Application Of Artificial Immune Algorithm In Geotechnical Engineering

From the information-processing perspective, the immune system is a highly parallel and distributed intelligent system that has learning, recognition, memory, and associative retrieval capabilities. Artificial Immune System, which has powerful information processing ability, simulates Biology Immune System. It is a novel intelligent computing research field following the invention of Artificial Neural Network and Evolutionary Computation, and it is an emergent interdisciplinary research field generated by life science and computer science and has become a hot point.The basic principles of the biologic immune system, the Clonal Selection Priciple, the researches and typical applications of AIS are introduced in this dissertation. The immune algorithm and its applications in geotechnical engineering are studied. The main works of this dissertation are summarized as follows.(1) Some basic concepts, functions and principles of the biological immune system are introduced. Then the causes of the premature convergence of the genetic algorithm (GA), the basic theory of IA, structure and process of the IA are analyzed. To verify the excellence of the immune algorithm, five numerical objective functions are adopted to compare the performance of genetic algorithm and immune algorithm. The simulation results demonstrate that IA has faster convergence speed and higher convergence accuracy.(2) The basic concepts of reliability theory are introduced. Based on the immune algorithm and geometric implication of the reliability index, a global optimization method is put forward to calculate the reliability index. By this method, reliability of the nonlinear and complex performance function of geotechnical engineering can be obtained without derivation. Two practical examples show that the method presented in this dissertation is reliable and accurate in the reliability analysis of geotechnical engineering.(3) Based on the results of static load tests of bored piles in Wuhan area, the statistics and reliability analyses of the bearing capacity of single PC pile are performed by utilizing the limit state equation of dimensionless random variables. The index of reliability of the single PC pile is calculated with both IA method and JC method. By immune algorithm, only the objective function value is used, reliability of the nonlinear and complex performance function of geotechnical engineering can be obtained without derivation. In recently years, multi-column composite foundation is widely used. The classification and the computation methods of bearing capacity of multi-column composite ground are introduced, and the ultimate bearing capacity equation is deduced. The program of computing reliability index is developed in MATLAB. Three practical examples using Monte-Carlo method and immune algorithm show that immune algorithm has the advantages of rapid convergence and high precision in the reliability analysis of bearing capacity of multi-column composite ground.(4) The Q-S curve of single pile has complicated nonlinear features because the ultimate bearing capacity of single pile is affected by many factors. Based on the results of static load test of prestressed concrete pipe piles in Wuhan area, immune algorithm program is developed by MATLAB to predict the ultimate bearing capacity of prestressed concrete pipe piles. Calculated results are in agreement with those from measurement.(5) To predict the settlement of foundations is an important issue in geotechnical engineering and one of the main concerns in design. IA is used in an attempt to obtain accurate settlement prediction. The predicted settlements obtained by IA are compared with those predicted by the least squares fitting method, Asaoka method and GA. The results show that IA is a useful technique for predicting the settlement of foundations.