Research On MHC Regulation Based Immune Algorithm And Its Applications In Tunnel Engineering

The development of biological immune system theory and intelligence technology brings new ideas and great opportunities for the generation of intelligence algorithms. Also the new requirements of exploring underground space bring the challenge and broad arena for the application of intelligence algorithms. Inspired by MHC (Major Histocompatibility Complex) regulation principle of immune theory and its research in various fields, this dissertation proposes a series of novel and innovative intelligence algorithms and successfully applies them to the engineering practices for the tunnel engineering.The dissertation firstly reviews the main research results on immune system, then analyzes the current situation for both the domestic and foreign research in the artificial immune system and goes deep into the studies of MHC regulation principle. After having summarized & understood the main difficulties and their root cause in tunnel construction, the dissertation puts forward the new ideas on mutual incorporation and penetration of academic research and engineering study. These researches focus on the combination optimization, numerical optimization, function discovering and automatic control.The second chapter of the dissertation proposes an immune combination optimization algorithm (IOAMHC) based on MHC regulation. The third chapter describes the application of MHC regulation principle to numerical optimization algorithm and proposes a new immune numerical optimization algorithm (MHCIEA) combined with the concept of uniform design. Both algorithms are using the character of MHC self-adjust to guide the antibody evolution. Compared with the other optimization algorithm, the performances of the IOAMHC and MHCIEA are obviously improved because of the enhanced optimization searching strategy. The experiment for the benchmark cases shows that the performances of the algorithms are outstanding, and the application in the tunnel engineering also confirmed the good effect of new algorithms.The fourth chapter proposes an innovative formula discovering algorithm (IFDA) based on MHC regulation, which enlarges the research fields of immune algorithm and provides the new development space for immune algorithm. IFDA is applied to self-searching formula of the horizontal and vertical settlement curve for DOT (Double-0 Tube) shield tunneling. Compare with the historical engineering data, the formula is proved to fit the actual data closely and reflect the rule of ground settlement successfully.In the fifth chapter, a new method based on immune system for multiple model control (IMMC) is introduced. The method simulates the strong ability of discrimination to the uncertain antigen in the biological immune system and tries to solve the difficulties in controlling the nonlinear and uncertain complicated system effectively and rapidly. The simulation experiment shows that the algorithm has excellent performance as it can rapidly adapt to the sudden changes in the control system. The algorithm is successfully applied to the settlement control in a DOT shield tunneling. Actually IMMC is an interdisciplinary algorithm which covers biological theory, control theory and computer science.Directed by the research results of the dissertation, two systems named "Shield Tunneling Remote Intelligent System" and "Shield Tunneling Segment Type Selection System" are successfully implemented. Both systems led to great benefits toward society, environment and economy as they are being used in about thirties engineering projects, such as Shanghai metro, cross-river tunnel etc.