CABC–CSA: a new chaotic hybrid algorithm for solving optimization problems

Recently a lot of methods have been presented for solving optimization problems. In this paper, we are trying to propose a new hybrid algorithm for solving these kinds of problem. The proposed algorithm is based on chaotic artificial bee colony and chaotic simulated annealing, CABC–CSA. The chaotic artificial bee colony finds new locations chaotically. Actually, the proposed algorithm provides a combination of local search accuracy of simulated annealing and the ability of global search of artificial bee colony. Furthermore, we used a different method for generating the initial population. The proposed algorithm is validated using 12 benchmark functions. The results are compared with those of the artificial bees’ algorithm, the hybrid algorithm of artificial bee colony and simulated annealing and particle swarm optimization. Simulation results show the efficiency of the proposed algorithm.     

Parameter estimation for chaotic systems by hybrid differential evolution algorithm and artificial bee colony algorithm

This paper is concerned with the parameter estimation of nonlinear chaotic system, which could be essentially formulated as a multi-dimensional optimization problem. In this paper, a hybrid algorithm by combining differential evolution with artificial bee colony is implemented to solve parameter estimation for chaotic systems. Hybrid algorithm combines the exploration of differential evolution with the exploitation of the artificial bee colony effectively. Experiments have been conducted on Lorenz system and Chen system. The proposed algorithm is applied to estimate the parameters of two chaotic systems. Simulation results and comparisons demonstrate that the proposed algorithm is better or at least comparable to differential evolution, artificial bee colony, particle swarm optimization, and genetic algorithm from literature when considering the quality of the solutions obtained.     

Chaotic ant swarm for the traveling salesman problem

Chaotic ant swarm (CAS) is an optimization algorithm based on swarm intelligence theory, which has been applied to find the global optimum solution in continuous search space. However, it is not able to solve the combinational optimization problem directly, e.g., the traveling salesman problem (TSP). To tackle this problem, we propose a new method to solve the traveling salesman problem based on chaotic ant swarm, CAS-TSP for short. The CAS-TSP is developed by introducing a mapping from continuous space to discrete space, reverse operator and crossover operator into the CAS. Computer simulations demonstrate that the CAS-TSP is capable of generating optimal solution to instances of the TSPLIB in almost all test problems of sizes up to 150. Also a comparative computational study shows that this CAS-TSP algorithm is an efficient tool for solving TSP and this heuristic is competitive also with other heuristics.     

CAS based clustering algorithm for Web users

This article devises a clustering technique for detecting groups of Web users from Web access logs. In this technique, Web users are clustered by a new clustering algorithm which uses the mechanism analysis of chaotic ant swarm (CAS). This CAS based clustering algorithm is called as CAS-C and it solves clustering problems from the perspective of chaotic optimization. The performance of CAS-C for detecting Web user clusters is compared with the popular clustering method named k-means algorithm. Clustering qualities are evaluated via calculating the average intra-cluster and inter-cluster distance. Experimental results demonstrate that CAS-C is an effective clustering technique with larger average intra-cluster distance and smaller average inter-cluster distance than k-means algorithm. The statistical analysis of resulted distances also proves that the CAS-C based Web user clustering algorithm has better stability. In order to show the utility, the proposed approach is applied to a pre-fetching task which predicts user requests with encouraging results.     

一种磨损预测的优化算法研究

根据机械部件磨损机理复杂、磨损量预测难精确的特点,提出基于免疫粒子群参数优化的最小二乘支持向量机方法预测磨损量.该算法采用免疫粒子群优化最小二乘支持向量机建模参数,避免了算法陷入局部最优解,实现了精确度高、泛化能力强的磨损量预测模型.对轴承钢试件磨损进行了试验研究,试验数据分析结果表明,基于免疫粒子群的最小二乘支持向量机预测方法优于前向反馈神经网络算法、遗传算法及蚁群算法,预测误差较小,具有很好的预测能力.     

Single amplifier biquad based autonomous electronic oscillators for chaos generation

Two simple autonomous chaotic electronic circuits have been proposed in this paper. The core of each of the circuits consists of a single amplifier biquad (SAB). We have proposed two configurations of converting this SAB into chaotic oscillators using suitable passive nonlinear element and a storage element in the form of an inductor. The mathematical models of the proposed chaotic circuits have been constructed, which are fourth order autonomous nonlinear differential equations. The behavior of the proposed circuits has been investigated through numerical simulations, Spice-based circuit simulations and electronic hardware experiments and they agree well with each other. It has been found that both the circuits show complex behaviors like bifurcations and chaos for a certain range of circuit parameters.     

