无选择策略的改进蜜蜂群算法

针对人工蜂群算法（ABC）中群体多样性较差的缺点,提出无选择策略的改进的蜜蜂群算法（MABC）。MABC算法改变ABC算法的框架,通过去掉ABC算法中跟随蜂对引领蜂的选择策略,来降低算法的选择压力,提高种群多样性和算法的全局搜索能力。仿真结果表明,该算法能够有效保证群体多样性,提高人工蜂群算法的性能。     

基于ZigBee的土壤墒情监测系统

介绍了基于Zig Bee的土壤墒情监测系统的原理和设计.采用了大功率Zig Bee无线数传模块,有效地减少了节点的个数,提高了通信的可靠性.用太阳能电池供电,使得节点的长期稳定工作有了保障.可用于实时监测土壤的湿度、温度参数,为自动喷灌或滴灌提供土壤的墒情信息.实验证明:该系统具有可靠性高、成本低、实时性较强等优点,适合土壤墒情监测的需要.     

基于人工蜂群与模糊C均值的自适应小波变换的噪声图像分割

针对传统模糊C均值(FCM)聚类算法在处理噪声图像时易受到噪声影响的问题,提出了基于FCM的小波域特征增强的噪声图像分割方法.首先,将噪声图像进行二维小波分解;其次,对近似系数进行边缘增强,同时利用人工蜂群(ABC)优化算法对细节系数进行阈值处理,并将处理后的系数进行小波重构;最后,对重构后的图片使用FCM算法来进行图...     

基于人工蜂群算法的群体动画路径生成方法

大多数群体智能算法容易陷入局部最优,且收敛速度较慢。为此,将粒子群优化算法引入人工蜂群算法中,提出一种改进的路径生成算法NewABC,实现最优目标位置的选取及粒子个体的路径规划。将该方法生成的路径数据导入maya三维动画制作软件中进行仿真实验,结果表明,该方法生成的群体动画效果逼真,动画创作效率有较大的提高。     

An efficient two phase approach for solving reliability–redundancy allocation problem using artificial bee colony technique

The main goal of the present paper is to present a two phase approach for solving the reliability–redundancy allocation problems (RRAP) with nonlinear resource constraints. In the first phase of the proposed approach, an algorithm based on artificial bee colony (ABC) is developed to solve the allocation problem while in the second phase an improvement of the solution as obtained by this algorithm is made. Four benchmark problems in the reliability–redundancy allocation and two reliability optimization problems have been taken to demonstrate the approach and it is shown by comparison that the solutions by the new proposed approach are better than the solutions available in the literature.     

Molecular identification of honey entomological origin based on bee mitochondrial 16S rRNA and COI gene sequences

The increasing recognition and production of stingless bee honey has raised the needs to develop rapid, sensitive and accurate methodologies for honey identification through bees' species from the DNA of bees present in honey. Genetic identification of raw honeys produced by different bee species from Malaysia was performed based on mitochondrial DNA sequences and phylogenetic analysis by means of forensically informative nucleotide sequencing (FINS) technique. The 300 bp of mitochondrial large subunit ribosomal RNA (16S rRNA) gene region and mitochondrial cytochrome c oxidase subunit I (COI) gene region were the gene markers used to classify and identify honey produced by Apis honey bees and Trigona stingless bees. The genetic identities of honey origin from Apis dorsata, Apis mellifera, Apis cerana, and Heterotrigona itama were accurately identified. Kelulut honey sourced from the stingless bee was distinguishable from other Apis type of honeys in phylogenetic analyses. This FINS technique is a specific and reliable method for identification of honey origin via its bee source that can be used to overcome the issue of false declaration of honey origin and mislabelling.     

无线传感器网络通信技术与标准化分析

通过分析现有无线传感器网络标准,并对Zig Bee、蓝牙以及Wi-Fi这3种最常用标准的优缺点进行详细比较,探讨了无线传感器网络通信技术面临的挑战,进一步研究策略和未来发展趋势。     

Synthesis of satellite footprint patterns from rectangular planar array antenna by using swarm‐based optimization algorithms

A pattern synthesis method based on Firefly Algorithm (FA) and Artificial Bee Colony (ABC) optimization has been presented to generate satellite footprint patterns from a rectangular planar array of isotropic antennas by modifying the amplitude, phase, and the state of the array elements. Three cases comprising three different footprints of rectangular, square, and circular boundary are generated from the same array by using two different swarm‐based optimization algorithms FA and ABC. Both the algorithms, following the proposed procedures are able to generate the three different footprint patterns while maintaining a satisfactory lower peak side lobe level and ripple. A comparative analysis has been carried out between FA, ABC, and Genetic Algorithm (GA) for the presented problem in terms of fitness value for the three different cases. The superiority of FA and ABC over GA has been established in terms of finding better solutions for all the three cases of the proposed problem. Copyright © 2013 John Wiley & Sons, Ltd.     

Swarm intelligence of artificial bees applied to In-Core Fuel Management Optimization

Artificial Bee Colony (ABC) algorithm is a relatively new member of swarm intelligence. ABC tries to simulate the intelligent behavior of real honey bees in food foraging and can be used for solving continuous optimization and multi-dimensional numeric problems. This paper introduces the Artificial Bee Colony with Random Keys (ABCRK), a modified ABC algorithm for solving combinatorial problems such as the In-Core Fuel Management Optimization (ICFMO). The ICFMO is a hard combinatorial optimization problem in Nuclear Engineering which during many years has been solved by expert knowledge. It aims at getting the best arrangement of fuel in the nuclear reactor core that leads to a maximization of the operating time. As a consequence, the operation cost decreases and money is saved. In this study, ABCRK is used for optimizing the ICFMO problem of a Brazilian “2-loop” Pressurized Water Reactor (PWR) Nuclear Power Plant (NPP) and the results obtained with the proposed algorithm are compared with those obtained by Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The results show that the performance of the ABCRK algorithm is better than or similar to that of other population-based algorithms, with the advantage of employing fewer control parameters.     

蜂花粉对受照大鼠抗辐射效应的研究

研究了口服蜂花粉对受照大鼠外周血白细胞（ＰＷＢＣ）数，血清超氧化物歧化酶总活力（Ｔ－ＳＯＤ），血清过氧化脂质（ＬＰＯ）终产物丙二醛（ＭＤＡ）和过氧化值（ＰＯＶ）的影响。结果表明“蜂花粉具有良好的抗辐射损伤的功能，即服食花粉组的ＰＷＢＣ数和Ｔ－ＳＯＤ明显高于对照的正常组和单放组。花粉线的ＭＤＡ和ＰＯＶ显著低于对照的正常组和单放组。提示蜂花粉的抗放射要理可能是由于蜂花粉能提高机体的造血重建力，提高体内