Investigation of Ant System parameter interactions by using design of experiments for job-shop scheduling problems

In recent years, one of the most important and promising research fields has been metaheuristics to find optimal or near-optimal solutions for NP-hard combinatorial optimization problems. Improving the quality of the solution or the solution time is basic research area on metaheuristics. Modifications of the existing ones or creation of hybrid approaches are the focus of these efforts. Another area of improving the solution quality of metaheuristics is finding the optimal combination of algorithm control parameters. This is usually done by design of experiments or one-at-a-time approach in genetic algorithms, simulated annealing and similar metaheuristics. We observe that, in studies which use Ant Colonies Optimization (ACO) as an optimization technique; the levels of control parameters are determined by some non-systematic initial experiments and the interactions of the parameters are not studied yet.In this study, the parameters of Ant System have been investigated on different sized and randomly generated job-shop scheduling problems by using design of experiments. The effects and interactions of the parameters have been interpreted with the outputs of the experiments. Referring to the statistical analysis it is observed that none of the interactions between the Ant System parameters has a significant effect on makespan value. A specific fractional experimental design is suggested instead of the full factorial design. Depending on the findings from the benchmark problems it will be a reliable approach to use the suggested design for saving time and effort in experiments without sacrificing the solution quality.     

Mean square asymptotic behavior of stochastic neural networks with infinitely distributed delays

In this paper, according to classic -matrix method, integral–differential inequality technique and Ito formula, we study asymptotic behavior in mean square sense of stochastic neural networks with infinitely distributed delays by establishing a generalized Halanay inequality. This is a new means for investigating asymptotic behavior of stochastic differential equation. Some useful results are derived. Especially, our methods can be extended to research p-moment asymptotic behavior easily. At last, example and simulations demonstrate the power of our methods.     

Synchronization analysis of coupled connected neural networks with mixed time delays

In this paper, the global exponential synchronization of coupled connected neural networks with both discrete and distributed delays is investigated under mild condition, assuming neither the differentiability and strict monotonicity for the activation functions nor the diagonal for the inner coupling matrices. By employing a new Lyapunov–Krasovskii functional, applying the theory of Kronecker product of matrices and the linear matrix inequality (LMI) technique, several delay-dependent sufficient conditions in LMI form are obtained for global exponential synchronization of such systems. Moreover, the decay rate is estimated. The proposed LMI approach has the advantage of considering the difference of neuronal excitatory and inhibitory efforts, which is also computationally efficient as it can be solved numerically using efficient Matlab LMI toolbox, and no tuning of parameters is required. In addition, the proposed results generalize and improve the earlier publications. An example with simulation is given to show the effectiveness of the obtained results.     

移动Sinks无线传感器网络的能量效率分析

能量效率是无线传感器网络的关键性问题,无线传感器网络通过移动sinks节点延长了网络的生命周期。讨论一些关键性要素对能量效率的影响,如簇的大小、移动sinks的速度、数量和数据包生命周期等。分析基于能量效率的单跳、多跳路由模式,提出最优跳数的簇路由模式,并以仿真实验验证移动sinks无线传感器网络的系统性能。     

A rapid-prototyping framework for extracting small-scale incident-related information in microblogs: Application of multi-label classification on tweets

Small scale-incidents such as car crashes or fires occur with high frequency and in sum involve more people and consume more money than large and infrequent incidents. Therefore, the support of small-scale incident management is of high importance.Microblogs are an important source of information to support incident management as important situational information is shared, both by citizens and official sources. While microblogs are already used to address large-scale incidents detecting small-scale incident-related information was not satisfyingly possible so far.In this paper we investigate small-scale incident reporting behavior with microblogs. Based on our findings, we present an easily extensible rapid prototyping framework for information extraction of incident-related tweets. The framework enables the precise identification and extraction of information relevant for emergency management. We evaluate the rapid prototyping capabilities and usefulness of the framework by implementing the multi-label classification of tweets related to small-scale incidents. An evaluation shows that our approach is applicable for detecting multiple labels with an match rate of 84.35%.     

地质标本虚拟仿真学习平台

地质标本的辨别是地学专业的学生必须具备的一项基础技能,但由于地质标本的种类多、属性特征不同、稀缺程度不一等原因,学生很难全面充裕的进行学习.本文从软件工程的角度出发,以地质标本的特点为切入点,确定了平台基本功能需求,设计系统的体系架构和功能模块,论述了系统主要技术及特色,最后对系统进行实现.通过地质标本虚拟仿真学习平台的建设,利用先进的软硬件技术,实现对地质标本的检索、属性浏览、三维展示等功能,为学生提供一种新的学习方式,提高他们的辨别技能.实际应用表明,该系统可以丰富学生对地质标本的认识,提高学生的辨别能力,取得了一定的效果.     

GPS井位勘测仪的研制与应用

在实际井位测量中,由于数据处理的滞后导致无法实时解算出定位结果,也无法对测量数据进行检核,这就很难保证测量数据的质量,一旦经内业处理后发现精度不合要求,还须返测,工作效率低下。为此介绍了一种以ARM9为开发平台,基于LINUX操作系统的手持式GPS井位勘测仪的实现原理,并给出了GPS井位勘测仪的总体结构设计、系统硬件设计和系统软件设计方案。该勘测仪能大幅提高油田井位勘测的工作效率,具有很高的实用价值。     

基于群体适应度方差的自适应混沌粒子群算法*

已有的混沌粒子群算法多使用Logistic混沌映射,但Logistic混沌映射产生的混沌序列不够均匀,影响了混沌粒子群算法的性能。提出在混沌粒子群算法中引入均匀性更好的An混沌映射,利用An混沌映射初始化粒子群的位置和速度,并通过适应度方差的变化来自适应控制部分粒子进行混沌更新,来改善混沌粒子群算法的性能。数值仿真的结果表明,改进算法的收敛性和全局搜索能力都有所提高,能有效避免早熟收敛。     

用于图像恢复的基于SVR的自适应新滤波器的研究*

提出了一种用SVR回归器识别脉冲噪声的思想,并将其应用于图像滤波和恢复,形成了用于对脉冲噪声进行滤波的SVR自适应滤波器。这种滤波器在滤波时,先用SVR对待识别像素作噪声识别,再对含噪声的像素作中值滤波。用SVR作噪声识别时,先对滤波窗口作SVR回归,通过待识别像素回归距的大小判断其是否含有噪声。在进行SVR回归时,使用鲁棒的Huber损失函数。由于更充分地利用了待识别像素点的局部背景信息,这种滤波器提高了脉冲噪声识别的正确率。实验表明,在保留原图像的细节信息方面,其滤波效果要优于基于SVC的中值滤波器。