Distributed and autonomous sensing based on the immune network

A distributed and autonomous sensor network is proposed based on the informational features of the immune network: recognition of nonself by distributed and dynamically interacting units, recognition by a simple comparison with the units themselves, dynamic propagation of activation that would lead to system-level recognition, and memory embedded as stable equilibrium states in the dynamic network. The network is explained by an illustrative example of an eight-coin puzzle: a balance must be used only three times to identify one coin with a different weight from the other seven coins. Our network also uses a dynamic structure network rather than the fixed structures used in neural networks. Simulations show that nonself (the different coin in the eight-coin puzzle, the sensor/process fault in the monitoring example) will be identified by dynamically propagating activation through the network. This work was presented, in part, at the International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1996     

基于免疫原理的模型预测控制方法及其在过热汽温控制中的应用

提出了基于免疫原理的模型预测控制方法，将免疫遗传算法作为优化技术用于模型预测控制的设计，并应用在电站锅炉过热汽温的控制系统中，仿真研究表明了该算法的可行性和有效性。     

自适应变尺度混沌免疫优化算法及其应用

结合混沌优化算法与免疫算法的特点,提出了一种采用折叠次数无限的自映射X=sin(2/x)产生混沌变量的自适应变尺度混沌免疫优化算法.该算法通过自适应变尺度方法不断调整优化变量的搜索空间,同时采用最大循环次数作为控制指标,既保证了寻优的准确性,又保证了算法的快速性.应用该算法对3个测试函数进行优化计算得到了比较满意的结果.将此算法应用于移动Ad Hoc网络入侵检测时的仿真实验结果表明,自适应变尺度混沌免疫优化算法能有效地减少对训练样本的依赖,同时减少噪音数据对入侵检测系统性能的影响,适用于移动自组网络对于入侵检测系统高检测率、高抗噪能力和低计算延迟的要求.     

求解模糊柔性Job-shop调度问题的多智能体免疫算法

考虑实际纸盆车间调度中模具、机器、操作人员等资源约束,以及加工时间和交货日期的不确定性,建立了批量可变的模糊柔性Job-shop调度问题模型.结合多智能体系统以及免疫信息处理机制,构造了一种求解实际Job-shop调度问题的多智能体免疫算法.该方法通过竞争、自学习、自适应疫苗接种、模拟退火等操作,更新每个智能体在解空间的位置,从而能精确地收敛到全局最优解.纸盆车间调度实例的求解结果验证了该算法的有效性.     

基于免疫原理的量子进化算法及收敛性研究

分析量子进化算法的特点及免疫进化的机理,提出一种基于免疫算子的量子进化算法．该算法通过免疫克隆选择、免疫细胞交叉变异、记忆细胞产生、抗体相似性抑制等进化机制,可以最终找出最优解,比传统的量子进化算法具有更好的种群多样性,更快的收敛速度和全局寻优能力．不仅从理论上证明了所提出算法的收敛性,而且通过仿真实验表明了该算法的优越性．     

基于免疫原理的分布式入侵检测系统的研究

生物的免疫系统成功地保护生物自身免受外来病原体的侵害,计算机的安全问题与生物免疫系统所遇到的问题具有惊人的相似,两者都在不断变化的环境中维持系统的稳定性。提出了免疫系统的分布的、灵活的、自适应和鲁棒的解决方式,这些特性正是计算机安全领域中期望得到的。用模拟免疫系统的工作原理来解决诸如故障诊断、病毒监测、异常检测等问题。     

基于免疫系统的多模型控制算法

针对非线性、不确定复杂系统控制困难的问题,借鉴生物免疫系统面临不确定的外来抗原呈现出的超强识别能力,模拟后天免疫中主要对象间的关系模型,提出了一种基于免疫系统的多模型控制新算法IMMC。通过计算机仿真实验,显示出算法在系统发生突变时具有良好的适应性能,并在双圆盾构法隧道施工对地面沉降控制中,取得了良好的效果,说明算法具有很强的推广应用价值。     

An adaptive balance optimization algorithm and its engineering application

The policy of balance between exploration capability and exploitation capability directly affects the solution performance of the meta-heuristic algorithm in a limited time. In order to better balance the exploration and exploitation capabilities of the algorithm and meet the solution requirements of complex real-world problems, the adaptive balance optimization algorithm (ABOA) is proposed in this paper. The algorithm consists of a global search phase (GSP) and a local search phase (LSP) and is controlled by a fixed parameter. ABOA not only considers the balance of exploration and exploitation capabilities of the algorithm throughout the whole iterative process but also focuses on the balance of exploration and exploitation in both GSP and LSP. The search in both phases is focused around the respective search centers from outside to inside. ABOA balances the exploration and exploitation capabilities of the algorithm throughout the search process by two adaptive policies: changing the search area and changing the search center. Fifty-two unconstrained benchmark test functions were employed to evaluate the performance of ABOA. The results of ABOA were compared with nine excellent optimization algorithms available in the literature. The statistical results and Friedman test showed that ABOA was significantly competitive. Finally, the results of the examined engineering design problems showed that ABOA can solve the constrained optimization problem better compared to other methods.     

