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2010 Second International Conference on Computational Intelligence and Natural Computing最新文献

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Application of keywords speech recognition in agricultural voice information system 关键词语音识别在农业语音信息系统中的应用
Wenhao Ou, W. Gao, Zhen Li, Shuliang Zhang, Qing Wang
This paper describes the Microsoft speech recognition technology and SAPI recognition interface provided by Microsoft speech development platform. Command mode of speech recognition, with custom keywords, can improve speech recognition accuracy. Then, an agricultural voice information system based on speech recognition is designed and implemented on the Microsoft speech development platform, which can improve the complicated touch-tone operations. The users can access the voice information system easily only through oral description. This technology also simplifies the process of system response.
本文介绍了微软语音识别技术和微软语音开发平台提供的SAPI识别接口。语音识别的命令模式,通过自定义关键字,可以提高语音识别的准确率。然后,在Microsoft语音开发平台上设计并实现了一个基于语音识别的农业语音信息系统,改善了复杂的按键式操作。用户只需通过口头描述即可方便地访问语音信息系统。该技术还简化了系统响应过程。
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引用次数: 11
Research on the improvement of slide projector calibration precision 提高幻灯机校准精度的研究
Zheng Li, Luo Jun, L. Tao
The camera calibration and projector calibration are very crucial since the coordinate computation depends on the accuracy of calibration. This calibration procedure consists of camera calibration and projector calibration, done in this order so that the calibrated camera can be used to calibrate the projector. The digital camera is firstly calibrated by the algorithm with 2D direct linear transformation (2D-DLT) and collinear equations. Based on the same calibration model, the calibration precision of projector is lower than that of CCD camera. It is analyzed by the following aspects, such as image and space. For the space point error by paper thickness and distortion, the Z value of space point is compensated through stimulant data. Then the improvement of projector calibration is completed successfully after bundle adjustment and the calculation to the projector parameters again.
摄像机标定和投影仪标定是非常重要的,因为坐标计算取决于标定的精度。此校准程序包括摄像机校准和投影仪校准,按此顺序完成,以便校准后的摄像机可以用于校准投影仪。首先利用二维直接线性变换(2D- dlt)和共线方程对数码相机进行标定。基于相同的标定模型,投影仪的标定精度低于CCD摄像机。主要从图像、空间等方面进行分析。对于纸张厚度和变形造成的空间点误差,通过刺激数据补偿空间点的Z值。然后再对投影机参数进行束调整和计算,成功完成投影机标定的改进。
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引用次数: 0
Application of facies-controlling stochastic modeling technique in heterogeneity reservoir and its effective application analysis 控相随机建模技术在非均质储层中的应用及其有效应用分析
Deng Mei-yin, Ren Weiwei, Zhang Jinliang
Many oilfield have gone into the intermediary or later stage of development, with the raise of the development level, reservoir geologic research urgently need some new practical technique method to describe reservoir properties accurately and carefully. Basing on principles of sedimentology and quantitative analysis of well logging interpretation, carrying out micro-phase study, and using the research results of micro-facies to constrain the spatial distribution of reservoir parameters. Establishing a fine reservoir geological model, and solve the problem of sedimentary facies modeling can not effective combination in the process of modeling. Practices have proved that this method is feasible, especially in the heterogeneity reservoirs. Application of phase control modeling technique not only provide a more accurate reservoir property model, but also can provide a geological basis for the remaining petroleum development and development adjustment.
许多油田已进入开发中后期,随着开发水平的提高,储层地质研究迫切需要一些新的实用技术方法来准确、细致地描述储层物性。基于沉积学原理和测井解释定量分析,开展微相研究,利用微相研究成果约束储层参数的空间分布。建立精细的储层地质模型,解决了建模过程中沉积相建模不能有效结合的问题。实践证明,该方法是可行的,特别是在非均质储层中。相控建模技术的应用不仅可以提供更精确的储层物性模型,而且可以为剩余油开发和开发调整提供地质依据。
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引用次数: 1
A fast algorithm of logarithm-form fractional lower-order spectrums 对数形式分数阶低阶谱的快速算法
Jinlong Jiang, Daifeng Zha, Qian Zhang
A fast algorithm of logarithm-form fractional lower-order spectrums is proposed in this paper in order to be facilitative for practice application that traditional fractional lower-order spectrums need to identify characteristic exponent alpha and improve its calculating speed for alpha stable distribution signal or noise. The algorithm is not depended on a prior knowledge of characteristic exponent alpha, and ease to apply to DSP systems by assembly language instructions and fast Fourier transform (FFT). The application in a TMS320VC5416 DSP system shows that the algorithm is effective.
