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11.
Kwangryul Hwang Takafumi Noguchi Fuminiro Tomosawa 《Cement and Concrete Research》2004,34(12):697-2276
Based on experimental results concerning the compressive strength development of concrete containing fly ash, the authors derived an estimation equation for compressive strength development. The equation can express coefficient , which indicates the activity of fly ash as a binder, in the form of a function of age, fly-ash content, and Blaine specific surface area of fly ash.
This equation is capable of explaining the increases in the early strength due to fly ash in place of part of fine aggregate, the decreases in the early strength due to fly ash in place of part of cement, the increases in the long-term strength due to pozzolanic reaction, the relationship between the fly-ash replacement ratio and the ratio of strength increase/decrease, and the effect of fly ash's Blaine specific surface area on the strength. 相似文献
12.
陈虎 《网络安全技术与应用》2014,(3):153-154
本文主要研究了在复杂网络环境下的信息安全风险预测问题。它提出了一种较为实用并且具有一定广泛意义的网络风险态势预测方法;通过实验表明,本方法可以满足因网络结构复杂、资产价值不一而造成的风险态势评估误报问题,有实际应用意义。 相似文献
13.
研究电力系统中用电量的准确预测问题.由于影响用电量的因素众多,并且用电量数据与相关因素之间呈现高度的非线性关系,传统的预测方法很难捕捉用电量的变化趋势,预测精度较低.为了提高预测的精度,提出了一种马尔可夫链优化的SVR模型.上述模型根据支持向量回归机原理,以网络搜索交叉验证的思想优化模型参数,通过加权马尔可夫链原理优化预测结果,将原来的数值预测转化为概率区间上的预测.同时,在利用加权马尔可夫链的预测信息之后,也提高了预测的精度.最后,将改进模型应用于江苏省全社会用电量的预测分析,实验结果表明优化的支持向量模型优于其它对比模型,有较高的泛化能力和预测精度. 相似文献
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15.
This study developed a methodology for formulating water level models to forecast river stages during typhoons, comparing various models by using lazy and eager learning approaches. Two lazy learning models were introduced: the locally weighted regression (LWR) and the k-nearest neighbor (kNN) models. Their efficacy was compared with that of three eager learning models, namely, the artificial neural network (ANN), support vector regression (SVR), and linear regression (REG). These models were employed to analyze the Tanshui River Basin in Taiwan. The data collected comprised 50 historical typhoon events and relevant hourly hydrological data from the river basin during 1996–2007. The forecasting horizon ranged from 1 h to 4 h. Various statistical measures were calculated, including the correlation coefficient, mean absolute error, and root mean square error. Moreover, significance, computation efficiency, and Akaike information criterion were evaluated. The results indicated that (a) among the eager learning models, ANN and SVR yielded more favorable results than REG (based on statistical analyses and significance tests). Although ANN, SVR, and REG were categorized as eager learning models, their predictive abilities varied according to various global learning optimizers. (b) Regarding the lazy learning models, LWR performed more favorably than kNN. Although LWR and kNN were categorized as lazy learning models, their predictive abilities were based on diverse local learning optimizers. (c) A comparison of eager and lazy learning models indicated that neither were effective or yielded favorable results, because the distinct approximators of models that can be categorized as either eager or lazy learning models caused the performance to be dependent on individual models. 相似文献
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17.
介绍了目前我国煤矿瓦斯安全的现状和瓦斯涌出量预测的6种方法,分析了预测方法的原理和适用条件,并对预测方法的性能进行比较。 相似文献
18.
This paper resolves the problem of predicting as well as the best expert up to an additive term of the order o(n), where n is the length of a sequence of letters from a finite alphabet. We call the games that permit this weakly mixable and give a geometrical characterisation of the class of weakly mixable games. Weak mixability turns out to be equivalent to convexity of the finite part of the set of superpredictions. For bounded games we introduce the Weak Aggregating Algorithm that allows us to obtain additive terms of the form . 相似文献
19.
Question-Answering Bulletin Boards (QABB), such as Yahoo! Answers and Windows Live QnA, are gaining popularity recently. Questions
are submitted on QABB and let somebody in the internet answer them. Communications on QABB connect users, and the overall
connections can be regarded as a social network. If the evolution of social networks can be predicted, it is quite useful
for encouraging communications among users. Link prediction on QABB can be used for recommendation to potential answerers.
Previous approaches for link prediction based on structural properties do not take weights of links into account. This paper
describes an improved method for predicting links based on weighted proximity measures of social networks. The method is based
on an assumption that proximities between nodes can be estimated better by using both graph proximity measures and the weights
of existing links in a social network. In order to show the effectiveness of our method, the data of Yahoo! Chiebukuro (Japanese
Yahoo! Answers) are used for our experiments. The results show that our method outperforms previous approaches, especially
when target social networks are sufficiently dense.
相似文献
Tsuyoshi MurataEmail: |
20.
BP神经网络算法预测及其在飞参数据分析中的应用 总被引:1,自引:0,他引:1
针对飞机喘振参数受随机因素影响的特点,提出了用人工神经网络中BP网络对飞机发动机喘振预测.通过对喘振数据及机组实际振动数据的预测结果检验,证明该神经网络预测有利于飞机发动机喘振状态的预测精度. 相似文献