电子商务客户流失的DBN预测模型研究

在电子商务迅速发展,企业快速抢占市场的背景下,客户成为企业竞争的核心因素。现有相关研究多致力于采用全数据输入模式解析客户流失现象,不同类型客户造成的差异性还有待进一步探讨。鉴于传统RFM模型不能精确解释电子商务客户流失原因,该研究将客户分为活跃与非活跃两个集群,提出一种优化的RFM理论模型与深度信念网络实证模型对电子商务客户流失进行预测。结果表明,不同类型客户流失因素的影响强度不同。对活跃用户而言,客户购买总金额是影响客户流失的主要因素;对非活跃用户而言,客户进入店铺的时间越长越可能留住客户。通过剖析非活跃用户不流失和活跃用户流失的原因,可帮助企业制定有效的客户管理策略,以最大程度地吸引潜在客户及保留现有客户,获取最多的市场利益。     

基于分步特征提取和组合分类器的电信客户流失预测模型

针对电信客户流失数据集存在的数据维度过高及单一分类器预测效果较弱的问题,结合过滤式和封装式特征选择方法的优点及组合分类器的较高预测能力,提出了一种基于Fisher比率与预测风险准则的分步特征选择方法结合组合分类器的电信客户流失预测模型。首先,基于Fisher比率从原始特征集合中提取具有较高判别能力的特征;其次,采用预测风险准则进一步选取对分类模型预测效果影响较大的特征;最后,构建基于平均概率输出和加权概率输出的组合分类器,以进一步提高客户流失预测效果。实验结果表明,相对于单步特征提取和单分类器模型,该方法能够提高对客户流失预测的效果。     

电子商务客户流失的建模与预测研究

研究电子商务客户流失预测问题,电子商务客户流失具有非线性、时变等特点,用单一预测模型难以对电子商务客户流失变化规律进行全面、准确预测,导致预测正确率低。为了提高电子商务客户流失预测正确率,提出一种组合的电子商务客户流失预测模型。组合预测模型首先采用遗传算法对影响客户流失因子进行筛选,提取对预测结果影响重要的因子,然后分别采用支持向量机和神经网络对其进行预测,最后采用支持向量机对两种预测结果进行融合,得到组合模型的电子商务客户流失预测结果。仿真结果表明,组合模型提高了电子商务客户流失预测正确率,解决了单一预测模型的缺陷,将为电子商务客户流失研究提供一种新预测思路。     

基于灰色关联度和K-Means++的电子商务客户价值分类

现有的模型大多采用RFM模型和K-means对客户价值进行分类,对指标权重的确定大多采用AHP法,没有考虑到RFM模型指标相互之间的联系.首先根据RFM模型选择平均购买时间间隔,客户在一定时间内的购买频率,平均每笔订单交易金额和客户的活跃时间构造RFMT模型来衡量客户价值.其次使用灰色关联度确定各指标权重.最后针对K-means的缺点,运用改进K-means （K-means++）和肘部法则对RFMT模型进行聚类分析.该模型能对客户群进行更加细致的划分,既能帮助电子商务企业识别出需要重点关注的客户即已流失客户和新客户群体,同时将该企业客户划分为价值由高到低的客户群,对不同客户群提出具体的营销建议.     

基于原型的EM朴素贝叶斯模型在直接营销中的应用

针对连锁型零售企业直接营销中的问题,基于原型理论的挖掘模型选择方法,提出基于EM聚类朴素贝叶斯模型,通过实验证明了该模型在客户购买行为的预测性能上明显优于基于K-means聚类朴素贝叶斯模型和无聚类的朴素贝叶斯模型。最后,利用该模型检验了直接营销中的对新客户进行分类预测的有效性。     

基于组合预测的电信客户流失预测

利用数据挖掘技术,对电信行业客户信息进行了分析,对用户进行关联、分类、聚类分析,给出了解决问题的模型和方法并在实践中得到评估和检验,本文提出了一种基于组合预测理论的预测算法,在实际客户流失预测分析的应用结果表明,该算法的流失预测的准确率高于传统的分类预测算法所得到的预测准确率.构建的预测模型对解决电信客户流失预测方面的问题具有应用价值.     

利用ClementineC5.0模型预测CDMA客户流失

该文针对目前电信行业中一个日益严峻的问题:客户离网进行研究,通过收集客户的基本数据、消费数据和缴费行为等数据,建立客户流失预测模型,进行客户流失分析及预测.通过对大量相关技术和统计方法的研究,最终确定了clementine的C5.0模型作为电信客户流失的预测模型.此模型对客户流失预测有较高的准确性,为电信经营分析系统作...     

基于决策树的证券客户流失模型

描述了证券业客户流失分析的重要性,客户流失的定义,提出了影响客户流失的各种特征因素.然后根据CRM中的RFM模型,加入客户收益率指标,提出了证券行业客户流失分析的RFM-ROI模型.用决策树方法构建了客户流失分析模型,并提出了解决决策树剪枝问题的停止阈值方法.结果表明该模型能达到80.7%的准确率,具有较强的实用性.     

