Improving the learning of Boolean queries by means of a multiobjective IQBE evolutionary algorithm     

O. Cordón  E. Herrera-Viedma  M. Luque 《Information processing & management》2006

The Inductive Query By Example (IQBE) paradigm allows a system to automatically derive queries for a specific Information Retrieval System (IRS). Classic IRSs based on this paradigm [Smith, M., & Smith, M. (1997). The use of genetic programming to build Boolean queries for text retrieval through relevance feedback. Journal of Information Science, 23(6), 423–431] generate a single solution (Boolean query) in each run, that with the best fitness value, which is usually based on a weighted combination of the basic performance criteria, precision and recall.  相似文献   

遗传算法中初始种群与交叉、变异率对解的影响及其解决方案   总被引：13，自引：0，他引：13  

唐世浩  朱启疆 《科技通报》2001,17(3):1-7

本文的研究表明，在相同的遗传算子下，初始种群性状和数量以及交叉、变异率的确定对算法收敛速度和结果的影响不能忽略。初始种群或交叉、变异率选择不当，将增加迭代次数，甚至直接导致算法陷入局部最优解。为此，本文提出一种基于空间分割的遗传算法及初始种群产生和种群数量确定方法，并根据有关文献，提出一种自适应交叉、变异率方法。实际计算表明，该算法在很大程度上避免了算法收敛于局部最优点，取得较好的效果。  相似文献   

Multi-layer self-organizing polynomial neural networks and their development with the use of genetic algorithms   总被引：1，自引：0，他引：1  

Sung-Kwun Oh 《Journal of The Franklin Institute》2006,343(2):125-136

In this paper, we introduce a new architecture of genetic algorithms (GA)-based self-organizing polynomial neural networks (SOPNN) and discuss a comprehensive design methodology. Let us recall that the design of the “conventional” PNNs uses an extended group method of data handling (GMDH) and exploits polynomials (such as linear, quadratic, and modified quadratic functions) as well as considers a fixed number of input nodes (as being selected in advance by a network designer) at polynomial neurons (or nodes) located in each layer. The proposed GA-based SOPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional PNNs. The design procedure applied in the construction of each layer of a PNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomial, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the network. To evaluate the performance of the GA-based SOPNN, the model is experimented with using chaotic time series data. A comparative analysis reveals that the proposed GA-based SOPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.  相似文献   

遗传算法在股票投资技术分析中的应用     

冯平  宣慧玉 《预测》2001,20(2):38-41

本文首先分析了股票投资技术分析的特点,然后阐述了遗传算法及基于遗传算法的分类器系统的基本理论.最后,详细讨论了遗传算法及分类器系统在两种最常用的股票投资技术分析方法(指标分析和图形分析)的计算机化中的运用问题.  相似文献   

聚合物的分子拓扑结构与物性的关联     

张引沁  田维 《平原大学学报》2002,19(4):38-40

应用分子拓扑指数来定量描述分子结构，采用遗传算法来选择与物性相关的分子连接性指数，通过多元线性回归分析建立分子拓扑结构与物性的关联方程，采用此方法，本研究了66种聚合物的玻璃化温度（Tg)与分子拓扑结构的关系，并对12种聚合物的玻璃化温度进行了推算，结果表明聚合物的玻璃化温度与分子连接性指数有较好的相关性。  相似文献   

演化算法求解约束多目标优化问题     

杨林根  李红梅周育人 《广东白云学院学刊》2005,(1):27-29

本文引入约束占优的定义，将约束条件与目标函数融合在一起，对有约束的多目标优化问题（MOP）建立了一种新的偏序关系。使用多父体杂交和非均匀变异来求解约束多目标优化问题，通过对测试函数的实验，验证了算法的可行性和有效性。  相似文献   

一种改进的Apriori算法     

陈建辉 《宜春学院学报》2007,29(4):87-88,122

在对关联规则挖掘算法Apriori进行深入研究的基础上,提出了一种改进的算法SDA算法,在三个方面进行了改进:(1)频繁2-项集生成方法;(2)改进Apriori_gen算法(3)减少事务数据库.在实验数据集上所做的实验结果表明SDA算法是有效的.  相似文献   

优化关联规则算法的方法研究     

潘雷 《南京晓庄学院学报》2005,21(5):71-76

Apriori算法是关联规则挖掘技术中的一个经典算法。笔者通过对该算法的思想和性能分析,认为它存在两方面的不足。本文提出了一种提高频繁项集挖掘算法效率的优化方法。实验表明,该优化算法对提高频繁项集挖掘算法的效率是有效的。  相似文献   

Apriori算法的改进算法设计与分析     

陈自力 《闽江学院学报》2011,32(2):38-40

提出采用事务压缩和哈希技术相结合方式的改进算法.该算法通过备份数据库Dk生成候选项目集Ck,在生成Ck的同时计算支持度.针对生成频繁2-项目集L2的瓶颈,在生成L2的时候使用DHP算法.从时间复杂度上对Apriori算法和改进算法进行比较,说明改进算法在效率上优于Apriori算法.  相似文献   

FARMER: A novel approach to file access correlation mining and evaluation reference model     

夏鹏  冯丹  王芳 《上海大学学报(英文版)》2011,15(6):574-588

File semantic has proven effective in optimizing large scale distributed file system. As a consequence of the elaborate and rich I/O interfaces between upper layer applications and file systems, file system can provide useful and insightful information about semantic. Hence, file semantic mining has become an increasingly important practice in both engineering and research community. Unfortunately, it is a challenge to exploit file semantic knowledge because a variety of factors could affect this information exploration process. Even worse, the challenges are exacerbated due to the intricate interdependency between these factors, and make it difficult to fully exploit the potentially important correlation among various semantic knowledges. This article proposes a file access correlation miming and evaluation reference (FARMER) model, where file is treated as a multivariate vector space, and each item within the vector corresponds a separate factor of the given file. The selection of factor depends on the application, examples of factors are file path, creator and executing program. If one particular factor occurs in both files, its value is non-zero. It is clear that the extent of inter-file relationships can be measured based on the likeness of their factor values in the semantic vectors. Benefit from this model, FARMER represents files as structured vectors of identifiers, and basic vector operations can be leveraged to quantify file correlation between two file vectors. FARMER model leverages linear regression model to estimate the strength of the relationship between file correlation and a set of influencing factors so that the “bad knowledge” can be filtered out. To demonstrate the ability of new FARMER model, FARMER is incorporated into a real large-scale object-based storage system as a case study to dynamically infer file correlations. In addition FARMER-enabled optimize service for metadata prefetching algorithm and object data layout algorithm is implemented. Experimental results show that is FARMER-enabled prefetching algorithm is shown to reduce the metadata operations latency by approximately 30%–40% when compared to a state-of-the-art metadata prefetching algorithm and a commonly used replacement policy.  相似文献