用于求解函数优化的一个蚁群处算法设计

文章通过对标准蚁群算法的认识，引进遗传算法的编码方式和选择操作，并对蚁群算法的信息素分配进行改进用于一般函数优化，通过几个函数求解，证明其是有效的。     

噪声图像中提取边缘的蚁群搜索算法

该文提出一种边缘引导的蚁群搜索算法,以解决常用的边缘提取方法抑制噪声能力不强,提取边缘不连续的缺点.此算法首先进行边缘检测获取由真实边缘和噪声组成的可能边缘点;然后利用可能边缘信息引导蚁群迭代搜索局部边缘曲线,并根据蚂蚁搜索曲线的长度更新其行走路径上的信息素分布,使搜索逐渐向真实的边缘收敛;最后,依据信息素遗留提取真实的边缘曲线.相对传统的蚁群算法,该文利用边缘信息引导蚁群搜索,增强了搜索的目的性,提高了算法效率.多组噪声图像的实验表明:该算法能够有效地从噪声图像中提取物体的真实边缘,在最大限度地保留细节信息的同时抑制噪声.     

基于蚁群算法的景象匹配定位

景象匹配定位是精确制导的重要技术,通过对景象匹配定位和蚁群算法的研究,提出一种基于蚁群算法的匹配定位方法,蚁群算法具有快速全局寻优能力,应用蚁群算法计算模版图像在基准图像中的匹配位置,根据匹配定位参数的特点,建立二维的蚁群搜索空间,定义图像的归一化积相关作为相似性度量并更新蚁群的信息素,利用信息素及启发信息来计算状态转移概率,蚁群最终聚集到适应度函数最大的路径上。实验结果表明：蚁群算法可以准确有效地估计匹配位置。     

Coupling ant colony systems with strong local searches

Ant colony system is a well known metaheuristic framework, and many efficient algorithms for different combinatorial optimization problems have been derived from this general framework. In this paper some directions for improving the original framework when a strong local search routine is available, are identified. In particular, some modifications able to speed up the method and make it competitive on large problem instances, on which the original framework tends to be weaker, are described. The resulting framework, called Enhanced Ant Colony System is tested on three well-known combinatorial optimization problems arising in the transportation field. Many new best known solutions are retrieved for the benchmarks available for these optimization problems.     

NS2中蚁群算法路由协议的实现

网络模拟是当前网络通信研究中的重要手段之一,在网络通信的建设开发过程中起着不可替代的作用。NS2由于其扩展性强、执行效率高,已被广泛应用于各种网络的仿真。首先介绍NS2的原理,然后结合蚁群算法介绍如何添加新协议到NS环境下并实现,最后给出新协议AntSense的仿真结果。     

Identification of protein methylation sites by coupling improved ant colony optimization algorithm and support vector machine

Protein methylation is involved in dozens of biological processes and plays an important role in adjusting protein physicochemical properties, conformation and function. However, with the rapid increase of protein sequence entering into databanks, the gap between the number of known sequence and the number of known methylation annotation is widening rapidly. Therefore, it is vitally significant to develop a computational method for quick and accurate identification of methylation sites. In this study, a novel predictor (Methy_SVMIACO) based on support vector machine (SVM) and improved ant colony optimization algorithm (IACO) is developed to identify methylation sites. The IACO is utilized to find the optimal feature subset and parameter of SVM, while SVM is employed to perform the identification of methylation sites. Comparison of the IACO with conventional ACO shows that the IACO converges quickly toward the global optimal solution and it is more useful tool for feature selection and SVM parameter optimization. The performance of Methy_SVMIACO is evaluated with a sensitivity of 85.71%, a specificity of 86.67%, an accuracy of 86.19% and a Matthew's correlation coefficient (MCC) of 0.7238 for lysine as well as a sensitivity of 89.08%, a specificity of 94.07%, an accuracy of 91.56% and a MCC of 0.8323 for arginine in 10-fold cross-validation test. It is shown through the analysis of the optimal feature subset that some upstream and downstream residues play important role in the methylation of arginine and lysine. Compared with other existing methods, the Methy_SVMIACO provides higher Acc, Sen and Spe, indicating that the current method may serve as a powerful complementary tool to other existing approaches in this area. The Methy_SVMIACO can be acquired freely on request from the authors.     

正交异性钢桥面系的多目标离散优化设计

将大跨径钢桥的正交异性钢桥面板和其上的铺装层作为钢桥面铺装体系整体进行多目标优化设计.取钢桥面铺装体系结构总重量最轻及铺装层使用年限最长两类指标构造目标函数,在此基础上采用功效函数法确定了目标函数的权重系数.应用正交异性钢桥面系力学性能控制指标和疲劳寿命预测公式,建立多目标优化设计的数学模型.引入蚂蚁算法,开发了钢桥面铺装体系结构多目标离散优化设计程序.以国内某大跨径钢桥为对象, 采用多目标优化设计方法, 给出钢桥面铺装体系中各参数的优化值.结果表明, 应用多目标优化设计方法对大跨径钢桥面铺装体系设计是可行的.研究成果可为大跨径钢桥面铺装体系结构的设计提供理论依据.     

A Hybrid Ant Colony Optimization for the Prediction of Protein Secondary Structure

Based on the concept of ant colony optimization and the idea of population in genetic algorithm, a novel global optimization algorithm, called the hybrid ant colony optimization （HACO）, is proposed in this paper to tackle continuous-space optimization problems. It was compared with other well-known stochastic methods in the optimization of the benchmark functions and was also used to solve the problem of selecting appropriate dilation efficiently by optimizing the wavelet power spectrum of the hydrophobic sequence of protein, which is the key step on using continuous wavelet transform （CWT） to predict a-helices and connecting peptides.     

气相色谱/质谱法分析柏树叶挥发油的化学成分

采用水蒸气蒸馏技术提取了3种柏树叶的挥发油,经气相色谱/质谱分析,共分离和鉴定了64种化学成分,其主要成分为萜烯类,其他成分为烷烃类、醇类、酚类和酯类等。其中圆柏树叶中分离鉴定出33种挥发性成分,主要萜类为桧烯(20.99%)和柠檬烯(19.78%);中山柏树叶中分离鉴定出37种挥发性成分,主要为α-蒎烯(10.39%)、桧烯(11.19%)和δ-3-蒈烯(8.88%);龙柏树叶中分离鉴定出37种挥发性成分,主要为柠檬烯(24.56%)和β-月桂烯(8.04%)。分离鉴定出3种柏树叶的共有成分14种。     

经过改进的求解TSP问题的蚁群算法

介绍了一种求解TSP问题的算法—改进的蚁群算法,算法通过模拟蚁群搜索食物的过程,可用于求解TSP问题,算法的主要特点是:正反馈、分布式计算、与某种启发式算法相结合.通过对传统蚁群算法的改进可以得到较好的结果.计算机仿真结果表明了该算法的有效性.