Markov random fields(MRF) have potential for predicting and simulating petroleum reservoir facies more accurately from sample data such as logging, core data and seismic data because they can incorporate interclass re...Markov random fields(MRF) have potential for predicting and simulating petroleum reservoir facies more accurately from sample data such as logging, core data and seismic data because they can incorporate interclass relationships. While, many relative studies were based on Markov chain, not MRF, and using Markov chain model for 3D reservoir stochastic simulation has always been the difficulty in reservoir stochastic simulation. MRF was proposed to simulate type variables(for example lithofacies) in this work. Firstly, a Gibbs distribution was proposed to characterize reservoir heterogeneity for building 3-D(three-dimensional) MRF. Secondly, maximum likelihood approaches of model parameters on well data and training image were considered. Compared with the simulation results of MC(Markov chain), the MRF can better reflect the spatial distribution characteristics of sand body.展开更多
Traditional image segmentation methods based on MRF converge slowly and require pre-defined weight. These disadvantages are addressed, and a fast segmentation approach based on simple Markov random field （MRF） for S...Traditional image segmentation methods based on MRF converge slowly and require pre-defined weight. These disadvantages are addressed, and a fast segmentation approach based on simple Markov random field （MRF） for SAR image is proposed. The approach is firstly used to perform coarse segmentation in blocks. Then the image is modeled with simple MRF and adaptive variable weighting forms are applied in homogeneous and heterogeneous regions. As a result, the convergent speed is accelerated while the segmentation results in homogeneous regions and boarders are improved. Simulations with synthetic and real SAR images demonstrate the effectiveness of the proposed approach.展开更多
对湖北田歌的分布与田歌孕育的地理环境之间的关系进行了探究,以期为区域音乐的实证研究提供新的思路和方法.以湖北田歌为研究对象,选取1 248个田歌样本数据集,运用地理信息系统(geographic information system,GIS)对初步选定的田歌分...对湖北田歌的分布与田歌孕育的地理环境之间的关系进行了探究,以期为区域音乐的实证研究提供新的思路和方法.以湖北田歌为研究对象,选取1 248个田歌样本数据集,运用地理信息系统(geographic information system,GIS)对初步选定的田歌分布及音乐要素影响因子进行建库,基于随机森林及可解释性算法(shapley additive explanations,SHAP)构建田歌影响因子体系分析模型,通过受试者工作特性曲线(receiver operating characteristic curve,ROC)对模型的有效性进行评价,分析田歌的分布、音乐要素与地理环境之间的关系.研究结果表明:1)基于随机森林构建的田歌影响因子体系模型预测效果较好,其曲线下面积(area under the curve,AUC)的值为0.82;2)对田歌产生及音乐要素影响因子重要性排序得出,多年平均降雨量和多年平均气温是孕育湖北田歌的主要因子.其随机森林及SHAP算法,能在一定程度上预测湖北田歌分布格局,对区域音乐文化与地理关联性研究具有重要意义.展开更多
针对实际档案库房操作空间的动态约束性,常见的运动规划算法难以满足快速在线规划的问题,分别从规划速度和动态空间在线规划两个方向进行研究.首先,提出一种新型快速搜索随机树法(rapidly-exploring random trees,RRT),基于剪枝和路径...针对实际档案库房操作空间的动态约束性,常见的运动规划算法难以满足快速在线规划的问题,分别从规划速度和动态空间在线规划两个方向进行研究.首先,提出一种新型快速搜索随机树法(rapidly-exploring random trees,RRT),基于剪枝和路径细化策略能够大幅减少无用节点计算和冗余路径运动.其次,将人工势场法与RRT算法相结合,新节点拓展时会受到期望为当前势场合力的高斯分布的影响,在满足对动态障碍物的在线运动规划的同时提高了算法的拓展能力.最后,通过仿真结果证明,新型RRT算法在拓展效率上的高效性和混合运动规划算法在动态规划和探索效率上的优越性.展开更多
为解决文本类地铁应急处置流程存在的流程顺序关系不明确、流程执行人员模糊等问题,提出了基于BiLSTM-CRF(Bidirectional Long Short-Term Memory-Conditional Random Field)的地铁应急处置知识抽取与推理方法。首先,利用BiLSTM-CRF方...为解决文本类地铁应急处置流程存在的流程顺序关系不明确、流程执行人员模糊等问题,提出了基于BiLSTM-CRF(Bidirectional Long Short-Term Memory-Conditional Random Field)的地铁应急处置知识抽取与推理方法。首先,利用BiLSTM-CRF方法对地铁应急处置流程的文本资料进行命名实体识别,完成文本资料的知识抽取;其次,选用TransD模型对识别后实体数据进行知识推理,从而完成以实体和属性对为节点、关系对为边的知识图谱构建;最后,利用Neo4j图数据库对构建的地铁应急处置流程知识图谱进行了可视化展示和案例分析。研究结果表明,基于BiLSTM-CRF的知识抽取模型的精确率、召回率和F1值均达到了90%以上,且基于BiLSTM-CRF的TransD模型的推理结果准确率提升了22.92%,保证了知识图谱构建的准确性,可为地铁应急管理提供决策支持。展开更多
基金Project(2011ZX05002-005-006)supported by the National "Twelveth Five Year" Science and Technology Major Research Program,China
文摘Markov random fields(MRF) have potential for predicting and simulating petroleum reservoir facies more accurately from sample data such as logging, core data and seismic data because they can incorporate interclass relationships. While, many relative studies were based on Markov chain, not MRF, and using Markov chain model for 3D reservoir stochastic simulation has always been the difficulty in reservoir stochastic simulation. MRF was proposed to simulate type variables(for example lithofacies) in this work. Firstly, a Gibbs distribution was proposed to characterize reservoir heterogeneity for building 3-D(three-dimensional) MRF. Secondly, maximum likelihood approaches of model parameters on well data and training image were considered. Compared with the simulation results of MC(Markov chain), the MRF can better reflect the spatial distribution characteristics of sand body.
