for the former one, we propose a precision optimization method based on information retrieval, and use recall and precision to measure it.

a probabilistic-based news full-text retrieval and ranking algorithm is discussed and the probability ranking principle for full-text is proposed.

本文讨论了概率模型的新闻资料全文检索及排序算法。作者提出了全文检索最佳排序原则。

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if i don't know the title or the author, what should i do?

如果我既不知道书名也不知道作者，该怎么检索？

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conclusion: the standards of peer-review must be developed that require authors of meta-analyses to report evidence for the effectiveness about their retrieval strategies.

结论：专家评审标准一定要力争得到进一步发展，那就要求Meta分析的作者，对他们检索策略的效果证据要加以报道。

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based on the retrieval examples from fulltext database of china journal net, this paper attempts to explore the methods of improving recall and accuracy ratio in terms of selecting subject terms and logical relations.

本文结合作者的文献检索工作实践，以中国期刊同专题全文数据库的检索为例，从选择主题词与配置合适的逻辑关系两方面探讨了提高文献检索查全率与查准率的方法。

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combining the author's practical experience, this paper discusses the retrieval skills of cbm disc, and lists many examples, which is of great reference value to both teachers and learners.

文章结合作者的检索实践，探讨了该库的有关检索技巧，对文献检索学习者和教学者有重要的参考价值。

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gray model and forecast of the orbit of mobile target

机动目标运动轨迹的灰色建模与预测

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the state space modeling and forecast of non-stable time sequence

非平稳时间序列的状态空间建模与预测

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modeling and predicting of water cut dynamics of polymer flooding

聚合物驱油含水率动态规律建模与预测

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nonlinear modeling and predictive control based on prior knowledge and neural networks

基于先验知识和神经网络的非线性建模与预测控制

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research on nonlinear combining modeling and forecasting of foreign exchange rate

汇率预报的非线性组合建模与预测方法研究

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optimal modeling and forecasting on 30 year tourism foreign exchange earnings

基于30年入境旅游外汇收入的最佳建模与预测

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the modelling and prediction of magnitude sequence of large north china

大华北震级序列的建模与预测

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we present that rbf neural networks can be used in the modeling and prediction of chaotic time series. a three layers rbf network structure is designed and fundamental properties of rbf networks are clarified when they are used in the modeling and prediction of chaotic time series.

提出将RBF神经网络应用于混沌时间序列的建模与预测中，设计了一个三层RBF网络结构，说明了RBF网络用于混沌时间序列建模和预测时的基本性质。

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in this paper we proposed a new algorithm, which called sliding window wavelet binary tree ( swbt), and it can detect and analyze the network anomalies. using swbt and arx model, we can model and forecast network traffic.

本文提出一种新的网络异常检测与分析方法，通过滑窗小波二叉树和ARX模型实现对网络流量的建模与预测，再由聚类EM算法对其分类并检测异常点。

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this paper presents a new nonlinear composite forecasting method for exchange rate modeling and forecasting based on support vector machines regression. furthermore, the problems how to select the kernel function, loss function and control capacity, and so on, are discussed with simulation demonstration.

本文提出了一种基于支持向量机回归（SVM）的汇率非线性组合建模与预测新方法，并讨论了建模中SVM核函数、损失函数的选取和容量控制等问题。

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as combining forecasts are more accurate than individual ones, this paper presents a new method to set up nonlinear composite and forecast the special treatment ( st) for listed firm based on fuzzy neural network, and gives the corresponding composite learning algorithm.

针对组合预测比单项预测具有更高的预测精度，本文提出了一种基于模糊神经网络的上市公司被ST的非线性组合建模与预测新方法，并给出了相应的混合学习算法。

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a separating feature selection approach concerning the combination of svms ( support vector machine) is proposed, whose basic idea is to execute feature selection on each svm in the combination and use the different selected feature subsets as the inputs.

文章提出了一种针对SVM组合技术的拆分特征选择方法，其主要思想是对SVM组合中的各个分类器分别进行特征选择，再采用不同的特征子集作为各子分类器的输入，进行组合建模与预测。

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a new model of integrating artificial neural network ( ann) with auto regressive moving average ( arma) is studied to handle existing problems of forecasting methods of product consumption based on non-stationary time series.

针对基于非平稳时序的产品需求量预测方法存在的问题，研究了人工神经网络（ANN）与自回归滑动平均（ARMA）模型的集成建模与预测方法。

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ls-svm model is used to mode and predict the gdp in the macroeconomic model. the ls-svm model parameters is optimized by using multi-scale chaotic genetic optimization.

运用LS-SVM模型进行宏观经济模型（以GDP为目标）的建模与预测，同时，利用改进的多尺度混沌遗传优化算法对LS-SVM模型的参数进行优化。

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third, the grey system model gm ( 1,1) and garch model can respectively be used to predict for stock price and volatility.

然而深市对沪市存在着正的波动性溢出效应，其效果要小于沪市对深市的溢出效应。灰色系统模型和GARCH模型均分别能够成功地用于对我国股市的价格和波动性的建模与预测。

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