An improvement method for the combining rule of Dempster evidence theory is proposed. Different from Dempster theory, the reliability of evidences isn't identical; and varies with the event. By weight evidence acc...An improvement method for the combining rule of Dempster evidence theory is proposed. Different from Dempster theory, the reliability of evidences isn't identical; and varies with the event. By weight evidence according to their reliability, the effect of unreliable evidence is reduced, and then get the fusion result that is closer to the truth. An example to expand the advantage of this method is given. The example proves that this method is helpful to find a correct result.展开更多
To study the scene classification in the Synthetic Aperture Radar （SAR） image, a novel method based on kernel estimate, with the Maxkov context and Dempster-Shafer evidence theory is proposed. Initially, a nonpaxame...To study the scene classification in the Synthetic Aperture Radar （SAR） image, a novel method based on kernel estimate, with the Maxkov context and Dempster-Shafer evidence theory is proposed. Initially, a nonpaxametric Probability Density Function （PDF） estimate method is introduced, to describe the scene of SAR images. And then under the Maxkov context, both the determinate PDF and the kernel estimate method axe adopted respectively, to form a primary classification. Next, the primary classification results are fused using the evidence theory in an unsupervised way to get the scene classification. Finally, a regularization step is used, in which an iterated maximum selecting approach is introduced to control the fragments and modify the errors of the classification. Use of the kernel estimate and evidence theory can describe the complicated scenes with little prior knowledge and eliminate the ambiguities of the primary classification results. Experimental results on real SAR images illustrate a rather impressive performance.展开更多
Transmembrane proteins are some special and important proteins in cells. Because of their importance and specificity, the prediction of the transmembrane regions has very important theoretical and practical significan...Transmembrane proteins are some special and important proteins in cells. Because of their importance and specificity, the prediction of the transmembrane regions has very important theoretical and practical significance. At present, the prediction methods are mainly based on the physicochemical property and statistic analysis of amino acids. However, these methods are suitable for some environments but inapplicable for other environments. In this paper, the multi-sources information fusion theory has been introduced to predict the transmembrane regions. The proposed method is test on a data set of transmembrane proteins. The results show that the proposed method has the ability of predicting the transmembrane regions as a good performance and powerful tool.展开更多
In this paper, it is proposed to apply the Dempster-Shafer Theory (DST) or the theory of evidence to map vegetation, aquatic and mineral surfaces with a view to detecting potential areas of observation of outcrops of ...In this paper, it is proposed to apply the Dempster-Shafer Theory (DST) or the theory of evidence to map vegetation, aquatic and mineral surfaces with a view to detecting potential areas of observation of outcrops of geological formations (rocks, breastplates, regolith, etc.). The proposed approach consists in aggregating information by using the DST. From pretreated Aster satellite images (geo-referencing, geometric correction and resampling at 15 m), new channels were produced by determining the spectral indices NDVI, MNDWI and NDBaI. Then, the DST formalism was modeled and generated under the MATLAB software, an image segmented into six classes including three absolute classes (E,V,M) and three classes of confusion ({E,V}, {M,V}, {E,M}). The control on the land, based on geographic coordinates of pixels of different classes on said image, has made it possible to make a concordant interpretation thereof. Our contribution lies in taking into account imperfections (inaccuracies and uncertainties) related to source information by using mass functions based on a simple support model (two focal elements: the discernment framework and the potential set of belonging of the pixel to be classified) with a normal law for the good management of these.展开更多
