基于群体智能算法的RFID系统防冲突算法设计

发布时间：2018-06-16 14:45

本文选题：射频识别 + 读写器防冲突　；参考：《哈尔滨工程大学》2016年硕士论文

【摘要】：近年来,无线射频识别(Radio Frequency Identification ---RFID)技术应用日益广泛,而在RFID技术应中存在的一些急需要解决的问题。在这些问题当中,读写器之间的冲突问题很少有人去研究,而读写器之间发生冲突对整个系统是很不利的,它影响系统稳定性,影响工作效率。因此,为了解决读写器之间发生冲突的问题,提出了用改进布谷鸟算法来进行RFID系统优化的方法。在解决读写器冲突的问题过程中,分析了读写器的网络构成原理,采用图论的方法构建了读写器防冲突问题的数学模型,该数学模型是个包含多个变量的函数表达式。这样,所要解决的问题变成对数学模型进行优化的问题。而解决此类函数优化问题可以利用群体智能算法,例如蚁群算法、遗传算法、布谷鸟算法等。本文选用了布谷鸟算法。在对基本布谷鸟算法进行分析后,又借鉴了其他的群体智能算法的改进方法,本文提出了一种对基本布谷鸟算法的改进算法,称之为群体共生布谷鸟算法。该算法利用在自然界中多种群更容易存活的原则,对基本布谷鸟算法的初始种群分成若干个子种群,改进算法在运行过程中,通过各个子种群之间互相传递优势信息,使得各种群的优秀个体共享优势信息,更有利于发现函数的最优解。实验结果表明:改进算法在测试函数上表现较好;具有收敛速度快,求解精度高,运行时间短的特点。所以,该算法对RFID系统读写器防冲突模型优化结果较好,能够得到比较理想的实验数据。该算法对其他工程应用中的优化问题的有一定的借鉴意义。
[Abstract]:In recent years, Radio Frequency Identification (RFID) technology has been widely used, but there are some urgent problems to be solved in RFID technology. Among these problems, the conflict between readers is rarely studied, but the conflict between readers is very harmful to the whole system, which affects the stability of the system and the efficiency of work. Therefore, in order to solve the conflict between readers, an improved cuckoo algorithm is proposed to optimize RFID system. In the process of solving the problem of reader conflict, this paper analyzes the principle of the reader's network structure, and constructs a mathematical model of the reader's conflict prevention problem by using graph theory. The mathematical model is a functional expression with multiple variables. In this way, the problem to be solved becomes the optimization of the mathematical model. To solve this kind of function optimization problem, we can use swarm intelligence algorithm, such as ant colony algorithm, genetic algorithm, cuckoo algorithm and so on. This paper chooses the cuckoo algorithm. After analyzing the basic cuckoo algorithm and referring to other improved methods of swarm intelligence algorithm, this paper proposes an improved algorithm for the basic cuckoo algorithm, which is called the colony symbiotic cuckoo algorithm. Based on the principle that many populations are easier to survive in nature, the algorithm divides the initial population of the basic Cuckoo algorithm into several sub-populations. It is more advantageous to find the optimal solution of the function by making the excellent individuals of various groups share the superior information. The experimental results show that the improved algorithm performs well in the test function and has the advantages of fast convergence, high accuracy and short running time. Therefore, the algorithm can optimize the anti-collision model of RFID system reader better, and can get ideal experimental data. The algorithm can be used for reference in other engineering applications.
【学位授予单位】：哈尔滨工程大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.44;TP18

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