客户流失预测数据挖掘方法对比分析

本文分析了用于客户流失预测建模的主流技术及其优缺点。探讨了客户流失预测模型的研究方向．最后提出了云模型在客户流失预测中的应用。     

基于RFM模型的随机森林算法对民航客户的流失分析

近几年,随着航空市场的快速发展,对于航空公司而言,如何在增加市场占有率的同时,对客户的流失进行有效的控制也刻不容缓。基于随机森林算法,根据航空客户数据,建立流失预测模型,对客户是否已流失进行预测研究,将传统的RFM客户价值模型进行改进,结合随机森林算法对客户流失进行预测。实验结果表明,基于RFM模型的随机森林算法构建的客户流失模型拥有更具有说服力的指标选取,AUC值达到0.92,且准确率较高。利用该模型可对航空公司客户流失进行较为准确的预测,对流失客户进行分类,为民航企业提供营销策略。     

GSTE is partitioned model checking

Verifying whether an ω-regular property is satisfied by a finite-state system is a core problem in model checking. Standard techniques build an automaton with the complementary language, compute its product with the system, and then check for emptiness. Generalized symbolic trajectory evaluation (GSTE) has been recently proposed as an alternative approach, extending the computationally efficient symbolic trajectory evaluation (STE) to general ω-regular properties. In this paper, we show that the GSTE algorithms are essentially a partitioned version of standard symbolic model-checking (SMC) algorithms, where the partitioning is driven by the property under verification. We export this technique of property-driven partitioning to SMC and show that it typically does speed up SMC algorithms. A shorter version of this paper has been presented at CAV’04 (R. Sebastiani et al., Lecture Notes in Comput. Sci., vol. 3114, pp. 143–160, 2004). R. Sebastiani supported in part by the CALCULEMUS! IHP-RTN EC project, code HPRN-CT-2000-00102, by a MIUR COFIN02 project, code 2002097822_003, and by a grant from the Intel Corporation. M.Y. Vardi supported in part by NSF grants CCR-9988322, CCR-0124077, CCR-0311326, IIS-9908435, IIS-9978135, EIA-0086264, and ANI-0216467 by BSF grant 9800096, and by a grant from the Intel Corporation.     

Formal approach to fault diagnosis in distributed discrete event systems with OBDD

In this paper, we study the fault diagnosis problem for distributed discrete event systems. The model assumes that the system is composed of distributed components which are modeled in labeled Petri nets and interact with each other via sets of common resources (places). Further, a component’s own access to a common resource is an observable event. Based on the diagnoser approach proposed by Sampath et al., a distributed fault diagnosis algorithm with communication is presented. The distributed algorithm assumes that the local diagnosis process can exchange messages upon the occurrence of observable events. We prove the distributed diagnosis algorithm is correct in the sense that it recovers the same diagnostic information as the centralized diagnosis algorithm. Furthermore, we introduce the ordered binary decision diagrams (OBDD) in order to manage the state explosion problem in state estimation of the system.     

面向安全攸关系统中小概率事件的统计模型检测

在开放运行环境中,安全攸关系统的不确定性行为有可能导致小概率事件的发生,而此类事件的可靠性指标往往很高,小概率事件一旦发生就会产生灾难性的后果,严重威胁到人们的生命、财产安全.因此,评估、预测小概率事件发生的概率,对于提高系统的可靠性具有重要意义.统计模型检测是一种基于模拟的模型验证技术,结合了系统的快速模拟及统计分析技术,能够有效提高模型检测的效率,适用于验证、评估安全攸关系统的可靠性,但其面临的挑战性问题之一是在可接受的样本数量下,使用统计模型检测技术难以预测、评估小概率事件发生的概率.因此,提出一种改进的统计模型检测框架,设计和开发基于机器学习的统计模型检测器,实现在相对较少的样本数量下预测和评估小概率事件发生的概率.结合轨道交通控制系统中避碰控制案例分析,进一步证明改进后的统计模型检测器能够有效预测和评估安全攸关系统中小概率事件发生的概率.     

