基于多维博弈的废旧汽车回收物流经营策略研究

以废旧汽车为例,运用多维度博弈理论建立了两家汽车生产商在不完全信息条件下的销售和利润静态模型,分别对两家汽车生产商在产品效益、回收物流投入和价格策略三个方面进行博弈分析,用求导的方法分解了权衡考虑产品效益、回收物流投入和价格策略三方面时的最优经营策略。结果表明,企业只有在综合考虑多方面的情况下才能实现利润的最大化,而且在回收物流方面的投入也具有重要的意义,该理论研究方法对企业的实际操作业也具有很重要的现实意义。

基于动态多维博弈模型的物流企业经营策略研究

以物流企业为例,运用多维度的动态博弈理论建立了两家物流企业在不完全信息条件下的销售和利润静态模型,分别对两家物流企业在物流硬件条件建设投入、服务质量策略和价格策略三方面进行了博弈分析,通过对目标函数求导的方法求解了权衡考虑物流硬件条件建设投入、服务质量策略和价格策略三方面时的最优经营策略。结果证明,企业只有在综合考虑多方面的情况下才能实现利润的最大化,特别是在服务质量方面的投入具有很重要的意义。

极点极线背景试题的计算策略

以极点极线为背景的试题计算困难.本文总结了解决此类问题的五种计算策略:设线策略、设点策略、向量策略、几何策略、曲线系策略.其中设线策略中又分为同构方程策略、非对称式消元策略、非对称式对称化策略.

广告和服务投入及价格选择的多维博弈分析

根据现代企业在市场竞争中的特点,建立了2个企业在市场上同时进行产品广告、服务和产品价格选择的多维博弈模型,并求得其均衡解.对均衡解的分析表明,企业确定产品广告和服务投入以及价格选择时,应从上述3方面综合考虑,选择最优的策略向量,以使企业的利润最大化.

基于Stackelberg动态多维博弈对企业竞争的分析与调控

针对企业在社会主义市场经济中的激烈竞争,建立多维Stackelberg动态博弈模型,对不同时期进入市场的企业进行最优化策略求解,根据在不同的博弈模型中所得出的Nash均衡结果对各类型企业提出相应的合理化建议。从模型的收益结果可以看出,先进入市场的企业具有"先动优势",后入的企业只得被动跟随,因此提高企业的自主创新能力和开拓新的生产领域是抢夺市场先机、获得丰厚回报的最佳选择。

基于SVM的人脸识别系统的研究

该文使用PCA来提取人脸的特征,克服了K-L算法计算量大,计算耗时长的缺点。实验表明该算法减少了特征提取时间。然后运用SVM来进行人脸识别。将两类分类问题的识别策略应用到多类分类问题。

Chinese multi-document personal name disambiguation

This paper presents a new approach to determining whether an interested personal name across doeuments refers to the same entity. Firstly,three vectors for each text are formed： the personal name Boolean vectors denoting whether a personal name occurs the text the biographical word Boolean vector representing title, occupation and so forth, and the feature vector with real values. Then, by combining a heuristic strategy based on Boolean vectors with an agglomeratie clustering algorithm based on feature vectors, it seeks to resolve multi-document personal name coreference. Experimental results show that this approach achieves a good performance by testing on ＂Wang Gang＂ corpus.

Strategic group theory： A customer-oriented view

Barney and Hoskisson （1990） argue that the strategic group research has neither established the existence of strategic groups, nor their relationship to firm performance. The primary reason behind the unsatisfactory results is the lack of a theoretical framework： what strategic variables to include in the analysis and their relative importance; the definition of an industry, and how to make competitive strategy operational. First, the author presents a customer-oriented theory of management which submits that, like Procter and Gamble, understanding customers should be the primary focus of a business. Second, the author proposes an integrated approach to competitive strategy. Because customer-perceived quality is far more critical to long-term success than any other factor, it should be the centerpiece of competitive strategy. The author suggests that competitive strategy should be divided in two interdependent dimensions： external and internal. It is the external strategy that should be considered the primary dimension because it reflects the customers＇ perspective, and provides a sense of direction regarding how the internal resources should be used. Next, the author presents an operational framework of competitive strategy which proposes that the best route to market share leadership in consumer markets is competing in the mid-price segment, offering superior quality compared to competition at a somewhat higher price： （1） to maintain an image of quality, and （2） to ensure that the strategy is profitable and sustainable. Finally, the author offers a framework of business or industry definition that extends Abell＇s （1980） three dimensions to seven. He suggests that an integrated approach to market segmentation provides the foundation for conducting strategic group analysis in consumer markets. So, in strategic group research, we need a bottom-up approach that begins with a product-market segment. In each product market, real competition occurs at the brand level. This is the ground where actual competitive wars are fought, and this is where the rich dynamics of competition often come to light.