A new chaotic attractor from hybrid optical bistable system

In this work, a new three-dimensional autonomous chaotic system has been introduced by modifying a hybrid optical system. The single quadratic nonlinearity is replaced by a single cubic nonlinearity; the new system can display two 1-scroll chaotic attractors simultaneously or one 2-scroll chaotic attractor. The bifurcation diagram is obtained and Lyapunov spectrum is calculated for the proposed system. The results show that the new system exhibits rich complexity features such as stable, periodic, and chaotic dynamics.     

遗传算法改进及其在岩土参数反分析中的应用

本文的主要目的是开发基于实数编码的杂交遗传算法来识别土体的本构参数。该杂交遗传算法在经典遗传算法框架下开发,融合两个新开发的交叉算子,形成了一个新的杂交策略。为了保持种群的多样性,在算法中采用了一个动态随机变异算子。另外,为了提高算法收敛性,采用了一个基于混沌的局部搜索技术。分别基于室内试验和现场试验,通过识别土的本构参数来测试新算法的搜索能力和搜索效率。为了测试新开发算法的突出表现,特选用5种经典的随机类算法（遗传算法、粒子群算法、模拟退火算法、差分算法和蜂巢算法）,分析同样的案例进行比较。结果表明,在收敛速度和最优解的准确度方面,新改进的算法可以很好地处理岩土工程的参数反演。     

Designing a multi-scroll chaotic system by operating Logistic map with fractal process

Recently, chaotic systems have been widely investigated in several engineering applications. This paper presents a new chaotic system based on Julia’s fractal process, chaotic attractors and Logistic map in a complex set. Complex dynamic characteristics were analyzed, such as equilibrium points, bifurcation, Lyapunov exponents and chaotic behavior of the proposed chaotic system. As we know, one positive Lyapunov exponent proved the chaotic state. Numerical simulation shows a plethora of complex dynamic behaviors, which coexist with an antagonist form mixed of bifurcation and attractor. Then, we introduce an algorithm for image encryption based on chaotic system. The algorithm consists of two main stages: confusion and diffusion. Experimental results have proved that the proposed maps used are more complicated and they have a key space sufficiently large. The proposed image encryption algorithm is compared to other recent image encryption schemes by using different security analysis factors including differential attacks analysis, statistical tests, key space analysis, information entropy test and running time. The results demonstrated that the proposed image encryption scheme has better results in the level of security and speed.     

基于蚁群算法的复合材料缠绕壳体铺层顺序优化

为了提高纤维复合材料缠绕壳体结构的屈曲稳定性,本文将蚁群算法(ACA)求解旅行商问题(TSP)的方法引入到缠绕层顺序优化的计算中.阐明铺层顺序优化的本质是调整沿板厚方向的刚度分布以提高版的抗弯刚度,同时改善荷载的传递路径,以降低由偏心而产生的附加弯矩,从而提高结构的抗屈曲能力;扩展了经典蚁群算法,提出一种分组编解码方法...     

Analog circuit design and optimal synchronization of a modified Rayleigh system

This paper addresses the problem of optimization of the synchronization of a chaotic modified Rayleigh system. We first introduce a four-dimensional autonomous chaotic system which is obtained by the modification of a two-dimensional Rayleigh system. Some basic dynamical properties and behaviors of this system are investigated. An appropriate electronic circuit (analog simulator) is proposed for the investigation of the dynamical behavior of the proposed system. Correspondences are established between the coefficients of the system model and the components of the electronic circuit. Furthermore, we propose an optimal robust adaptive feedback which accomplishes the synchronization of two modified Rayleigh systems using the controllability functions method. The advantage of the proposed scheme is that it takes into account the energy wasted by feedback coupling and the closed loop performance on synchronization. Also, a finite horizon is explicitly computed such that the chaos synchronization is achieved at an established time. Numerical simulations are presented to verify the effectiveness of the proposed synchronization strategy. Pspice analog circuit implementation of the complete master–slave controller system is also presented to show the feasibility of the proposed scheme.     