一种完整的非对称公钥叛逆者追踪方案的密码学分析与改进

王青龙等人提出了一种完整的非对称公钥叛逆者追踪方案,并称该方案具有完善的撤销性和更高的传输效率等优点。对此进行详细分析发现它存在明显缺陷,提出一种攻击方案,使得叛逆者可以进行共谋攻击,但是管理者却无法使用黑盒叛逆者追踪方法对它们进行追踪。最后提出一种改进方案,在改进方案中,叛逆者虽然仍能实施上面提到的攻击,但是会被追踪者追踪到。     

Haplotype inference using a novel binary particle swarm optimization algorithm

The knowledge of haplotypes allows researchers to identify the genetic variation affecting phenotypic such as health, disease and response to drugs. However, getting haplotype data by experimental methods is both time-consuming and expensive. Haplotype inference (HI) from the genotypes is a challenging problem in the genetics domain. There are several models for inferring haplotypes from genotypes, and one of the models is known as haplotype inference by pure parsimony (HIPP) which aims to minimize the number of distinct haplotypes used. The HIPP was proved to be an NP-hard problem. In this paper, a novel binary particle swarm optimization (BPSO) is proposed to solve the HIPP problem. The algorithm was tested on variety of simulated and real data sets, and compared with some current methods. The results showed that the method proposed in this paper can obtain the optimal solutions in most of the cases, i.e., it is a potentially powerful method for HIPP.     

An improved semantically-secure identity-based signcryption scheme in the standard model

Recently, Yu et al. proposed the first identity-based signcryption scheme without random oracles and proved it was semantically secure in the standard model. However, in this paper we find that their scheme actually does not reach the semantic security as they claimed. To make up for this defect, we propose a rescue scheme and show our improvement is really secure in the standard model based on the intractability of the Decisional Bilinear Diffie-Hellman assumption.     

Nonlinear system modeling and predictive control using the RBF nets-based quasi-linear ARX model

On the basis of the single-input single-output (SISO) RBF-ARX model proposed in previous works [Peng, H., et al. (2003b). Stability analysis of the RBF-ARX model based nonlinear predictive control. In Proceedings of the ECC2003; Peng, H., et al. (2003c). Modeling and control of nonlinear nitrogen oxide decomposition process. In Proceedings of the CDC’03; Peng, H., et al. (2004). RBF-ARX model based nonlinear system modeling and predictive control with application to a NO_x decomposition process. Control Engineering Practice, 12, 191–203; Peng, H., et al. (2007). Nonlinear predictive control using neural nets-based local linearization ARX model—Stability and industrial application. IEEE Transactions on Control Systems Technology, 15, 130–143] the multi-input multi-output (MIMO) RBF-ARX model and its state-space representation are derived to describe the dynamics of a class of multivariable nonlinear systems whose working-point varies with time and which may be linearized around the working-point. The proposed MIMO RBF-ARX model has a basic regression-model structure that is analogous to the linear ARX model structure, and the elements of its regression matrices are composed of Gaussian radial basis function (RBF) neural networks that are dependent on the working-point state of the current system. An off-line estimation approach to parameters and orders of the MIMO RBF-ARX model is presented, and, on the basis of the estimated MIMO RBF-ARX model, a predictive control strategy is designed to control the underlying nonlinear system. A case study on a simulator of a thermal power plant is also given to illustrate the effectiveness of the nonlinear modeling and control method proposed in this paper.     

Efficient online schedulability tests for real-time systems

Many computer systems, such as those for open system environments or multimedia services, need an efficient schedulability test for online admission control of new jobs. Although various polynomial time schedulability tests have been proposed, they often fail to decide the schedulability of the system precisely when the system is heavily loaded. On the other hand, most precise schedulability tests proposed to date have a high complexity and may not be suitable for online tests. We present new efficient online schedulability tests for both the periodic process model [C. L. Liu et al., (1973)] and the multiframe process model [A. K. Mok et al., (1997)] in uniprocessor environments. The schedulability tests are shown to be more precise and efficient than any existing polynomial-time schedulability tests. Moreover, the tests can be done incrementally as each new task arrives at the system. Our proposed tests can also be used for the multiframe model where a task may have different computation times in different periods. We show the performance of the proposed schedulability tests in several simulation experiments.     

一种多重数字签名方案的安全性分析

Lu等人指出Harn的多重数字签名方案和Ji等人的多重数字签名方案存在一个共同的缺点,即部分成员在生成密钥时合谋作弊,就能达到事后否认的目的,并对这两个多重数字签名方案提出了改进方案。本文〖BP）〗对文献[3]的改进方案进行了分析,并提出了新的多重数字签名方案。新方案不仅能抵抗合谋作弊攻击,而且还具有前向安全特性,即使所有签名人的签名密钥被泄露,曾经产生的多重数字签名依然有效。     

代理盲签名和多重代理盲签名的安全性分析

王国瞻等人(计算机工程,2010年第3期和第8期)分别对谷利泽等人提出的代理盲签名方案和Lu等人提出的多重代理盲签名方案进行攻击,指出这2个方案不满足盲性。针对王国瞻等人对谷利泽等人和Lu等人方案的可追踪性攻击问 题,指出王国瞻等人的攻击是无效的,并采用构造方法证明代理签名人不能根据已有的信息追踪到签名。分析结果证明,王国瞻等人的攻击无效,谷利泽等人的方案和Lu等人的方案仍然满足盲性,是不可追踪的。