{"currentpage":1,"firstResult":0,"maxresult":10,"pagecode":5,"pageindex":{"endPagecode":5,"startPagecode":1},"records":[{"abstractinfo":"本文根据多孔介质渗流换热理论建立了高温水泥熟料的物理换热模型和数学换热模型,并针对高温水泥熟料数学换热模型的特点,提出采用<span style=\"color:red\">剖开</span><span style=\"color:red\">算子</span><span style=\"color:red\">法</span>对其进行求解.并通过仿真实验验证了该换热模型的正确性,给出了换热过程中熟料和气体的温度变化规律,仿真实验结果显示该数学换热模型能比较准确的反映实际情况,在此基础上分析了篦下风速对熟料冷却效果的影响,为篦冷机优化配风设计提供了理论指导.","authors":[{"authorName":"郝晓辰","id":"da2056c3-5b0a-4a1c-a641-985b50b4815e","originalAuthorName":"郝晓辰"},{"authorName":"范新丰","id":"89f57eed-604b-4566-830f-66ccf39fa756","originalAuthorName":"范新丰"},{"authorName":"刘彬","id":"83dbd165-5cd8-4111-97bd-2e79dd170fe3","originalAuthorName":"刘彬"}],"doi":"","fpage":"6","id":"c77464dd-8e37-49d6-8859-cd83d9a36d8f","issue":"1","journal":{"abbrevTitle":"GSYTB","coverImgSrc":"journal/img/cover/GSYTB.jpg","id":"36","issnPpub":"1001-1625","publisherId":"GSYTB","title":"硅酸盐通报   "},"keywords":[{"id":"7c5baf69-602a-49e9-867c-a0c9c5027391","keyword":"篦冷机","originalKeyword":"篦冷机"},{"id":"61898bbb-cef6-449e-94eb-bb7a8389172c","keyword":"多孔介质","originalKeyword":"多孔介质"},{"id":"79d30824-180f-4ee7-bc05-a5a21c380eec","keyword":"换热模型","originalKeyword":"换热模型"},{"id":"7c05a99e-feb6-4714-93a5-a9ef96307e69","keyword":"数值解法","originalKeyword":"数值解法"},{"id":"8b920d42-f76d-473f-815a-978552289226","keyword":"<span style=\"color:red\">剖开</span><span style=\"color:red\">算子</span><span style=\"color:red\">法</span>","originalKeyword":"剖开算子法"}],"language":"zh","publisherId":"gsytb201301002","title":"基于<span style=\"color:red\">剖开</span><span style=\"color:red\">算子</span><span style=\"color:red\">法</span>的水泥篦冷机熟料换热模型研究","volume":"32","year":"2013"},{"abstractinfo":"给出了格子Boltzmann方法(LBM)密度分布函数和温度分布函数的两个重构<span style=\"color:red\">算子</span>,解决了LBM与其它方法耦合的关键难题.构造了LBM与有限容积<span style=\"color:red\">法</span>(FVM)以及LBM与分子动力模拟方法(MD)的两个耦合模型.通过方腔自然对流以及平板通道内的泊肃叶流动对耦合模型进行验证.结果表明,基于重构<span style=\"color:red\">算子</span>的耦合模型可以正确地应用于LBM与其它方法的耦合计算中.","authors":[{"authorName":"栾辉宝","id":"7b38cbb8-23f4-49b7-9912-9b46c86a966b","originalAuthorName":"栾辉宝"},{"authorName":"陈黎","id":"b759723f-66da-4d8e-9ed5-dd05ed43422d","originalAuthorName":"陈黎"},{"authorName":"周文静","id":"fefc3818-51c2-4b8a-86c3-4ebaf68d001d","originalAuthorName":"周文静"},{"authorName":"孙杰","id":"2b3214bc-10f0-4cae-8aa1-1a2cdc256af5","originalAuthorName":"孙杰"},{"authorName":"何雅玲","id":"b627244c-b9d3-492d-8e8a-d937028c184d","originalAuthorName":"何雅玲"},{"authorName":"陶文铨","id":"4f0a5470-9de2-40c2-94e6-751db4d33367","originalAuthorName":"陶文铨"}],"doi":"","fpage":"997","id":"3c9ea869-485a-4b7e-9a28-98865140a2e0","issue":"6","journal":{"abbrevTitle":"GCRWLXB","coverImgSrc":"journal/img/cover/GCRWLXB.jpg","id":"32","issnPpub":"0253-231X","publisherId":"GCRWLXB","title":"工程热物理学报   "},"keywords":[{"id":"b748550c-ae86-4c9e-aae1-3b85b12e8f47","keyword":"格子Botlzmann方法","originalKeyword":"格子Botlzmann方法"},{"id":"05110c1c-49bb-457c-ba58-7910fb3f36ef","keyword":"多尺度","originalKeyword":"多尺度"},{"id":"cfc80772-18e6-44cf-ae13-a8aac835c008","keyword":"耦合","originalKeyword":"耦合"},{"id":"552da216-7a61-431e-9bec-6378efbedc9e","keyword":"重构<span style=\"color:red\">算子</span>","originalKeyword":"重构算子"}],"language":"zh","publisherId":"gcrwlxb201106025","title":"格子Boltzmann方法分布函数重构<span style=\"color:red\">算子</span>的应用","volume":"32","year":"2011"},{"abstractinfo":"本文提出一种基于 GPU＋CPU 的快速实现 Canny <span style=\"color:red\">算子</span>的方法.首先将<span style=\"color:red\">算子</span>分为串行和并行两部分,高斯滤波、梯度幅值和方向计算、非极大值抑制和双阈值处理在 GPU 中完成,将二维高斯滤波分解为水平方向上和垂直方向上的两次一维滤波从而降低计算的复杂度；然后使用 CUDA 编程完成多线程并行计算以加快计算速度；最后使用共享存储器隐藏线程访问全局存储的延迟；在 CPU 中则使用队列 FIFO 完成边缘连接.仿真测试结果表明：对分辨率为1024×1024的8位图像的处理时间为122 ms,相对应单独使用 CPU 而言,加速比最高可达5．39倍,因此本文方法充分利用了GPU 的并行性的特征和 CPU 的串行处理能力.","authors":[{"authorName":"唐斌","id":"b25aaf5d-6154-47e4-9942-4db92d100bc7","originalAuthorName":"唐斌"},{"authorName":"龙文","id":"3ed50337-146f-4f0b-882e-7424c33c81d7","originalAuthorName":"龙文"}],"doi":"10.3788/YJYXS20163107.0714","fpage":"714","id":"1769d87f-37ec-4856-acf8-569a104b384a","issue":"7","journal":{"abbrevTitle":"YJYXS","coverImgSrc":"journal/img/cover/YJYXS.jpg","id":"72","issnPpub":"1007-2780","publisherId":"YJYXS","title":"液晶与显示   "},"keywords":[{"id":"62168b81-1d38-445d-a43d-090b938638e1","keyword":"CANNY","originalKeyword":"CANNY"},{"id":"d3058d5e-9d02-49e8-9672-6b823ef45aa2","keyword":"CUDA","originalKeyword":"CUDA"},{"id":"7b9e67e3-11bc-4f59-9330-629f7c18c1e1","keyword":"GPU","originalKeyword":"GPU"},{"id":"1c055ac6-39b8-46b0-8db5-d09d26cd05ed","keyword":"加速","originalKeyword":"加速"}],"language":"zh","publisherId":"yjyxs201607014","title":"基于 GPU＋CPU 的 CANNY <span style=\"color:red\">算子</span>快速实现","volume":"31","year":"2016"},{"abstractinfo":"图像在传输过程中会受到各种噪声干扰,为了实现消除噪声的目的,提出一种基于LoG<span style=\"color:red\">算子</span>改进的自适应阈值去噪算法.首先,利用LoG<span style=\"color:red\">算子</span>提取图像的边缘特征信息.接着,根据图像的边缘特征和非边缘特征分别求取改进的阈值函数:对于图像非边缘部分的阈值函数,在软阈值函数的基础上添加一个阈值修正系数,构建新的阈值函数;对于图像边缘部分的阈值函数,将边缘部分小波系数附近的能量和阈值相结合,构建新的阈值函数.最后利用改进的阈值函数对图像R、G、B3个通道分别处理,保留图像所有的细节信息.实验结果表明,消噪后图像与含噪图像的PSNR值高于传统自适应算法12.09％;MAE值低于传统自适应算法22％.