非均质算法在油藏数值模拟中的应用与研究

三维地质模型网格数据量庞大,直接应用于油藏模拟多有不便。为减轻CPU工作负荷,方便油藏数值模拟,需要对大数据量的数值模型进行粗化处理,旨在减少三维网格体数据量的同时,尽量保持储层原有的地质信息。由此引发我们对精细油藏描述中非均质算法的研究,这一研究对油藏数值模拟有着重要意义。     

Data Fusion-based resilient control system under DoS attacks: A game theoretic approach

In this paper, the resilient control under the Denial-of-Service (DoS) attack is rebuilt within the framework of Joint Directors of Laboratories (JDL) data fusion model. The JDL data fusion process is characterized by the so-called Game-in-Game approach, where decisions are made at different layers. The interactions between different JDL levels are considered which take the form of Packet Delivery Rate of the communication channel. Some criterions to judge whether the cyber defense system is able to protect the underlying control system is provided. Finally, a numerical example is proposed to verify the validity of the proposed method.     

An adaptive discrete-time ILC strategy using fuzzy systems for iteration-varying reference trajectory tracking

In this article, a novel fuzzy systems based on adaptive Iterative Learning Control (ILC) strategy is presented to deal with a class of non-parametric nonlinear discrete-time systems which perform iteration-varying reference trajectory tracking. Using the technique of fuzzy systems to compensate for the non-parametric uncertainty of the discrete-time system dynamics, the proposed adaptive ILC scheme can well track the iteration-varying reference trajectory beyond the initial time points. The convergence of the fuzzy systems based adaptive ILC algorithm is guaranteed by theoretical analysis, and a numerical example is given to illustrate the effectiveness of the adaptive ILC scheme.

     

信息安全策略实施困难的原因与对策分析

随着企业生产规模的扩大,其所掌控的资产也越来越多。信息作为企业重要的资产,其安全性正得到越来越多的企业的关注,很多企业为了保证自身信息的安全与保密性,也制订了自身的信息安全策略。然而,很多企业的信息安全策略常常形同虚设,没有发挥其应有的作用,甚至存在着严重的漏洞,为企业的健康发展埋下了不小的隐患。笔者结合自身多年的工作经验,就企业信息安全策略实施过程中存在的问题进行分析,并针对性的提出几点对策,希望对相关人士能有所帮助。     

基于系统辨识的自适应控制技术的应用

介绍基于系统辨识的自适应控制系统模型在莱钢2#精炼炉合金下料系统中的应用,通过不断地调整控制过程中的参数值,使控制系统的瞬态响应过程达到最优,消除了生产过程中人为因素的影响,提高了生产的均一性和稳定性.     

An update-based step-wise optimal cache replacement for wireless data access

Many network applications requires access to most up-to-date information. An update event makes the corresponding cached data item obsolete, and cache hits due to obsolete data items become simply useless to those applications. Frequently accessed but infrequently updated data items should get higher preference while caching, and infrequently accessed but frequently updated items should have lower preference. Such items may not be cached at all or should be evicted from the cache to accommodate items with higher preference. In wireless networks, remote data access is typically more expensive than in wired networks. Hence, an efficient caching scheme considers both data access and update patterns can better reduce data transmissions in wireless networks. In this paper, we propose a step-wise optimal update-based replacement policy, called the Update-based Step-wise Optimal (USO) policy, for wireless data networks to optimize transmission cost by increasing effective hit ratio. Our cache replacement policy is based on the idea of giving preference to frequently accessed but infrequently updated data, and is supported by an analytical model with quantitative analysis. We also present results from our extensive simulations. We demonstrate that (1) the analytical model is validated by the simulation results and (2) the proposed scheme outperforms the Least Frequently Used (LFU) scheme in terms of effective hit ratio and communication cost.     

Fast and effective color-based object tracking by boosted color distribution

In this paper, we propose a novel tracking algorithm, boosted color distribution (BCD), for tracking color objects. There exist three contributions in this paper. First, we propose a novel online gentle boost (OGB) algorithm for online learning. The essential idea of OGB is composed of two aspects: online updating candidate weak classifiers, and then choosing and combining them in a boosting way. Second, we design a novel weak classifier, log color feature distribution ratio, which focuses on the difference of color distributions rather than individual samples and provides a simple yet effective manner of mining color features for object tracking. Third, by combining our OGB algorithm and our log color features, we develop a fast yet effective color-based object tracking algorithm. Numerous experiments demonstrate that our tracking algorithm is better than or not worse than some state-of-the-art tracking algorithms on some public sequences.Overall, this paper presents a novel BCD algorithm for color object tracking that achieves good results at a fast speed.