Data Mining and Causal Modeling of Customer Behaviors

This paper shows how to apply data-mining and modeling methods to learn predictive models of customer behaviors from survey and behavioral data. The models predict transition rates of individual customers among states, including product adds and drops and account attrition rates. A key insight is that classification tree algorithms from data mining can be used to test conditional independence (Cl) relations among variables in large multivariate data sets. This suggests constructive techniques for (a) Building causal graph models from data; and (b) Using data to define the states of a dynamic transition process. The resulting models can be used to help optimize product offers, forecast demand for products, and plan marketing campaigns. We use several real data sets to illustrate how to: (a) Develop predictive models from survey data and from billing data, (b) Validate model assumptions by using classification trees to identify and test conditional independence relations, (c) Evaluate model performance compared to other (e.g., logistic regression or discriminant analysis) models using cross-validation, and (d) Recommend the next logical product to offer to each customer and the best customers to target for each product in order to maximize sales.     

串联系统的备件配置方法

针对非指数分布串联系统的备件配置问题,首先根据指数分布的良好特性,建立指数分布串联系统的备件需求预测和配置模型;然后根据期望累积失效相等的原则,将非指数分布等效成指数分布。在此基础上,利用指数分布串联系统的备件模型近似地计算非指数分布串联系统的备件需求量。并以几种典型非指数分布的串联系统为例,如Weibull分布、正态分布和Gamma分布,分别给出了给定时间内的备件配置结果。通过Monte-Carlo模拟仿真,结果表明比实际略偏保守,且与经典方法相比,具有计算过程简单,预测时间更长与可操作性更强的优点,满足实际的保障要求,能够为工程应用带来方便。     

Linear and neural dynamic models: shared benefits between the industrial customer and the ESCo from the energy services' perspective

In this corrspondence, we investigate the application of linear and neurodynamic models to solve the critical problem of obtaining the most cost-effective electrical load forecast for an industrial site. This is done from the perspective of an energy service company (ESCo). The ESCos' business model is based on the notion of making money by providing a means to enable their commercial customers to lower their electric bills. This in turn is based on the idea that the energy supplier's cost of doing business is reduced if its commercial customers can provide a reliable load forecast. A portion of that cost savings is passed on to the user as a discount in the selling price. Since it is not cost effective for the customer to install extensive monitoring instrumentation, the load forecast must be made on the basis of a model that is determined by applying systems identification techniques to the user's consumption pattern. By a single-point observation of the electrical energy consumption in a dairy plant at quarter-hour intervals over a two-year period, we were able to identify a model and use it to devise a straightforward strategy for nontrivial cost savings to the user and a profitable line of service for the ESCo. The performance of several models is compared. The results for the weekly-based models are reported and the effective cost reduction along with the implementation time to set up the service package are quantified and verified in the proposed final business plan. The project produces overall revenues of roughly /spl euro/13 600 over a five-year contracting period.     

A non-homogeneous Markov model for phased-mission reliabilityanalysis

Three assumptions of Markov modeling for reliability of phased-mission systems that limit flexibility of representation are identified. The proposed generalization has the ability to represent state-dependent behavior, handle phases of random duration using globally time-dependent distributions of phase change time, and model globally time-dependent failure and repair rates. The approach is based on a single nonhomogeneous Markov model in which the concept of state transition is extended to include globally time-dependent phase changes. Phase change times are specified using nonoverlapping distributions with probability distribution functions that are zero outside assigned time intervals; the time intervals are ordered according to the phases. A comparison between a numerical solution of the model and simulation demonstrates that the numerical solution can be several times faster than simulation     

遗传算法在船舶转向避碰幅度决策中的应用研究

针对船舶避碰决策系统中的船舶运动趋势和避碰时机，应用遗传算法模型，实时预测各目标船相对于本船在下一时刻的运动参数，预估目标船相对于本船的最近会遇距离（DCPA）和最近会遇时间（TCPA）。同时，应用遗传算法模型预测避碰最优角度问题。仿真结果表明，该方法能有效提高船舶海上航行的灵活性和安全可靠性，达到提前预警和帮助驾驶员提前做好避碰准备等目的。     

Scenario analysis of demand in a technology market using leadingindicators

This paper proposes an approach to analyzing demand scenarios in technology-driven markets where product demands are volatile, but follow a few identifiable lifecycle patterns. After examining a large amount of semiconductor data, we found that not only can products be clustered by lifecycle patterns, but in each cluster there exists a leading indicator product that provides advanced indication of changes in demand trends. Motivated by this finding, we propose a scenario analysis structure in the context of stochastic programming. Specifically, the demand model that results from this approach provides a mechanism for building a scenario tree for semiconductor demand. Using the Bass growth model and a Bayesian update structure, the approach streamlines scenario analysis by focusing on parametric changes of the demand growth model over time. The Bayesian structure allows expert judgment to be incorporated into scenario generation while the Bass growth model allows an efficient representation of time varying demands. Further, by adjusting a likelihood threshold, the method generates scenario trees of different sizes and accuracy. This structure provides a practical scenario analysis method for manufacturing demand in a technology market. We demonstrate the applicability of this method using real semiconductor data     