针对传统分数阶低阶谱对α稳定分布信号或噪声需要识别特征指数α,提高其计算速度的问题,本文提出了一种对数形式分数阶低阶谱的快速算法。该算法不依赖于特征指数alpha的先验知识,并且易于通过汇编语言指令和快速傅里叶变换(FFT)应用于DSP系统。在TMS320VC5416 DSP系统上的应用表明了该算法的有效性。
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引用次数: 0
A cognitive learning model in classroom interaction 课堂互动中的认知学习模式
Cui Guang-zuo
This paper, based on the cognitive architecture of learning and thinking [7], proposes a cognitive learning model in classroom interaction, which bridges the gap between classroom interaction and learning outcome. In this model, a learning activity is defined as a cognitive matrix at a low level in which M rows and N columns are set, each row represents a logical cognitive step of learning procedure, and each column contains all the contents processed by a corresponding component in cognitive architecture. At the meantime, the learning outcome can be produced from contents of column LTDM, AO and AADM of cognitive architecture [7]. A memory consolidation model is also proposed and simulated with PDP tool. Experiment of teaching concept knowledge indicates the effectiveness of the proposed models.
本文基于学习与思维的认知架构[7],提出了一种课堂互动中的认知学习模型,它弥合了课堂互动与学习结果之间的差距。该模型将学习活动定义为一个低级的认知矩阵,其中设置M行N列,每一行表示学习过程的一个逻辑认知步骤,每一列包含认知架构中相应组件处理的所有内容。同时,学习成果可以从认知架构的LTDM、AO和AADM栏目的内容中产生[7]。提出了一个内存整合模型,并用PDP工具进行了仿真。教学概念知识实验表明了模型的有效性。
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引用次数: 3
Wind turbine simulation of offshore environmental conditions 海上风力机环境条件模拟
Dazhi Wang, Huaming Wang, Yupeng Shi, Jun Li, Keling Song, Shengli Liu, Yiqi Li
In order to achieve the simulation of the external offshore environmental conditions in the wind power generation system, a wind speed model and a tower load module was built by simulink for calculating the wind load and current load on the wind rotor and tower load and introduce the ice load briefly. The simulation results show that the model can not only show positive responses to the actual wind speed, but also provide the correct source parameters for the study of wind power generation analog systems. Load model has directive significance for the calculations of the offshore wind turbine load.
为了实现对风力发电系统海上外部环境条件的仿真,利用simulink建立了风速模型和塔荷载模块,计算了风转子和塔荷载上的风荷载和电流荷载,并对冰荷载进行了简要介绍。仿真结果表明,该模型不仅能较好地响应实际风速,而且能为风力发电模拟系统的研究提供正确的风源参数。负荷模型对海上风电机组负荷的计算具有指导意义。
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引用次数: 0
A k-climax neighbors policy based viterbi decoding for large vocabulary mandarin speech recognition 基于k-高潮邻居策略的大词汇量普通话语音识别viterbi解码
Pei Zhao, Xihong Wu
In this paper, we apply the k-climax neighbors (k-CN) policy derived from the Bayesian Ying-Yang (BYY) learning framework to Viterbi decoding for Hidden Markov Model based large vocabulary mandarin speech recognition, to adaptively obtain a more precise state decision boundary in the decoding phase. When calculating the posterior probability for each state on a given frame, k Gaussian components from these states are selected by the k-CN policy as the most reliable descriptions, which make the decision boundaries among the competitive candidate states more precise. The experimental results show that a 2.1% relative reduction of the character error rate is achieved on Hub-4 test by adopting the proposed approach.
本文将基于Bayesian yingyyang (BYY)学习框架的k-climax neighbors (k-CN)策略应用到基于隐马尔可夫模型的大词汇量普通话语音识别的Viterbi解码中,自适应地获得更精确的解码阶段状态决策边界。在计算给定帧上每个状态的后验概率时,k- cn策略从这些状态中选择k个高斯分量作为最可靠的描述,使得竞争候选状态之间的决策边界更加精确。实验结果表明,采用该方法可使Hub-4测试的字符错误率相对降低2.1%。
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引用次数: 0
ℌFlower basin effectℍ and autonomous foreign language learning with the aid of network and multimedia <s:1>花盆效应<e:1>与网络多媒体辅助外语自主学习
Zhang Chun, Fan Xiying
ℌFlower Basin Effectℍ exists universally in foreign language study. This paper first studied incomparable superiority of classroom teaching(ℌflower basinℍ environment) to language acquisition in natural environment , as well as its inherent limitations. In order to overcome limitations of classroom teaching and maximize the learning efficiency, the paper explored the development of the students' autonomous learning ability in the new environment ----network and multimedia environment. The main ways are: we should socialize classroom teaching, give students diagnosis and training of their learning strategies, adopt teaching mode combining classroom teaching and network autonomous learning and establish network autonomous learning resource bank.