该算法有效保存了图像的边缘信息,综合去噪效果明显提高.","authors":[{"authorName":"董雪","id":"953eb2b6-f498-4293-b99f-32ec65abfafd","originalAuthorName":"董雪"},{"authorName":"林志贤","id":"11117af8-b2e4-4e47-b531-5cec85ce7d6c","originalAuthorName":"林志贤"},{"authorName":"郭太良","id":"8015dae8-f3a3-47f6-ad58-db8193091327","originalAuthorName":"郭太良"}],"doi":"10.3788/YJYXS20142902.0275","fpage":"275","id":"2b9fd7bf-d86a-4705-a4b7-9d66600a3190","issue":"2","journal":{"abbrevTitle":"YJYXS","coverImgSrc":"journal/img/cover/YJYXS.jpg","id":"72","issnPpub":"1007-2780","publisherId":"YJYXS","title":"液晶与显示   "},"keywords":[{"id":"d513f4b0-4bfd-4389-9ff1-078a964212a5","keyword":"阈值去噪","originalKeyword":"阈值去噪"},{"id":"c33aab0a-b03d-406d-a687-7d5a47f8e8d6","keyword":"LoG<span style=\"color:red\">算子</span>","originalKeyword":"LoG算子"},{"id":"868d9b6f-1589-4422-9114-61d78bed8246","keyword":"边缘信息","originalKeyword":"边缘信息"},{"id":"2619df56-0433-437b-9abb-711a646dae58","keyword":"小波系数能量","originalKeyword":"小波系数能量"}],"language":"zh","publisherId":"yjyxs201402020","title":"基于LoG<span style=\"color:red\">算子</span>改进的自适应阈值小波去噪算法","volume":"29","year":"2014"},{"abstractinfo":"振幅阻尼噪声存在于大量具有能量损失的真实量子比特系统中.利用两原子和单模腔共振相互作用的普遍模型,推导出振幅阻尼信道下两量子比特系统的联合Kraus<span style=\"color:red\">算子</span>表示.这为解决与量子信息处理相关的具体过程提供了有效方法,例如两量子比特纠缠分发和量子纠错.由于其普适性和计算的简便性,该方法还有助于解决很多实际的物理问题.","authors":[{"authorName":"杨青","id":"d2c094ac-fd14-45ec-8549-1f492c95e45e","originalAuthorName":"杨青"},{"authorName":"甄秀兰","id":"be0f3896-7890-496a-a35e-6aadc5fce438","originalAuthorName":"甄秀兰"},{"authorName":"杨名","id":"f8b5c0bf-46bd-45cc-8106-5bfc287e235d","originalAuthorName":"杨名"},{"authorName":"曹卓良","id":"04e2bbf2-dd61-4094-bdc7-b9016e0afb06","originalAuthorName":"曹卓良"}],"doi":"10.3969/j.issn.1007-5461.2014.06.011","fpage":"710","id":"8fa945bc-1d19-4439-a1bf-0165155ff49b","issue":"6","journal":{"abbrevTitle":"LZ","coverImgSrc":"journal/img/cover/LZ.jpg","id":"52","issnPpub":"1005-4006","publisherId":"LZ","title":"连铸"},"keywords":[{"id":"90e42dba-3b30-4b3a-93d7-e9738ca7fd60","keyword":"量子光学","originalKeyword":"量子光学"},{"id":"64e1b30b-bd1b-4512-8e2b-00dca17f8a3a","keyword":"Kraus<span style=\"color:red\">算子</span>","originalKeyword":"Kraus算子"},{"id":"ff5a1cb8-ff11-4f8f-bb69-a44824939a71","keyword":"振幅阻尼","originalKeyword":"振幅阻尼"},{"id":"3568a1a8-b2d5-4daf-92bb-4d073a63058c","keyword":"两量子比特","originalKeyword":"两量子比特"}],"language":"zh","publisherId":"lzdzxb201406011","title":"振幅阻尼信道下两量子比特的联合Kraus<span style=\"color:red\">算子</span>表示","volume":"31","year":"2014"},{"abstractinfo":"本文介绍了用时间倾斜<span style=\"color:red\">算子</span>来处理非定常计算中非等栅距的方法.通过引入时间倾斜<span style=\"color:red\">算子</span>对N-S方程进行转化,而不对几何结构作任何改变,且所计算的叶片通道数小,以确保有较好的计算效率.粘性的影响被归类到源项中来进行求解,在作时间倾斜的方程转换时,就不用忽略粘性应力项的影响,使得方程的求解更为真实.同商用软件的计算结果进行了比较,结果表明应用本文所发展的程序,能很好的预测离心压缩机级的非定常流动.","authors":[{"authorName":"周莉","id":"9e166bc5-e558-48a8-b5e0-12f89679231e","originalAuthorName":"周莉"},{"authorName":"席光","id":"01921fa9-b5c7-4572-a89b-5f0c207c8c97","originalAuthorName":"席光"},{"authorName":"高丽敏","id":"ca6171bf-6126-45a0-b498-33505b833f23","originalAuthorName":"高丽敏"},{"authorName":"王尚锦","id":"1e139281-4c48-48e8-b434-b168e19e3514","originalAuthorName":"王尚锦"}],"doi":"","fpage":"770","id":"a3a33781-10ff-4c80-afce-f8fab29dd388","issue":"5","journal":{"abbrevTitle":"GCRWLXB","coverImgSrc":"journal/img/cover/GCRWLXB.jpg","id":"32","issnPpub":"0253-231X","publisherId":"GCRWLXB","title":"工程热物理学报   "},"keywords":[{"id":"bcd25d0a-836c-43a1-8c86-ff478ffb8101","keyword":"时间倾斜<span style=\"color:red\">算子</span>","originalKeyword":"时间倾斜算子"},{"id":"91a91ad4-9d2b-4d09-bf0c-9ff860551e0e","keyword":"非等栅距","originalKeyword":"非等栅距"},{"id":"3ec7ac9b-4328-49f2-8d32-d12860e1c47b","keyword":"非定常","originalKeyword":"非定常"},{"id":"37a94bb6-daf6-4366-94ec-522c5b241123","keyword":"双时间步","originalKeyword":"双时间步"}],"language":"zh","publisherId":"gcrwlxb200505016","title":"时间倾斜<span style=\"color:red\">算子</span>在离心压缩机动/静相干非定常模拟中的应用","volume":"26","year":"2005"},{"abstractinfo":"通过对双曲正切-S<span style=\"color:red\">算子</span>的改进，提出了一种用于钢的大气腐蚀影响因子评估的BP神经网络模型，采用零均值标准化使输入数据符合模型要求，引入贝叶斯正则化算法解决了小样本泛化问题。仿真试验表明，该模型能在无任何先验知识的情况下较好的反映诸因子对大气腐蚀的影响。","authors":[{"authorName":"栾瑞鹏","id":"3e3fdca6-1057-45e5-82d0-b30c2d3646ae","originalAuthorName":"栾瑞鹏"},{"authorName":"贲可荣","id":"6f842f52-32c2-43ba-a4ca-6f1f0c623235","originalAuthorName":"贲可荣"},{"authorName":"萧星","id":"364f795a-9eef-4e7a-a565-80561e0dc3f5","originalAuthorName":"萧星"},{"authorName":"田立业","id":"38f2ffc4-ae88-410e-b600-a744f560acae","originalAuthorName":"田立业"}],"categoryName":"|","doi":"","fpage":"227","id":"b90bbbd6-76c8-4023-8f13-2e7002ce0f4a","issue":"3","journal":{"abbrevTitle":"ZGFSYFHXB","coverImgSrc":"journal/img/cover/中国腐蚀封面19-3期-01.jpg","id":"81","issnPpub":"1005-4537","publisherId":"ZGFSYFHXB","title":"中国腐蚀与防护学报"},"keywords":[{"id":"94867450-e643-4af1-9306-f0d1d989a818","keyword":"双曲正切-S<span style=\"color:red\">算子</span>","originalKeyword":"双曲正切-S算子"},{"id":"a0af3895-a8cb-4c1b-8088-ac05cce87e55","keyword":"BP neural network","originalKeyword":"BP neural network"},{"id":"c354b98e-021e-490f-9916-87c250779108","keyword":"Bayesian-regularization","originalKeyword":"Bayesian-regularization"},{"id":"11ac9de6-0818-4847-85dc-5fa59ae68090","keyword":"atmospheric corrosion","originalKeyword":"atmospheric corrosion"}],"language":"zh","publisherId":"1005-4537_2010_3_6","title":"基于改进型S<span style=\"color:red\">算子</span>BP神经网络的钢材大气腐蚀影响因子评估模型","volume":"30","year":"2010"},{"abstractinfo":"采用多波长薄层色谱扫描<span style=\"color:red\">法</span>,不经过传统的薄层色谱展开步骤实现混合体系的快速定量.废木料液化过程产物为混合体系,分别将不同液化反应时间点所取样品点样于硅胶板上.仅对液化过程终点的样本点进行一次展开,分离斜投影建模所需的反射光谱,切割出目标产物(乙酰丙酸)和背景光谱,构造斜投影<span style=\"color:red\">算子</span>;对其他液化过程中的样品点不展开,采集混合光谱,经斜投影算法分离出其中的目标产物纯光谱,从而实现定量.