Bandwidth Allocation Strategies in Wide-Band Integrated Networks

A common digital transmission facility in a wide-band integrated service digital network (ISDN) provides shared access to a community of heterogeneous users. Traffic demands from these users vary in their arrival rate, their service time, and their bit rate. In order for this type of communication system to handle its traffic demands with high efficiency and flexibility, a close control of access to the shared bandwidth is required. We model the system by a general multiserver queueing system where customers demand service from a random number of servers. If no waiting is allowed, this queueing model is readily analyzed, and various server allocation strategies can be studied. If the various access requests are queued for service, then the system calls for efficient strategies for allocating servers to waiting customers. In this case, exact analysis of the underlying queueing model becomes quite difficult. For this case, we present some analytic and simulation results of the performance of the system under several server allocation policies.     

基于小波分析的导弹装备备件需求组合预测

针对导弹装备备件需求呈现非线性、非平稳的特征,提出了把小波分析理论应用于导弹装备备件需求预测的构想.首先根据总体评价指标来确定小波最佳分解级数,将备件需求时间序列分解到不同尺度上以减少原始序列的随机性和波动性;然后对具有平稳特性的高频信息用改进动态自适应隔代映射遗传算法和阻尼最小二乘法优化的ARMA模型进行预测,而对反映整体趋势的低频信息用GM（1,1）模型进行预测;再将各模型的预测结果进行叠加,从而得到原始序列的预测值.最后通过导弹装备备件需求的实例,验证了本方法的有有效性和可行性.     

Routing protocol development for quality of service optimization of video‐on‐demand system over mobile ad hoc networks

A video‐on‐demand (VoD) application system over mobile ad hoc networks typically requires particular quality of service (QoS) parameters to be achieved. In this paper, we have proposed a novel QoS‐based routing protocol called as mobile VoD protocol. This protocol has been developed for improving the QoS of the mobile VoD system (normal Mobi_VoD approach). The protocol uses customer caching scheme for storing the first fragment of the entire video in the mobile customers and thereafter broadcast them when the new mobile customers missed the portion of the already transmitted first fragment for reducing the service delay of the customer, consequently optimizing QoS parameters. Various scenarios have been studied, and the efficacy of simulation results proves that the proposed system architecture in which the mobile customers use an ad hoc network caching scheme (mobile VoD protocol) is more efficient and performs better than the existing system (ad hoc on‐demand distance vector protocol) when compared in terms of QoS parameters such as the end‐to‐end delay, energy consumption, packet delivery ratio, throughput, and overhead.     

基于贝叶斯网络的移动业务客户流失预测研究

准确的客户流失预测能够使移动业务针对特定用户需求和消费水平进行差异化服务.本文提出了一种基于贝叶斯网络的客户流失预测模型,根据案例分析的结果识别客广1离网倾向原因,寻找具有高离网倾向的客户群,通过分类的特征分析,得出客户流失规则,并验证模型的有效性.     

MATHEMATICAL MODEL FOR ACCESS MODE OF CONTENTION－COLLISION CANCELLATION IN A STAR LAN

I type system model of CCCAM(Contention-Collision Cancellation Access Mode) is studied through mathematical modelling and simulation.There are two innovations:(1) in the process of mathematical modelling,the instance of ^4serving customers unsuccessfully‘ is taken into account;(2) the time at which customers depart after having been served successfully are chosen to be the embedded point,thereby “free period” is introduced reasonably.So the mathematical modelling and analysis result in this paper are significant for application of wire star LAN and wireless star LAN.     

基于BP网络的交通运输能力预测

交通运输能力预测是货运需求和经济发展关系研究中的一个重要问题,对货运量的预测研究和分析具有实际意义.在分析了货运量影响因素和预测特点的基础上,利用BP神经网络对货运量进行了预测.网络的输出和仿真结果证明了网络的有效性.     

Telecommunications Demand and Pricing Structure: An Econometric Analysis

The main objective of this paper is to analyse residential demand by traffic destination, using a translogarithmic indirect utility function. We focus on five traffic directions, in order to construct a model adapted to evaluate the characteristics of telecommunications demand in a competitive market. The resulting price elasticities express high reactivity to own price changes for the main traffic directions, as well as little interactions between the different types of traffic. Moreover, the high values of income elasticities confirm the importance of income effects when analysing residential telecommunications demand. This model shows useful for welfare analysis. The computation of customers' income equivalent variation shows, on average, a higher willingness to pay for some traffic directions than the bill actually paid. Finally, we show that the optimal prices for the operator, in a cost minimisation point of view, are higher than the observed prices for local and national traffic directions. This emphasises the existence of important cross-subsidies among the different segments of customers.     