摘要花盆效应在外语学习中普遍存在。本文首先研究了课堂教学(花盆环境)对自然环境下语言习得的不可比拟的优势,以及其固有的局限性。为了克服课堂教学的局限性,最大限度地提高学习效率,本文探讨了在新环境----网络和多媒体环境下学生自主学习能力的培养。主要有:课堂教学社会化,对学生的学习策略进行诊断和训练,采用课堂教学与网络自主学习相结合的教学模式,建立网络自主学习资源库。
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引用次数: 0
Hierarchical exploration based active learning with support vector machine 基于层次探索的支持向量机主动学习
Yanping Yang, E. Song, Guangzhi Ma
The goal of active learning is to minimize the amount of labeled data required for machine learning. Some methods have focused on exploiting the samples with high uncertainty, but those methods fail in getting a representative set of the data samples. Other methods try to explore the representative samples by utilizing the prior distribution of the dataset. However, they are often computationally expensive and need a large amount of labeled data for initialization. In this paper we develop a hierarchical exploration based active learning algorithm that takes into account both the distribution of the dataset and the decision boundary of the current hypothesis. Our method uses the support vector machine (SVM) as the classifier. The hierarchical clustering algorithm is used to discover the dataset's structure step by step in a top-down manner. In each step of hierarchical structure discovery, the representative samples will be queried for labels to check the relative cluster's purity. The cluster with low purity will be divided further. After the draft SVM model is built with those representative samples, the uncertain samples near decision boundary will be further labeled if it can help reduce the entropy of the classifier. To show the effectiveness of the proposed method, our proposed method is compared with five state-of-art algorithms on six datasets from UCI. Our method shows the best performance through the comparison.
主动学习的目标是最小化机器学习所需的标记数据量。一些方法侧重于开发具有高不确定性的样本,但这些方法无法获得具有代表性的数据样本集。其他方法试图通过利用数据集的先验分布来探索代表性样本。然而,它们通常在计算上很昂贵,并且需要大量的标记数据进行初始化。在本文中,我们开发了一种基于分层探索的主动学习算法,该算法同时考虑了数据集的分布和当前假设的决策边界。我们的方法使用支持向量机(SVM)作为分类器。采用分层聚类算法,自上而下逐步发现数据集的结构。在层次结构发现的每一步中,都会查询代表性样本的标签,以检查相对聚类的纯度。纯度低的团簇将进一步划分。在用这些代表性样本构建SVM模型草稿后,对决策边界附近的不确定样本进行进一步标记,以帮助降低分类器的熵。为了证明该方法的有效性,我们将该方法与来自UCI的六个数据集上的五种最新算法进行了比较。通过比较,我们的方法表现出最好的性能。
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引用次数: 3
Statistical analysis of Rician and Nakagami-m fading channel using multipath Shape factors 基于多径形状因子的rici和nakagami衰落信道统计分析
Hai-ying Shang, Yu Han, Ji-hua Lu
Statistical characteristics of Rician and Nakagami-m fading channel are considered which develops the statistical analysis to characterize the frequency-selective fading properties. We use a new analytical multipath shape factors proposed by Durgin which greatly simplifies the description of Rician and Nakagami-m fading channel. The three shape factors are angular spread, angular constriction and azimuthal direction of maximum fading. The first-order and second-order statistics of received signal fluctuations in Rician and Nakagami-m multipath fading channel are analyzed. Analytical expressions for spatial unit autocovariance and coherence distance are both used in the shape factor theory.
考虑了rici和Nakagami-m衰落信道的统计特性,对其频率选择性衰落特性进行了统计分析。我们使用了Durgin提出的一种新的解析型多径形状因子,极大地简化了对rici和Nakagami-m衰落信道的描述。三个形状因子分别是角扩展、角收缩和最大衰落的方位方向。分析了接收信号在rici和Nakagami-m多径衰落信道中的一阶和二阶统计量。在形状因子理论中,空间单位自协方差和相干距离都使用解析表达式。
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引用次数: 11
期刊
2010 Second International Conference on Computational Intelligence and Natural Computing
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