将该方法的定量结果与高效液相色谱<span style=\"color:red\">法</span>的定量结果对比,得到两种方法测定乙酰丙酸的相对误差小于3.27％,表明两种方法具有良好的一致性.","authors":[{"authorName":"粟晖","id":"584a338c-98b3-44a9-9433-ba98f630947f","originalAuthorName":"粟晖"},{"authorName":"葛军","id":"a717d5c7-cd3d-43f8-b4c7-f247801a0ae6","originalAuthorName":"葛军"},{"authorName":"方凤","id":"9c44e200-aa47-46bc-8ba1-0ac6a5f49bb0","originalAuthorName":"方凤"},{"authorName":"姚志湘","id":"7d042234-71e4-476a-81ba-53c5f5999dc8","originalAuthorName":"姚志湘"},{"authorName":"宋光均","id":"66af12d0-e224-48d4-a2d5-7ec57306bbb5","originalAuthorName":"宋光均"}],"doi":"10.3724/SP.J.1123.2013.08008","fpage":"100","id":"7ee1c4dd-9d67-4a55-b226-cb58075f780e","issue":"1","journal":{"abbrevTitle":"SP","coverImgSrc":"journal/img/cover/SP.jpg","id":"58","issnPpub":"1000-8713","publisherId":"SP","title":"色谱 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style=\"color:red\">法</span>对废木料液化产物乙酰丙酸的过程分析","volume":"32","year":"2014"},{"abstractinfo":"","authors":[{"authorName":"张亦弛","id":"6176dcd7-0de2-4d4f-9c14-489dc06f9511","originalAuthorName":"张亦弛"},{"authorName":"苏扬","id":"6c661572-0205-4d1f-adab-77e44b83de8e","originalAuthorName":"苏扬"}],"doi":"10.3969/j.issn.1000-6826.2011.01.013","fpage":"45","id":"4851e903-fd7f-4689-bf84-00851f484242","issue":"1","journal":{"abbrevTitle":"JSSJ","coverImgSrc":"journal/img/cover/3abe017a-2574-4821-8152-4ae974ef0471.jpg","id":"47","issnPpub":"1000-6826","publisherId":"JSSJ","title":"金属世界"},"keywords":[{"id":"ac8c879a-d6a6-4be3-ac5f-8484518642e4","keyword":"","originalKeyword":""}],"language":"zh","publisherId":"jssj201101013","title":"哪种MATLAB边缘检测<span style=\"color:red\">算子</span>更适合金属表面平整度检测?","volume":"","year":"2011"},{"abstractinfo":"从分数导数的定义出发,提出了在经典粘弹性模型理论中采用Abel粘壶取代传统牛顿粘壶的新观点.将有机硅高分子材料在MTS831.10材料试验机上进行动态力学行为试验,对试验结果分别用经典粘弹性模型和分数导数模型进行拟合.结果表明,分数导数Kelvin模型可以同时精确地拟合高分子材料的存储模量和损耗模量随频率变化的曲线,而且其形式简单、统一,在计算过程中需要调整的参数很少.","authors":[{"authorName":"孙海忠","id":"1af632c4-98f5-4c34-a7f2-18b534bbf147","originalAuthorName":"孙海忠"},{"authorName":"张卫","id":"9d1171f2-68a5-4b4e-94ff-27f4c9e62c65","originalAuthorName":"张卫"}],"doi":"10.3969/j.issn.1673-2812.2006.06.034","fpage":"926","id":"5152c5a3-3501-4ce5-bf5d-afe13a0a0794","issue":"6","journal":{"abbrevTitle":"CLKXYGCXB","coverImgSrc":"journal/img/cover/CLKXYGCXB.jpg","id":"13","issnPpub":"1673-2812","publisherId":"CLKXYGCXB","title":"材料科学与工程学报"},"keywords":[{"id":"e7d3895c-183b-4bca-9323-a3407ccdbfe5","keyword":"分数导数","originalKeyword":"分数导数"},{"id":"a7ee3663-2059-4c68-90f5-3afbfdfbb050","keyword":"高分子材料","originalKeyword":"高分子材料"},{"id":"e1f40a63-0715-4dd4-91f8-4f2b686712b4","keyword":"粘弹性","originalKeyword":"粘弹性"},{"id":"3e497bcc-eab3-4b24-a61e-bf13529d2186","keyword":"MTS","originalKeyword":"MTS"},{"id":"1e08f44d-e322-44c6-b642-b357a6170d3c","keyword":"本构关系","originalKeyword":"本构关系"}],"language":"zh","publisherId":"clkxygc200606034","title":"分数<span 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