基于仿真的备件需求量确定方法

准确的备件库存量预测是合理有效地进行备件保障等各项综合保障工作的基础。为了实现装备备件的精确化保障,提高保障效率,降低保障成本,介绍了一种根据部件的维修性、可靠性参数确定备件储备量的解析算法模型。基于Exspect平台实现了Petri网对一次任务的仿真算法,求出了备件储备量,并对不同的备件保障方案进行了对比,采用逐个对比的方法得出库存量的最优值。通过最后的计算实例,对仿真方法进行备件储备量确定的可行性进行了验证。     

离散时间闸门式多级门限服务的两级优先级轮询排队系统分析

本文提出了一种基于闸门式多级门限服务的两级优先级轮询系统.论文先构建了系统的排队分析模型,然后把模型中各个站点内的等待顾客数合起来设定为系统状态变量,对系统状态变量的概率母函数求二阶偏导后组成迭代方程组,联立求解后得到了站点的平均排队队长、顾客平均等待时间以及服务器查询周期等关键指标的完整数学解析表达式.最后,对该模型进行了仿真实验分析,实验结果与理论结果相一致.系统性能分析表明该轮询系统满足了周期性系统服务资源分配过程中业务多样性和弹性服务的发展需求,使得轮询控制策略应用方面更为广泛.     

Stationary characteristics of an M 2 X /M/n queue with hysteretic control of the input flow intensity

A multichannel queueing system with an unlimited queue length is considered. In the system, the service time and time intervals between arrivals of customer batches are characterized by exponential distributions and a hysteretic mechanism is applied to control the input flow intensity. The system receives two independent types of flows of customers one of which is blocked in the overload mode. An algorithm for determination of the stationary distribution of the number of customers and the stationary characteristics (the mean queue length, the mean time of waiting in the queue, the probability of a loss of customers) is proposed. The obtained results are verified with the help of a simulation model developed with the help of the GPSS World tools.     

数据挖掘技术在客户关系管理中的应用研究

在电子商务环境下,客户对企业起着至关重要的影响。新客户的获取无疑对企业的生存和发展起到很重要的作用。客户关系管理系统中,通过分析海量数据之间的联系,建立规范全面的信息模型。为了解决新客户的获取问题,采用数据挖掘技术对客户类别进行预测。通过对数据挖掘各种算法的比较,做了决策树算法编程实验,获得客户类别的预测结果。结果表明,数据挖掘技术能有效提高客户预测的准确率,提高了数据利用率。     

应用ABAQUS模拟激光焊接温度场

为了减小焊接变形,优化焊接工艺,需要准确预测激光焊接过程中温度场的分布情况,使用有限元模拟来预测温度场的分布是一种较好的方法.通过分析和总结激光焊接过程有限元模拟和理论分析的研究现状,以平板的焊接为例,建立了物理模型,并利用ABAQUS进行了激光焊接三维温度场的有限元模拟,讨论了模型的网格划分、边界条件及其模拟结果的后处理.模拟结果可以给出试件上任意一点任意时刻的温度情况,在激光功率为2000W、焊接速度为20mm/s的参数下模拟焊接2mm厚的A3钢板.结果表明,最高温度为3100℃左右,距焊接中心横向mm处A点的最高温度为150℃左右,与相同参数条件下的实验结果基本一致,说明有限元模拟可以准确预测焊接过程的温度场分布情况.     

ARCH-Based Traffic Forecasting and Dynamic Bandwidth Provisioning for Periodically Measured Nonstationary Traffic

Network providers are often interested in providing dynamically provisioned bandwidth to customers based on periodically measured nonstationary traffic while meeting service level agreements (SLAs). In this paper, we propose a dynamic bandwidth provisioning framework for such a situation. In order to have a good sense of nonstationary periodically measured traffic data, measurements were first collected over a period of three weeks excluding the weekends in three different months from an Internet access link. To characterize the traffic data rate dynamics of these data sets, we develop a seasonal autoregressive conditional heteroskedasticity (ARCH) based model with the innovation process (disturbances) generalized to the class of heavy-tailed distributions. We observed a strong empirical evidence for the proposed model. Based on the ARCH-model, we present a probability-hop forecasting algorithm, an augmented forecast mechanism using the confidence-bounds of the mean forecast value from the conditional forecast distribution. For bandwidth estimation, we present different bandwidth provisioning schemes that allocate or deallocate the bandwidth based on the traffic forecast generated by our forecasting algorithm. These provisioning schemes are developed to allow trade off between the underprovisioning and the utilization, while addressing the overhead cost of updating bandwidth. Based on extensive studies with three different data sets, we have found that our approach provides a robust dynamic bandwidth provisioning framework for real-world periodically measured nonstationary traffic.     

Control-Relevant Demand Forecasting for Tactical Decision-Making in Semiconductor Manufacturing Supply Chain Management

Forecasting highly uncertain demand signals is an important component for successfully managing inventory in semiconductor supply chains. We present a control-relevant approach to the problem that tailors a forecasting model to its end-use purpose, which is to provide forecast signals for a tactical inventory management policy based on model predictive control (MPC). The success of the method hinges on a control-relevant prefiltering operation applied to demand estimation data that emphasizes a goodness-of-fit in regions of time and frequency most important for achieving desired levels of closed-loop performance. A multiobjective formulation is presented that allows the supply-chain planner to generate demand forecasts that minimize inventory deviation, starts change variance, or their weighted combination when incorporated in an MPC decision policy. The benefits obtained from this procedure are demonstrated on a case study drawn from the final stage of a semiconductor manufacturing supply chain.