Quantum Genetic Algorithm And Its Application In The Data Rectification

In chemical production process, The quality of the plant is due to the quality of the production process data and these data is the foundation of scientific research, computer process operation, simulation and optimization and production management. Measurement data theoretically should meet the constraints such as material balance, energy balance and so on. But in fact, the data which collect from the field with the error inevitablely, because of the precision of measuring instruments, measuring methods and environment factors, further affect the operating condition, so we need to eliminate the error by data reconciliation. Generally measurment data can be classified as random error and gross error. Traditional data reconciliation will appear the situation that errors which the data has allocated to the data without error. The solving method of the data coordination and Data classification need to use the equation derication or matrix conversion and calculate complexity. So we introduce a novel probabiliatic optimization Algorithm—Quantum genetic algorithm.Quantum genetic algorithm is a kind of probabilistic optimization method, which combines quantum computing theory with genetic algorithm. Compared with Genetic algorithm, it has better characteristics of population diversity, computing parallelism, quicker convergence rate, higher search efficiency and stronger ability of global optimization. But for continuous functions with extreme values, Quantum genetic algorithm is easy to fall into local optimization, so an improved quantum genetic algorithm is proposed to overcome the shortcoming of QGA,and it is applied in data reconciliation.This paper is divided into six chapters. Fristly, introduct the research status of data reconciliation and describe research of genetic algorithm and quantum genetic algorithm, compare genetic algorithm with quantum genetic algorithm. Secondly, this paper elaborates the basic concepts and principles of QGA, and show its flow chart, then an improved quantum genetic algorithm is proposed to overcome the shortcoming. The results using two typical function tested show that improved quantum genetic algorithm's ability of optimization and convergence rate is better than quantum genetic algorithm.Finally, the concepts of data reconciliation are introducted, and improved quantum genetic algorithm is applied in the data reconciliation of secondary-air system and General rectifying tower. The results show its feasibility of the program.