Research On Clustering Algorithm Based On Quantum Theory

The amount of data is increasing rapidly with the development of database technology and wide use of database management systems. Data mining emerged in this promoting. Data mining techniques have been a research boom and are used in a wide range of applications. It is widely used in information retrieval, decision support and so on. Its applications have become increasingly widespread.The theoretical study of quantum computing is still a hot research topic, and in the past decade, quantum computing has made a series of astonishing achievement. According to quantum mechanics, quantum state has many advantages of the coherence and entanglement and the inner parallelism of quantum algorithm is totally different from the classical algorithm. Shor's algorithm shows the advantage of quantum algorithm in solving some classical Non-polynomial problems, and then Grover's search algorithm further proves this point. And this brought more and more research on quantum algorithm in many countries. Particularly quantum computing provides a new way to accelerate the running speed of the algorithms.So far, the research of quantum theory used in data mining field has gained some valuable research achievement. However, research in this field has yet to be promoted. In this paper, Quantum theory and algorithms has been studied. The main contributions are as following:(1) An improved clustering algorithm based on quantum mechanism. Quantum clustering is an algorithm based on quantum mechanism. The algorithm introduces the quantum potential energy in quantum mechanics theory. Some clustering algorithms can only find the globular clusters. This paper proposes an improved density clustering algorithm based on the quantum mechanism. Simulation results show that the new algorithm can effectively improves the cluster result.(2) The quantum ant colony clustering algorithm. Due to the shortage of ant colony algorithm been used in clustering process, this paper proposes a quantum ant colony clustering algorithm that has been used in clustering process. Simulation results show that the new algorithm not only accelerates the convergence speed but also makes the clustering effect more stable.