基金supported by the Specialized Research Found for the Doctoral Program of Higher Education (20070699013)the Natural Science Foundation of Shaanxi Province (2006F05)the Aeronautical Science Foundation (05I53076)
文摘Traditional image segmentation methods based on MRF converge slowly and require pre-defined weight. These disadvantages are addressed, and a fast segmentation approach based on simple Markov random field （MRF） for SAR image is proposed. The approach is firstly used to perform coarse segmentation in blocks. Then the image is modeled with simple MRF and adaptive variable weighting forms are applied in homogeneous and heterogeneous regions. As a result, the convergent speed is accelerated while the segmentation results in homogeneous regions and boarders are improved. Simulations with synthetic and real SAR images demonstrate the effectiveness of the proposed approach.
文摘对湖北田歌的分布与田歌孕育的地理环境之间的关系进行了探究,以期为区域音乐的实证研究提供新的思路和方法.以湖北田歌为研究对象,选取1 248个田歌样本数据集,运用地理信息系统(geographic information system,GIS)对初步选定的田歌分布及音乐要素影响因子进行建库,基于随机森林及可解释性算法(shapley additive explanations,SHAP)构建田歌影响因子体系分析模型,通过受试者工作特性曲线(receiver operating characteristic curve,ROC)对模型的有效性进行评价,分析田歌的分布、音乐要素与地理环境之间的关系.研究结果表明:1)基于随机森林构建的田歌影响因子体系模型预测效果较好,其曲线下面积(area under the curve,AUC)的值为0.82;2)对田歌产生及音乐要素影响因子重要性排序得出,多年平均降雨量和多年平均气温是孕育湖北田歌的主要因子.其随机森林及SHAP算法,能在一定程度上预测湖北田歌分布格局,对区域音乐文化与地理关联性研究具有重要意义.
文摘针对实际档案库房操作空间的动态约束性,常见的运动规划算法难以满足快速在线规划的问题,分别从规划速度和动态空间在线规划两个方向进行研究.首先,提出一种新型快速搜索随机树法(rapidly-exploring random trees,RRT),基于剪枝和路径细化策略能够大幅减少无用节点计算和冗余路径运动.其次,将人工势场法与RRT算法相结合,新节点拓展时会受到期望为当前势场合力的高斯分布的影响,在满足对动态障碍物的在线运动规划的同时提高了算法的拓展能力.最后,通过仿真结果证明,新型RRT算法在拓展效率上的高效性和混合运动规划算法在动态规划和探索效率上的优越性.
文摘该研究致力于构建一个高质量的数据集,用于南美白对虾养殖领域的命名实体识别(named entity recognition,NER)任务,命名为VamNER。为确保数据集的多样性,从CNKI数据库中收集了近10年的高质量论文,并结合权威书籍进行语料构建。邀请专家讨论实体类型,并经过专业培训的标注人员使用IOB2标注格式进行标注,标注过程分为预标注和正式标注两个阶段以提高效率。在预标注阶段,标注者间一致性(inter-annotation agreement,IAA)达到0.87,表明标注人员的一致性较高。最终,VamNER包含6115个句子,总字符数达384602,涵盖10个实体类型,共有12814个实体。研究通过与多个通用领域数据集和一个特定领域数据集进行比较,揭示了VamNER的独特特性。在实验中使用了预训练的基于变换器的双向编码器表示(bidirectional encoder representations from Transformers,BERT)模型、双向长短期记忆神经网络(bidirectional long short-term memory network,BiLSTM)和条件随机场模型(conditional random fields,CRF),最优模型在测试集上的F1值达到82.8%。VamNER成为首个专注于南美白对虾养殖领域的NER数据集,为中文特定领域NER研究提供了丰富资源,有望推动水产养殖领域NER研究的发展。
文摘为解决文本类地铁应急处置流程存在的流程顺序关系不明确、流程执行人员模糊等问题,提出了基于BiLSTM-CRF(Bidirectional Long Short-Term Memory-Conditional Random Field)的地铁应急处置知识抽取与推理方法。首先,利用BiLSTM-CRF方法对地铁应急处置流程的文本资料进行命名实体识别,完成文本资料的知识抽取;其次,选用TransD模型对识别后实体数据进行知识推理,从而完成以实体和属性对为节点、关系对为边的知识图谱构建;最后,利用Neo4j图数据库对构建的地铁应急处置流程知识图谱进行了可视化展示和案例分析。研究结果表明,基于BiLSTM-CRF的知识抽取模型的精确率、召回率和F1值均达到了90%以上,且基于BiLSTM-CRF的TransD模型的推理结果准确率提升了22.92%,保证了知识图谱构建的准确性,可为地铁应急管理提供决策支持。
