IMS 中基于策略QoS 管理模型

IMS（IP多媒体子系统）给客户带来丰富的多媒体体验的同时,也对服务质量（QoS）管理提出了更高的要求,即针对不同用户定制的不同服务,网络运营商应该制定差异化的策略进行QoS管理。3GPP定义了基于策略的QoS管理框架,但这个框架只是逻辑上的架构,没有定义具体物理实施的方案。对基于策略QoS管理模型进行了分析,在参照3GPP定义的标准基础上,提出了一种管理模型的实现方案,设计并实现了该模型中两个关键服务器策略决策服务器（PDF）和策略执行服务器（PEP）。经过测试,两个服务器能互相配合,正确完成查询策略信息,做出策略决策,执行带宽请求预留、QoS等级协商功能,为网络运营商提供了参考。     

电信资费优惠规则知识表示、冲突检测与实现研究

目前电信运营商资费优惠规则（俗称套餐）采用自然语言来描述,不仅容易产生歧义而且不能用计算机来进行重复套餐的自动冲突检测。针对重复套餐增多致使业务支撑系统（BSS）不堪重负而出现效率低下甚至宕机的现象,运用人工智能知识表示的方法将电信资费每条优惠规则表示为条件部分和结论部分,采用当前有代表性的冲突检测算法Rete算法和Rete改进算法的思想,提出了优惠规则冲突检测算法,与专家平台相结合,实现了优惠规则的自动化冲突检测。最后通过实例验证了优惠规则知识表示和冲突检测算法的合理性和有效性,在优惠规则的科学设置、减少客户投诉、压缩优惠规则数量、提高系统效率和增加经济效益与社会效益等方面都取得了较好的效果。     

一种基于灵活市场的区分服务网络定价策略

基于区分服务的网络模型,提出了一种新的灵活市场的定价策略。为了使定价策略能够更好地应用在区分服务网络中,在边界路由器中使用了探测和反馈机制,并且对灵活市场定价策略中的竞标值进行了归一化处理。通过仿真实验验证了基于区分服务模型的灵活市场定价策略的自适应性。     

电信运营商前台客户感知提升策略

随着移动互联网的飞速发展,客户使用行为发生了巨大的变化,流量和终端消费给全球电信业带来新增长的 同时也给运营商营业厅服务带来了新挑战。本文基于实践经验,对电信运营商营业厅前台客户感知提升策略进行了研究,并 取得了良好的效果。     

OSS的台前幕后

电信行业“以客户为中心”的本质是向客户提供灵活的、多样的、个性化的服务,这要求电信运营商建立一个多业务的统一视窗,做到数据的集中化、中心化。这就是OSS智能服务的价值所在     

基于属性的访问控制策略合成代数

访问控制策略合成是确定分布式聚合资源访问控制策略的关键.为了规范策略合成和保障策略合成正确性,基于属性刻画了实体间的授权关系,通过属性值的计算结构扩展了现有的策略合成形式化框架,建立了新的基于属性的策略合成代数模型APoCA(attribute-base access control policy composition algebra).通过示例分析说明APoCA具有更强的策略合成描述能力和普适性,适应于更为复杂的应用场景.用代数表达式形式化地描述聚合资源的访问控制策略,讨论了策略表达式的若干代数性质,说明可借助策略表达式的代数性质去验证策略合成结果是否符合各方对聚合资源的保护性需求.给出了将代数表达式翻译成逻辑程序的翻译器,为聚合资源的访问控制策略评估和应用提供基础.     

一种多模态信息融合的视频检索模型

针对包含复杂语义信息的视频检索的需要,提出了一种基于关系代数的多模态信息融合视频检索模型,该模型充分利用视频包含的文本、图像、高层语义概念等多模态特征,构造了对应于多个视频特征的查询模块,并创新地使用关系代数表达式对查询得到的多模态信息进行融合。实验表明,该模型能够充分发挥多模型视频检索及基于关系代数表达式的融合策略在复杂语义视频检索中的优势,得到较好的查询结果。     

基于产品3D模型点击流的客户行为分析

将Web服务日志进行扩展，以基于Web的产品3D模型浏览的操作日志和客户基本信息作为源数据，建立了客户操作模型，采用FP-growth关联规则分析方法，挖掘客户对产品及产品系列的兴趣度，为企业制定相应的产品开发策略和市场营销策略提供决策支持。     

基于属性和规则的访问控制模型

针对分布式服务环境中用户数目大量增长和资源访问策略复杂多样化的问题,分析目前访问控制模型的应用局限性,提出多用户服务模式中一种基于属性和规则的访问控制模型。该模型引入复合属性表达式和复合权限的概念,制定授权约束规则,为用户分配多组角色。给出模型实例,并将其与其他模型进行比较。     

OWL-S模型转化为重写逻辑模型的方法

OWL-S模型在基于服务的软件设计中具有重要作用,但由于其非完全形式化的模型,不能直接对其进行形式化分析与验证。基于OWL-S模型的重写逻辑语义框架,通过对数据类型、表达式、控制结构与Process的转换,设计并实现了OWL-S模型到重写逻辑模型的自动转化工具,为能够在软件实现前为设计模型的形式化分析与验证,以及可靠性分析提供基础。     

基于价格折扣的有条件延期支付策略

在延期支付及价格折扣策略下,建立以供货商为主导的主从斯坦伯格模型,从供货商的角度研究基于价格折扣的有条件延期支付策略设置问题.通过对模型的理论分析和模型求解,给出了各情形下供货商的延期支付策略、零售商的最佳订单量和货款的最佳支付时间.数值结果表明,此策略在激励零售商加大订单量的同时,还能吸引其尽早交付货款,从而加快供货商的资金周转,实现双赢.     