面向工程全局优化的混沌优化算法研究进展Research advances of chaos optimization algorithms for engineering global optimization

近年来,基于混沌的初值敏感性、伪随机性、遍历性以及自相似分形等非线性动力学特性所发展的混沌优化方法,是一种有潜力的工程全局优化新工具,已广泛应用于科学与工程技术的各学科领域。根据混沌优化方法的发展历程,以算法基本思想和工程应用研究状况为重点,评述了混沌神经网络优化方法、第一类混合混沌优化算法（基于混沌搜索）、第二类混合混沌优化算法（混沌序列代替随机序列）以及混沌分形优化四种主要混沌优化算法。混沌映射最早被引入神经网络,发展了混沌神经网络优化方法,可解决复杂的组合优化等全局优化问题。遗传算法及粒子群等启发式随机算法虽具全局搜索能力,但易出现早熟并陷入局部最优。然后,出现了混沌搜索的概念,研究者将其嵌入启发式算法建立了第一类混合混沌优化算法,可有效克服原启发式算法早熟收敛的缺点。随后,利用混沌映射产生的混沌序列代替启发式算法中的随机参数形成了第二类混合混沌优化算法。混合混沌优化算法有益于实现快速全局收敛和提高计算精度。最后,利用混沌分形特性,从分形理论出发提出一类新颖的混沌分形优化算法,可搜索到优化问题的所有全局最优解。此外,对混沌优化算法研究的几个发展方向进行了展望,诸如加强混沌优化算法的参数设计、处理大规模优化、多目标优化问题以及使用代理模型等。     

Particle tracking velocimetry with an ant colony optimization algorithm

A new concept algorithm based on the ant colony optimization is developed for the use in 2-D and 3-D particle tracking velocimetry (PTV). In the particle matching process of PTV, the ant colony optimization is usually aimed at minimization of the sum of the distances between the first-frame and second-frame particles. But this type of minimization often goes unsuccessfully in the regions where the particles are located very close to each other. In order to avoid this flaw, a new type of minimization is attempted using a physical property corresponding to the flow consistency or the quasi-rigidity of particle distribution patterns. Specifically, the ant colony optimization is now aimed at minimization of the sum of the relaxation of neighbor particles. In the present study, the new algorithm is applied to sets of 2-D and 3-D synthetic particle images as well as the experimental images with successful results.     

高速列车气动外形优化研究进展

随着运行速度的提升, 高速列车对气动外形的要求也越来越高, 追求性能优异、美观大方的气动外形是新型高速列车研发的一个重要方向. 基于当前高速列车外形研发的思路, 可以将气动外形优化概括为基于流场机理的改型优化和基于优化算法的外形优化两类. 本文简要回顾了当前国内外在这两类优化途径上的系列工作, 着重介绍了作者所在团队近年来做过的一系列气动外形优化工作. 在基于流场机理的改型优化上, 着重从"和谐号"和"复兴号"这两款主力车型的外形研发上探讨其改型优化的思路, 主要探讨了空调导流罩、受电弓平台、风挡和转向架裙板几类对列车阻力影响较为明显的部件的优化设计,并介绍了其相对于上一代车型在气动性能上的提升. 基于优化算法的外形优化方法,则因循气动外形优化流程, 在列车外形已经具有较好性能的基础上,以高速列车头型流线型为主要优化对象,分别从高速列车参数化方法、替代模型开发以及优化算法改进三个方面进行介绍.其中,高速列车参数化方法主要介绍了局部型函数法、修正车辆造型函数法和类别/形状函数法三类;替代模型开发介绍了最优化替代模型和基于交叉验证的Kriging模型; 在优化算法的改进上介绍了改进的非劣分类多目标粒子群算法和连续域混沌蚁群算法两方面的内容.基于上述三个方面介绍了气动外形优化策略在典型工程上的应用案例.      

Trajectory planning and tracking control for autonomous bicycle robot

Control of the autonomous bicycle robot offers considerable challenges to the field of robotics due to its nonholonomic, underactuated, and nonminimum-phase properties. Furthermore, instability and complex dynamic coupling make the trajectory planning of the bicycle robot even more challenging. In this paper, we consider both trajectory planning and tracking control of the autonomous bicycle robot. The desired motion trajectory of the contact point of the bicycle’s rear wheel is constructed using the parameterized polynomial curve that can connect two given endpoints with associated tangent angles. The parameters of the polynomial curve are determined by minimizing the maximum of the desired roll angle’s equilibrium of the bicycle, and this optimization problem is solved by the particle swarm optimization algorithm. Then, a control scheme that can achieve full-state trajectory tracking while maintaining the bicycle’s balance is proposed by combining a planar trajectory tracking controller with a roll angle balance controller. Simulation results are presented to demonstrate the effectiveness of the proposed method.     