基于通用FLAC的模糊自适应UKF算法及其应用

针对量测噪声方差统计值未知的非线性UKF(Unscented Kalman Filter)滤波问题,提出了一种基于通用FLAC(Fussy Logic Adaptive Controller)的模糊自适应UKF算法.在标准的非线性UKF算法基础上,以残差的实际方差与理论方差的比值作为FLAC的输入,使FLAC对滤波模型的依赖性减弱,强化了模糊自适应UKF方法的通用性;在对未知的量测噪声方差阵进行动态调节的过程中设置了指数调节参数,可不同程度地放大或缩小方差阵调节的幅度,使算法的调节速度和精度得到控制.将算法应用于GPS/DR(Dead-Reckoning)组合导航系统中,仿真结果表明了该算法的有效性.     

基于自适应布谷鸟搜索算法的K-means聚类算法及其应用

针对原始K-means聚类算法受初始聚类中心影响过大以及容易陷入局部最优的不足,提出一种基于改进布谷鸟搜索（CS）的K-means聚类算法（ACS-K-means）。其中,自适应CS（ACS）算法在标准CS算法的基础上引入步长自适应调整,以提高搜索精度和收敛速度。在UCI标准数据集上,ACS-K-means算法可得到比K-means、基于遗传算法的K-means（GA-K-means）、基于布谷鸟搜索的K-means（CS-K-means）和基于粒子群优化的K-means（PSO-K-means）算法更优的聚类质量和更高的收敛速度。将ACS-K-means聚类算法应用到南宁市青秀区“城管通”系统的城管案件热图的开发中,在地图上对案件地理坐标进行聚类并显示,应用结果表明,聚类效果良好,算法收敛速度快。     

An artificial immune system based algorithm to solve unequal area facility layout problem

This study introduces an artificial immune system (AIS) based algorithm to solve the unequal area facility layout problem (FLP) with flexible bay structure (FBS). The proposed clonal selection algorithm (CSA) has a new encoding and a novel procedure to cope with dummy departments that are introduced to fill the empty space in the facility area. The algorithm showed consistent performance for the 25 test problem cases studied. The problems with 100 and 125 were studied with FBS first time in the literature. CSA provided four new best FBS solutions and reached to sixteen best-so-far FBS solutions. Further, the two very large size test problems were solved first time using FBS representation, and results significantly improved the previous best known solutions. The overall results state that CSA with FBS representation was successful in 95.65% of the test problems when compared with the best-so-far FBS results and 90.90% compared with the best known solutions that have not used FBS representation.     

An adaptive waveform coding algorithm and its application in speech coding

This paper proposes a novel waveform coding algorithm based on the forward adaptive technique with the goal to provide the overreaching of the signal to quantization noise ratio achievable by the coding solution designed according to G.711 standard. The novel algorithm performs frame-by-frame analysis of the input signal, according to which one of the two compandors, the restricted or the unrestricted one, is selected for the particular frame procession. The basic concept of the proposed algorithm is to enable a more preferable selection of the restricted compandor than the unrestricted one, since, in such a manner, an increase of the signal to quantization noise ratio can be provided. Since both the theoretical and the simulation results, which are obtained for the assumed input speech signal, indicate the performance improvement over the G.711 standard along with approximately 1 bit/sample compression, one can expect that the proposed algorithm will be effective in coding of signals, that as well as speech signals follow Laplacian distribution and have the time varying characteristics.     

基于免疫原理的进化算法

基于人类免疫系统的机理提出一种进化算法．简述了算法的基本原理与特点，定义了克隆、超变异、选择和记忆4种基本操作算子，给出了算法的主要步骤，并证明了算法能够以概率1收敛到全局最优点．用不同的测试函数进行仿真实验，结果表明该算法是有效的，能以较快的速度完成给定范围的搜索和优化任务．     

基于自适应混合遗传算法的协调控制系统

单元机组协调控制系统是大型火力发电机组的重要组成部分,针对协调控制系统过程的非线性、时变、大迟延、强藕合等特点,常规的机炉协调控制系统策略已经不能满足电网对单元机组协调控制系统的设计要求和控制品质要求。本文利用实数编码自适应混合遗传算法对协调控制系统的PID控制器参数进行优化,得到目标函数的全局最优解。仿真结果表明,文中方法使控制性能得到很大提高。     