A multi-objective quantity discount and joint optimization model for coordination of a single-buyer multi-vendor supply chain

Supply chain management is concerned with the coordination of different parts of the production system. Companies have realized that they must closely collaborate with the suppliers of their strategic components or products. Recently, developing integrated inventory models for the supplier selection problem has attracted a significant amount of attention amongst researchers. In these models some incentives are required from the vendors to motivate the buyer to change his (her) policies to the policy which is optimal for the entire system. Quantity discount policies are used as common incentives in the literature. However, the literature on this problem does not incorporate quantity discount into the coordination model. This paper develops a multi-objective mixed integer nonlinear programming model to coordinate the system of a single buyer and multiple vendors under an all-unit quantity discount policy for the vendors. Due to the complexity of the problem two well known meta-heuristic algorithms are proposed to solve the problem. An illustrative example is given to show the behavior of the model. Results obtained from solving the sample problems show good performance of the proposed algorithms in finding the optimal solutions.     

Buyer's optimal ordering policy and payment policy under supplier credit

This paper tries to incorporate previous studies to develop the buyer's inventory model. That is, we want to investigate the buyer's optimal cycle time and optimal payment time under the supplier's trade credit policy and cash-discount policy. Mathematical models have been derived for obtaining the optimal cycle time and optimal payment time for item under the supplier's trade credit and cash discount so that the annual total relevant cost is minimized. Furthermore, numerical examples are given to illustrate the results developed in this paper and to yield managerial implications.     

Joint replenishment policy with backordering and special sale

In this paper, an inventory control model with a joint replenishment policy and a temporary discount is developed. We assume that shortage is allowed and buyer uses an economic order quantity inventory control model. Different cases based on ordering policies for the first joint replenishment if the special order is not taken, and coincidence of a special period length with a positive or negative inventory level of the last regular period length, are investigated. Furthermore, several theorems are proved through which closed-form solutions are obtained. At the end, two numerical examples illustrate the different situations that the buyer may face and sensitivity analyses for both examples are reported.     

Unified discount pricing models of a two-echelon channel with a monopolistic manufacturer and heterogeneous retailers

This paper considers a two‐echelon channel in which a monopolistic manufacturer supplies a single product to multiple heterogeneous retailers who are in separate markets. The present paper studies the problem of how the manufacturer in a manufacturer‐Stackelberg game designs a unified quantity‐discount pricing scheme to improve the whole channel's profit as well as each partner's profit. Considered in the paper are two types of unified quantity‐discount pricing schemes: the regular quantity‐discount pricing scheme and the incremental volume discount pricing scheme. Each of the two types of schemes includes a single price‐break discount policy and a non‐linear quantity discount policy. Optimal solutions are derived and numerical examples presented to illustrate the efficiency of each discount policy.     

Joint replenishment with imperfect items and price discount

A joint replenishment problem is presented to determine the ordering policy for multiple items having a certain percentage of defective units. The purpose of this paper is to study the impact of the percentage of defective units on the ordering policy. Two different scenarios are presented for joint replenishment problem: (1) without price discount and (2) with price discount. For each scenario, the total expected cost per unit time is derived and algorithms are presented to determine the family cycle length and the integer number of intervals that the replenishment quantity of each item will last. Numerical examples are presented and the results are discussed.     

Credibility decay model in temporal evidence combination

Data fusion in time domain is sequential and dynamic. Methods to deal with evidence conflict in spatial domain may not suitable in temporal domain. It is significant to determine the dynamic credibility of evidence in time domain. The Markovian requirement of time domain fusion is analyzed based on Dempster's combination rule and evidence discount theory. And the credibility decay model is presented to get the dynamic evidence credibility. Then the evidence is discounted by dynamic discount factor. It's illustrated that such model can satisfied the requirement of data fusion in time domain. Proper and solid decision can be made by this approach.     

基于灰色神经网络的航线客流量预测

准确预测航线客流量对于航空公司制定航线销售政策有着重要的作用。现有研究中鲜见考虑民航旅客出行的随机性、客流量表现出的非线性特征以及对航线客流量影响因素的分析。针对以上问题,提出一种基于灰色神经网络的航线客流量预测模型。该模型运用灰色理论弱化数据序列的随机性,再结合非线性处理能力较强的BP神经网络,构建基于灰色神经网络的航线客流量预测模型。同时验证了平均折扣率对航线客流量的影响。实验结果表明,相比于灰色GM(1,2)模型、BP神经网络模型,灰色神经网络模型具有更高的航线客流量预测精度和更强的稳定性。     

基于深度强化学习的动态装配算法

针对动态装配环境中存在的复杂、动态的噪声扰动,提出一种基于深度强化学习的动态装配算法。将一段时间内的接触力作为状态,通过长短时记忆网络进行运动特征提取;定义序列贴现因子,对之前时刻的分奖励进行加权得到当前时刻的奖励值;模型输出的动作为笛卡尔空间位移,使用逆运动学调整机器人到达期望位置。与此同时,提出一种对带有资格迹的时序差分算法改进的神经网络参数更新方法,可缩短模型训练时间。在实验部分,首先在圆孔–轴的简单环境中进行预训练,随后在真实场景下继续训练。实验证明提出的方法可以很好地适应动态装配任务中柔性、动态的装配环境。