Adaptive synchronization control based on QPSO algorithm with interval estimation for fractional-order chaotic systems and its application in secret communication

In this paper, the synchronization problem and its application in secret communication are investigated for two fractional-order chaotic systems with unequal orders, different structures, parameter uncertainty and bounded external disturbance. On the basis of matrix theory, properties of fractional calculus and adaptive control theory, we design a feedback controller for realizing the synchronization. In addition, in order to make it better apply to secret communication, we design an optimal controller based on optimal control theory. In the meantime, we propose an improved quantum particle swarm optimization (QPSO) algorithm by introducing an interval estimation mechanism into QPSO algorithm. Further, we make use of QPSO algorithm with interval estimation to optimize the proposed controller according to some performance indicator. Finally, by comparison, numerical simulations show that the controller not only can achieve the synchronization and secret communization well, but also can estimate the unknown parameters of the systems and bounds of external disturbance, which verify the effectiveness and applicability of the proposed control scheme.     

Analysis of a new 3D smooth autonomous system with different wing chaotic attractors and transient chaos

This letter proposes a new 3D quadratic autonomous chaotic system which displays an extremely complicated dynamical behavior over a large range of parameters. The new chaotic system has five real equilibrium points. Interestingly, this system can generate one-wing, two-wing, three-wing and four-wing chaotic attractors and periodic motion with variation of only one parameter. Besides, this new system can generate two coexisting one-wing and two coexisting two-wing attractors with different initial conditions. Furthermore, the transient chaos phenomenon happens in the system. Some basic dynamical behaviors of the proposed chaotic system are studied. Furthermore, the bifurcation diagram, Lyapunov exponents and Poincaré mapping are investigated. Numerical simulations are carried out in order to demonstrate the obtained analytical results. The interesting findings clearly show that this is a special strange new chaotic system, which deserves further detailed investigation.     

Bayesian system identification and chaotic prediction from data for stochastic Mathieu-van der Pol-Duffing energy harvester

In this paper, the approximate Bayesian computation combines the particle swarm optimization and sequential Monte Carlo methods, which identify the parameters of the Mathieu-van der Pol-Duffing chaotic energy harvester system. Then the proposed method is applied to estimate the coefficients of the chaotic model and the response output paths of the identified coefficients compared with the observed, which verifies the effectiveness of the proposed method. Finally, a partial response sample of the regular and chaotic responses, determined by the maximum Lyapunov exponent, is applied to detect whether chaotic motion occurs in them by a 0–1 test. This paper can provide a reference for data-based parameter identification and chaotic prediction of chaotic vibration energy harvester systems.     

A novel strange attractor with a stretched loop

This short paper introduces a new 3D strange attractor topologically different from any other known chaotic attractors. The intentionally constructed model of three autonomous first-order differential equations derives from the coupling-induced complexity of the well-established 2D Lotka?CVolterra oscillator. Its chaotification process via an anti-equilibrium feedback allows the exploration of a new domain of dynamical behavior including chaotic patterns. To focus a rapid presentation, a fixed set of parameters is selected linked to the widest range of dynamics. Indeed, the new system leads to a chaotic attractor exhibiting a double scroll bridged by a loop. It mutates to a single scroll with a very stretched loop by the variation of one parameter. Indexes of stability of the equilibrium points corresponding to the two typical strange attractors are also investigated. To encompass the global behavior of the new low-dimensional dissipative dynamical model, diagrams of bifurcation displaying chaotic bubbles and windows of periodic oscillations are computed. Besides, the dominant exponent of the Lyapunov spectrum is positive reporting the chaotic nature of the system. Eventually, the novel chaotic model is suitable for digital signal encryption in the field of communication with a rich set of keys.     

蚁群算法求解二维拉压不同模量反问题

利用光滑函数技术对二维拉压不同模量本构关系进行光滑化处理,采用初应力方法求解二维拉压不同模量正问题的有限元方程。在此基础上,建立了基于连续域蚁群算法的二维拉压不同模量反问题的数值求解模型,考虑了区域非均质的影响,实现了对拉压弹性模量和泊松比的单一/组合识别。通过两个数值算例,对所提算法进行了数值验证,分别探讨了蚁群算法相关参数、测点分布和数据噪音等对识别结果的影响。数值验证表明,所提算法可有效地求解二维拉压不同模量反问题,并具有较好的计算精度。