针对视频情感识别中存在运算复杂度高的缺点,提出一种基于时空局部二值模式矩(Temporal-Spatial Local Binary Pattern Moment,TSLBPM)的双模态情感识别方法。首先对视频进行预处理获得表情和姿态序列;然后对表情和姿态序列分别提取TSL...针对视频情感识别中存在运算复杂度高的缺点,提出一种基于时空局部二值模式矩(Temporal-Spatial Local Binary Pattern Moment,TSLBPM)的双模态情感识别方法。首先对视频进行预处理获得表情和姿态序列;然后对表情和姿态序列分别提取TSLBPM特征,计算测试序列与已标记的情感训练集特征间的最小欧氏距离,并将其作为独立证据来构造基本概率分配(Basic Probability Assignment,BPA);最后使用Dempster-Shafer证据理论联合规则得到情感识别结果。在双模态表情和姿态情感数据库上的实验结果表明,本文提出的时空局部二值模式矩可以快速提取视频图像的时空特征,能有效识别情感状态。与其他方法的对比实验也验证了本文融合方法的优越性。展开更多
In this paper,we propose temporal Dempster-Shafer theory to handle the combination of uncertainty andtime. In temporal Dempster-Shafer theory,the element of the temporal frame of discernment is defined as an eventthat...In this paper,we propose temporal Dempster-Shafer theory to handle the combination of uncertainty andtime. In temporal Dempster-Shafer theory,the element of the temporal frame of discernment is defined as an eventthat associates a hypothesis with corresponding time interval. And the assignment of belief to subset of the temporalframe of discernment is performed by the mass function. It is a representation and reasoning mechanism that combinesuncertainty and time by the basic frame of Dempster-Shafer theory.展开更多
[目的]揭示驱动盘龙江流域不透水表面扩张的影响因子,以及影响因子各属性值对不透水表面扩张的影响程度,并在分析驱动机制的基础上,模拟预测盘龙江流域的扩张趋势,为流域生态建设合理规划提供依据。[方法]采用Dempster—Shafer(D—S)证...[目的]揭示驱动盘龙江流域不透水表面扩张的影响因子,以及影响因子各属性值对不透水表面扩张的影响程度,并在分析驱动机制的基础上,模拟预测盘龙江流域的扩张趋势,为流域生态建设合理规划提供依据。[方法]采用Dempster—Shafer(D—S)证据理论来描述和融合多种空间数据,在已有的不透水表面(impervious surfaces,IS)信息与多种空间数据的量关系的基础上,采用数据驱动方法分配基本概率函数(basic probability assignment,BPA)。经过定义多种空间数据的BPA函数,然后采用D—S证据理论的融合规则融合多个BPA函数以获取研究区域IS的信任函数、不信任函数、不确定函数、似真函数。[结果]距道路距离,距居民点距离,距水系距离,人口密度,GDP,IS邻域单元数,坡度,高程驱动因子对盘龙江流域不透水表面的扩张影响比较大,而坡向对不透水表面扩张的影响程度变化不明显。不透水表面扩张模拟的精度达到78.04%。[结论]采用D—S证据理论方法来描述空间数据和融合多种空间数据具有比传统逻辑回归模型更好的分析和预测功能。展开更多
文摘An improvement method for the combining rule of Dempster evidence theory is proposed. Different from Dempster theory, the reliability of evidences isn't identical; and varies with the event. By weight evidence according to their reliability, the effect of unreliable evidence is reduced, and then get the fusion result that is closer to the truth. An example to expand the advantage of this method is given. The example proves that this method is helpful to find a correct result.
基金the National Nature Science Foundation of China (60372057).
文摘To study the scene classification in the Synthetic Aperture Radar （SAR） image, a novel method based on kernel estimate, with the Maxkov context and Dempster-Shafer evidence theory is proposed. Initially, a nonpaxametric Probability Density Function （PDF） estimate method is introduced, to describe the scene of SAR images. And then under the Maxkov context, both the determinate PDF and the kernel estimate method axe adopted respectively, to form a primary classification. Next, the primary classification results are fused using the evidence theory in an unsupervised way to get the scene classification. Finally, a regularization step is used, in which an iterated maximum selecting approach is introduced to control the fragments and modify the errors of the classification. Use of the kernel estimate and evidence theory can describe the complicated scenes with little prior knowledge and eliminate the ambiguities of the primary classification results. Experimental results on real SAR images illustrate a rather impressive performance.
