The thesis introduces some ANN design algorithms, which are BP algorithm, FP algorithm, alternative covering design algorithm of multi-layer neural networks.
文中介绍了目前使用的几种不同的人工神经网络设计算法：BP算法、FP算法、多层前向网络的交叉覆盖设计算法。
Moreover, we take dimension into account in our E-FP algorithm. We show that our E-FP algorithm is more flexible at capturing desired knowledge than previous studies.
实验证明我们的E-FP算法比以往的算法更适合于多层高维频繁序列的挖掘。
Secondly, based on the defined priority principle of Fault Prediction and using the Fault Prediction allowance value set got by weighted algorithm, a sequential graph of FP is designed.
然后在定义了故障预测的优先原则的基础上，利用专家系统加权算法得到的故障预测容许值集合，设计了故障预测的流程图；
Peculiarity association rule mining algorithm RSFPA based on FP-tree is presented by using FP-tree idea oriented association rule miming.
运用面向关联规则的FP树构造方法，提出了一种特异关联规则挖掘算法rsfpa。
Finally, valuable decision-making information is discovered by using the parallel algorithm based on FP-growth while mining the association rules of online transactions.
利用该算法对网上交易进行关联规则挖掘，发现了有价值的决策支持信息。
This paper proposes a new algorithm for mining association rules with composite items based on the FP-growth algorithm.
文章基于FP-增长算法提出了一种新的挖掘复合项关联规则的算法。
To make further improvement on the scalability of the algorithm, we make a further study on the pattern tree, and propose a new algorithm called FP-DFS based on the study.
该算法通过对模式树的各种操作简化了对频繁项集的搜索过程。
Compared with Apriori algorithm and FP-growth algorithm, Combination Tree algorithm has better efficiency.
与Apriori算法和FP - growth算法相比，该算法具有更好的效率。
This paper presents a new algorithm for distributed mining association rules with item constraints called DAMICFP, which is based on a new type algorithm for association rule mining, FP-growth.
在分布式环境中挖掘约束性关联规则是当前研究的热点问题之一。
This paper presents a new algorithm for distributed mining association rules with item constraints called DAMICFP, which is based on a new type algorithm for association rule mining, FP-growth.
在分布式环境中挖掘约束性关联规则是当前研究的热点问题之一。
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