A novel hybrid multi-objective immune algorithm with adaptive differential evolution

In this paper, we propose a novel hybrid multi-objective immune algorithm with adaptive differential evolution, named ADE-MOIA, in which the introduction of differential evolution (DE) into multi-objective immune algorithm (MOIA) combines their respective advantages and thus enhances the robustness to solve various kinds of MOPs. In ADE-MOIA, in order to effectively cooperate DE with MOIA, we present a novel adaptive DE operator, which includes a suitable parent selection strategy and a novel adaptive parameter control approach. When performing DE operation, two parents are respectively picked from the current evolved and dominated population in order to provide a correct evolutionary direction. Moreover, based on the evolutionary progress and the success rate of offspring, the crossover rate and scaling factor in DE operator are adaptively varied for each individual. The proposed adaptive DE operator is able to improve both of the convergence speed and population diversity, which are validated by the experimental studies. When comparing ADE-MOIA with several nature-inspired heuristic algorithms, such as NSGA-II, SPEA2, AbYSS, MOEA/D-DE, MIMO and D²MOPSO, simulations show that ADE-MOIA performs better on most of 21 well-known benchmark problems.     

An immune system based differential evolution algorithm using near-neighbor effect in dynamic environments

Many real-world problems are dynamic,requiring optimization algorithms being able to continuously track changing optima(optimum) over time.This paper proposes an improved differential evolutionary algorithm using the notion of the near-neighbor effect to determine one individuals neighborhoods,for tracking multiple optima in the dynamic environment.A new mutation strategy using the near-neighbor effect is also presented.It creates individuals by utilizing the stored memory point in its neighborhood,and utilizing the differential vector produced by the ’nearneighbor -superior’ and ’near-neighbor-inferior’.Taking inspirations from the biological immune system,an immune system based scheme is presented for rapidly detecting and responding to the environmental changes.In addition,a differencerelated multidirectional amplification scheme is presented to integrate valuable information from different dimensions for effectively and rapidly finding the promising optimum in the search space.Experiments on dynamic scenarios created by the typical dynamic test instance—moving peak problem,have demonstrated that the near-neighbor and immune system based differential evolution algorithm(NIDE) is effective in dealing with dynamic optimization functions.     

基于自适应模糊免疫PID阀门定位器的设计

传统工业阀门定位器具有控制精度低、功耗大、控制方式单一、阀位易抖动等缺点,且其在使用的过程中须进行现场调试才能进一步适应生产要求;为了提高阀门定位器控制系统的适应能力,对控制算法进行了深入研究,设计了一种基于STM32芯片的低功耗阀门定位器;硬件设计以STM32L152芯片为控制核心,外围电路包括4～20 mA转3.3 V电源电路、开度/位移信号转换电路、人机交互模块电路;软件设计采用自适应免疫模糊PID算法替代常规PID算法,实现了阀位控制参数的自整定;在MATLAB中构建阀门各机构数学模型的广义传递函数,搭建仿真电路;最终得出控制系统的调整时间只需0.8 s,且在整个控制过程中无超调量产生;有效提高了阀门的控制精度,避免了阀位的抖动现象.     

一种改进的基于免疫网络模型(aiNet) 的故障诊断算法

根据抗体群与抗原群的匹配关系,提出一种改进的基于免疫网络模型(aiNet)的故障诊断算法.建立了自适应调整剪枝和抑制阈值的规则,并对K近邻算法的附加距离阈值加以限制,提高了基于aiNet故障诊断算法对已知故障的识别率,克服了其不能识别新故障的缺点.仿真结果表明,改进算法具有优良的故障诊断性能.     

Realization of a self-recognition algorithm based on the biological immune system

As the use of the computer is popularized, the damage from computer viruses and hacking by malicious users is increasing rapidly. To block the hacking that is an intrusion into a person's computer, and the viruses that destroy data, a study into an intrusion detection and virus detection system based on the biological immune system is in progress. In this article, we describe a model of positive and negative selection for self-recognition, which has a similar function to the cytotoxic T cells that play an important role in the biological immune system. We propose a self/nonself discrimination algorithm for a computer system, which will the important when we detect data infected by a computer virus, of data modified by an intrusion from outside. We also show the validity and effectiveness of the proposed self-recognition algorithm by a computer simulation of some infected data obtained from cell changes and string changes in the self-file. This work was presented, in part, at the Seventh International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

小波变换自适应滤波器及在主动噪声控制中的应用

讨论了传统的 L MS在信号处理中的不足 ,研究了小波变换自适应算法 (WL MS)的滤波器结构和实现 ,并将其应用于主动噪声控制。仿真结果表明 ,与传统的 L MS算法相比 ,WL MS算法的收敛速度和稳定性得到显著的提高