Research And Application Of Intelligence Algorithm Based On Quantum Computation

Quantum Computation(QC)has the properties of parallelism, exponential storage and speed up etc.., It has been one of the advancing fields in modern science and technology. The features of superposition of quantum states, entanglement and interference in Quantum theory, is possible to solve many difficult problems in classical computing, It caused widespread concern as its unique computing performance and powerful computing technology.Intelligent algorithm is an important research fielding optimized area in recent years, more and more researchers pay attention to it especially Swarm intelligence. It is the property of a system whereby the collective behaviors of agents interacting locally with their environment. Smart as the typical modes of the main groups, intelligent simulation of biological Ant colony algorithm optimization and simulation exercise habits of the PSO algorithm model is being widely academia concern .they are quickly recognized by the international field of evolutionary studies in the short run due to its simple concept and easy to be realized.Intelligent optimization algorithms combined with quantum computation is a new subject rised in recent years. It can improve the computational efficiency and overcome fall into local minimum to a certain extent. Therefore, the research of Quantum Computational Intelligence that the basic concepts of Quantum computation can be introduced to the classical algorithm to improve the performance of classical computing has the important value both on the theory and practice. We study the intelligence algorithm combined with quantum computation reference the features of quantum theory. Firstly we propose a new ant algorithm using the quantum algorithm to optimize the control parameters of the ACS and we use it to solve Chinese Traveling Salesman Problem (CTSP); Then we propose an improved quantum particle swarm algorithms and the improved algorithm is proven valid. The specific research and innovation are as follows:1. The overview of the quantum computation principle. We introduce the principle of quantum computing, quantum bit, quantum gates, register, the features of quantum computing such as quantum state superposition, quantum coherence, entanglement and interference etc..2. The research of the intelligence algorithm. We introduce PSO algorithm, including its principle, algorithm processes and applications goes into particulars, as well as the ACO algorithm including its principle, Algorithm processes, features and improved ACA algorithm. ACA algorithm is used for training neural network, then this network model is applied to credit evaluation system of Small-middle Enterprise, the result demonstrates that it has strong generalization ability as well as high accuracy rate.3. Research and Application of quantum ant colony algorithm. We propose an improved ant colony algorithm based quantum which Pheromone is be represented by quantum and using quantum rotation gate operation to update the pheromone .At the same time we give the steps of the new algorithm. Experimental results show that this algorithm improves the convergence speed and the ability to find the optimal solution, then we use it to solve Chinese traveling salesman problem and obtain the optimal solution, indicating that the algorithm is feasible and practical in solving practical problems.4. Improved Quantum Particle swarm algorithm is proposed. We propose an improved algorithm based the study of quantum particle swarm algorithm principle, algorithm processes, This algorithm adopts two particle swarm putting up evolution at one time, the experiment proves that the improved algorithm global search capability has been strengthened and also proved the superiority of this algorithm.