liu Xue-Qing Bi Chen-Chen Zhang Feng-Qi Fang Yuan Tahir Azeem 《应用地球物理:英文版》 SCIE CSCD 2019年第1期64-76,共13页
Multiwave seismic technology promotes the application of joint PP–PS amplitude versus offset (AVO) inversion;however conventional joint PP–PS AVO inversioan is linear based on approximations of the Zoeppritz equatio... Multiwave seismic technology promotes the application of joint PP–PS amplitude versus offset (AVO) inversion;however conventional joint PP–PS AVO inversioan is linear based on approximations of the Zoeppritz equations for multiple iterations. Therefore the inversion results of P-wave, S-wave velocity and density exhibit low precision in the faroffset;thus, the joint PP–PS AVO inversion is nonlinear. Herein, we propose a nonlinear joint inversion method based on exact Zoeppritz equations that combines improved Bayesian inference and a least squares support vector machine (LSSVM) to solve the nonlinear inversion problem. The initial parameters of Bayesian inference are optimized via particle swarm optimization (PSO). In improved Bayesian inference, the optimal parameter of the LSSVM is obtained by maximizing the posterior probability of the hyperparameters, thus improving the learning and generalization abilities of LSSVM. Then, an optimal nonlinear LSSVM model that defi nes the relationship between seismic refl ection amplitude and elastic parameters is established to improve the precision of the joint PP–PS AVO inversion. Further, the nonlinear problem of joint inversion can be solved through a single training of the nonlinear inversion model. The results of the synthetic data suggest that the precision of the estimated parameters is higher than that obtained via Bayesian linear inversion with PP-wave data and via approximations of the Zoeppritz equations. In addition, results using synthetic data with added noise show that the proposed method has superior anti-noising properties. Real-world application shows the feasibility and superiority of the proposed method, as compared with Bayesian linear inversion. 展开更多
关键词 NONLINEAR problem JOINT PP-PS AVO inversion particle swarm optimization Bayesian INFERENCE least SQUARES support vector machine
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Comparison of deterministic and stochastic approaches to crosshole seismic travel-time inversions 预览
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作者 YanZhe Zhao YanBin Wang 《地球与行星物理:英文版》 CSCD 2019年第6期547-559,共13页
The Bayesian inversion method is a stochastic approach based on the Bayesian theory.With the development of sampling algorithms and computer technologies,the Bayesian inversion method has been widely used in geophysic... The Bayesian inversion method is a stochastic approach based on the Bayesian theory.With the development of sampling algorithms and computer technologies,the Bayesian inversion method has been widely used in geophysical inversion problems.In this study,we conduct inversion experiments using crosshole seismic travel-time data to examine the characteristics and performance of the stochastic Bayesian inversion based on the Markov chain Monte Carlo sampling scheme and the traditional deterministic inversion with Tikhonov regularization.Velocity structures with two different spatial variations are considered,one with a chessboard pattern and the other with an interface mimicking the Mohorovičićdiscontinuity(Moho).Inversions are carried out with different scenarios of model discretization and source–receiver configurations.Results show that the Bayesian method yields more robust single-model estimations than the deterministic method,with smaller model errors.In addition,the Bayesian method provides the posterior probabilistic distribution function of the model space,which can help us evaluate the quality of the inversion result. 展开更多
关键词 stochastic approach deterministic approach Bayesian inversion Markov Chain Monte Carlo Tikhonov regularization
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