基金Supported by the National Natural Science Foundation of China (No. 60874105, 61174022)the Program for New Century Excellent Talents in University (No. NCET-08-0345)the Chongqing Natural Science Foundation (No. CSCT, 2010BA2003)
文摘Transmembrane proteins are some special and important proteins in cells. Because of their importance and specificity, the prediction of the transmembrane regions has very important theoretical and practical significance. At present, the prediction methods are mainly based on the physicochemical property and statistic analysis of amino acids. However, these methods are suitable for some environments but inapplicable for other environments. In this paper, the multi-sources information fusion theory has been introduced to predict the transmembrane regions. The proposed method is test on a data set of transmembrane proteins. The results show that the proposed method has the ability of predicting the transmembrane regions as a good performance and powerful tool.
文摘In this paper, it is proposed to apply the Dempster-Shafer Theory (DST) or the theory of evidence to map vegetation, aquatic and mineral surfaces with a view to detecting potential areas of observation of outcrops of geological formations (rocks, breastplates, regolith, etc.). The proposed approach consists in aggregating information by using the DST. From pretreated Aster satellite images (geo-referencing, geometric correction and resampling at 15 m), new channels were produced by determining the spectral indices NDVI, MNDWI and NDBaI. Then, the DST formalism was modeled and generated under the MATLAB software, an image segmented into six classes including three absolute classes (E,V,M) and three classes of confusion ({E,V}, {M,V}, {E,M}). The control on the land, based on geographic coordinates of pixels of different classes on said image, has made it possible to make a concordant interpretation thereof. Our contribution lies in taking into account imperfections (inaccuracies and uncertainties) related to source information by using mass functions based on a simple support model (two focal elements: the discernment framework and the potential set of belonging of the pixel to be classified) with a normal law for the good management of these.
文摘针对视频情感识别中存在运算复杂度高的缺点,提出一种基于时空局部二值模式矩(Temporal-Spatial Local Binary Pattern Moment,TSLBPM)的双模态情感识别方法。首先对视频进行预处理获得表情和姿态序列;然后对表情和姿态序列分别提取TSLBPM特征,计算测试序列与已标记的情感训练集特征间的最小欧氏距离,并将其作为独立证据来构造基本概率分配(Basic Probability Assignment,BPA);最后使用Dempster-Shafer证据理论联合规则得到情感识别结果。在双模态表情和姿态情感数据库上的实验结果表明,本文提出的时空局部二值模式矩可以快速提取视频图像的时空特征,能有效识别情感状态。与其他方法的对比实验也验证了本文融合方法的优越性。
文摘In this paper,we propose temporal Dempster-Shafer theory to handle the combination of uncertainty andtime. In temporal Dempster-Shafer theory,the element of the temporal frame of discernment is defined as an eventthat associates a hypothesis with corresponding time interval. And the assignment of belief to subset of the temporalframe of discernment is performed by the mass function. It is a representation and reasoning mechanism that combinesuncertainty and time by the basic frame of Dempster-Shafer theory.
文摘[目的]揭示驱动盘龙江流域不透水表面扩张的影响因子,以及影响因子各属性值对不透水表面扩张的影响程度,并在分析驱动机制的基础上,模拟预测盘龙江流域的扩张趋势,为流域生态建设合理规划提供依据。[方法]采用Dempster—Shafer(D—S)证据理论来描述和融合多种空间数据,在已有的不透水表面(impervious surfaces,IS)信息与多种空间数据的量关系的基础上,采用数据驱动方法分配基本概率函数(basic probability assignment,BPA)。经过定义多种空间数据的BPA函数,然后采用D—S证据理论的融合规则融合多个BPA函数以获取研究区域IS的信任函数、不信任函数、不确定函数、似真函数。[结果]距道路距离,距居民点距离,距水系距离,人口密度,GDP,IS邻域单元数,坡度,高程驱动因子对盘龙江流域不透水表面的扩张影响比较大,而坡向对不透水表面扩张的影响程度变化不明显。不透水表面扩张模拟的精度达到78.04%。[结论]采用D—S证据理论方法来描述空间数据和融合多种空间数据具有比传统逻辑回归模型更好的分析和预测功能。