An Optimal Control Strategy Combining SVM with RGA for Improving Fermentation Titer

An optimal control strategy is proposed to improve the fermentation titer,which combines the support vector machine(SVM)with real code genetic algorithm(RGA).A prediction model is established with SVM for penicillin fermentation processes,and it is used in RGA for fitting function.A control pattern is proposed to overcome the coupling problem of fermentation parameters,which describes the overall production condition.Experimental results show that the optimal control strategy improves the penicillin titer of the fermentation process by 22.88%,compared with the routine operation.

MAVP-FE:Multi-Authority Vector Policy Functional Encryption with Efficient Encryption and Decryption

In cloud,data access control is a crucial way to ensure data security.Functional encryption(FE) is a novel cryptographic primitive supporting fine-grained access control of encrypted data in cloud.In FE,every ciphertext is specified with an access policy,a decryptor can access the data if and only if his secret key matches with the access policy.However,the FE cannot be directly applied to construct access control scheme due to the exposure of the access policy which may contain sensitive information.In this paper,we deal with the policy privacy issue and present a mechanism named multi-authority vector policy(MAVP) which provides hidden and expressive access policy for FE.Firstly,each access policy is encoded as a matrix and decryptors can only obtain the matched result from the matrix in MAVP.Then,we design a novel function encryption scheme based on the multi-authority spatial policy(MAVPFE),which can support privacy-preserving yet non-monotone access policy.Moreover,we greatly improve the efficiency of encryption and decryption in MAVP-FE by shifting the major computation of clients to the outsourced server.Finally,the security and performance analysis show that our MAVP-FE is secure and efficient in practice.

Seat inventory control methods for Chinese passenger railways

Railway seat inventory control strategies play a crucial role in the growth of profit and train load factor. The railway passenger seat inventory control problem in China was addressed. Chinese passenger railway operation features and seat inventory control practice were analyzed firstly. A dynamic demand forecasting method was introduced to forecast the coming demand in a ticket booking period. By clustering, passengers' historical ticket bookings were used to forecast the demand to come in a ticket booking period with least squares support vector machine. Three seat inventory control methods: non-nested booking limits, nested booking limits and bid-price control, were modeled under a single-fare class. Different seat inventory control methods were compared with the same demand based on ticket booking data of Train T15 from Beijing West to Guangzhou. The result shows that the dynamic non-nested booking limits control method performs the best, which gives railway operators evidence to adjust the remaining capacity in a ticket booking period.

Adaptive Nonlinear Model Predictive Control Using an On-line Support Vector Regression Updating Strategy

The performance of data-driven models relies heavily on the amount and quality of training samples, so it might deteriorate significantly in the regions where samples are scarce. The objective of this paper is to develop an online SVR model updating strategy to track the change in the process characteristics efficiently with affordable computational burden. This is achieved by adding a new sample that violates the Karush–Kuhn–Tucker conditions of the existing SVR model and by deleting the old sample that has the maximum distance with respect to the newly added sample in feature space. The benefits offered by such an updating strategy are exploited to develop an adaptive model-based control scheme, where model updating and control task perform alternately.The effectiveness of the adaptive controller is demonstrated by simulation study on a continuous stirred tank reactor. The results reveal that the adaptive MPC scheme outperforms its non-adaptive counterpart for largemagnitude set point changes and variations in process parameters.

Fabrication of high-quality all-graphene devices with low contact resistances

All-graphene devices are new class of graphene devices with simple layouts and low contact resistances. Here we report a clean fabrication strategy for all-graphene devices via a defect-assisted anisotropic etching. The as-fabricated graphene is free of contamination and retains the quality of pristine graphene. The contact resistance at room temperature （RT） between a bilayer graphene channel and a multilayer graphene electrode can be as low as -5 Ω.·μm, the lowest ever achieved experimentally. Our results suggest the feasibility of employing such all-graphene devices in high performance carbon-based integrated circuits.

Generation of Bell states via Lyapunov control on a two-qubit system with an anisotropic XY Heisenberg interaction

We demonstrate that an arbitrary Bell state can be achieved in a two qubit anisotropic Heisenberg XY chain via Lyapunov control. During the whole process, we only need to apply an external field along a given direction to a single qubit. This control strategy is effective for all initial states in the four-dimensional Hilbert space where the target state is asymptotically stable. The effects of imperfections on the fidelity for the target state such as Gaussian leakage of local control and localized dephasing of individual spins are also considered.