Estimation of the rock mass modulus of deformation(Em)is one of the most important design parameters in designing many structures in and on rock.This parameter can be obtained by in situ tests,empirical relations betw...Estimation of the rock mass modulus of deformation(Em)is one of the most important design parameters in designing many structures in and on rock.This parameter can be obtained by in situ tests,empirical relations between deformation modulus and rock mass classifcation,and estimating from laboratory tests results.In this paper,a back analysis calculation is performed to present an equation for estimation of the rock mass modulus of deformation using genetic programming(GP)and numerical modeling.A database of 40,960 datasets,including vertical stress(rz),horizontal to vertical stresses ratio(k),Poisson’s ratio(m),radius of circular tunnel(r)and wall displacement of circular tunnel on the horizontal diameter(d)for input parameters and modulus of deformation for output,was established.The selected parameters are easy to determine and rock mass modulus of deformation can be obtained from instrumentation data of any size circular galleries.The resulting RMSE of 0.86 and correlation coeffcient of97%of the proposed equation demonstrated the capability of the computer program(CP)generated by GP.展开更多
Web image retrieval is a challenging task. One central problem of web image retrieval is to rank a set of images according to how well they meet the user information need. The problem of learning to rank has inspired ...Web image retrieval is a challenging task. One central problem of web image retrieval is to rank a set of images according to how well they meet the user information need. The problem of learning to rank has inspired numerous approaches to resolve it in the text information retrieval, related work for web image retrieval, however, are still limited. We focus on the problem of learning to rank images for web image retrieval, and propose a novel ranking model, which employs a genetic programming architecture to automatically generate an effective ranking function, by combining various types of evidences in web image retrieval, including text information, image visual content features, link structure analysis and temporal information. The experimental results show that the proposed algorithms are capable of learning effective ranking functions for web image retrieval. Significant improvement in relevancy obtained, in comparison to some other well-known ranking techniques, in terms of MAP, NDCG@n and D@n.展开更多
Currently,deep drilling operates under extreme conditions of high temperature and high pressure,demanding more from subterranean power motors.The all-metal positive displacement motor,known for its robust performance,...Currently,deep drilling operates under extreme conditions of high temperature and high pressure,demanding more from subterranean power motors.The all-metal positive displacement motor,known for its robust performance,is a critical choice for such drilling.The dimensions of the PDM are crucial for its performance output.To enhance this,optimization of the motor's profile using a genetic algorithm has been undertaken.The design process begins with the computation of the initial stator and rotor curves based on the equations for a screw cycloid.These curves are then refined using the least squares method for a precise fit.Following this,the PDM's mathematical model is optimized,and motor friction is assessed.The genetic algorithm process involves encoding variations and managing crossovers to optimize objective functions,including the isometric radius coefficient,eccentricity distance parameter,overflow area,and maximum slip speed.This optimization yields the ideal profile parameters that enhance the motor's output.Comparative analyses of the initial and optimized output characteristics were conducted,focusing on the effects of the isometric radius coefficient and overflow area on the motor's performance.Results indicate that the optimized motor's overflow area increased by 6.9%,while its rotational speed reduced by 6.58%.The torque,as tested by Infocus,saw substantial improvements of38.8%.This optimization provides a theoretical foundation for improving the output characteristics of allmetal PDMs and supports the ongoing development and research of PDM technology.展开更多
Aim To determine the global optimal solution for a mine ventilation network under given network topology and airway characteristics. Methods\ The genetic algorithm was used to find the global optimal solution of the ...Aim To determine the global optimal solution for a mine ventilation network under given network topology and airway characteristics. Methods\ The genetic algorithm was used to find the global optimal solution of the network. Results\ A modified genetic algorithm is presented with its characteristics and principle. Instead of working on the conventional bit by bit operation, both the crossover and mutation operators are handled in real values by the proposed algorithms. To prevent the system from turning into a premature problem, the elitists from two groups of possible solutions are selected to reproduce the new populations. Conclusion\ The simulation results show that the method outperforms the conventional nonlinear programming approach whether from the viewpoint of the number of iterations required to find the optimum solutions or from the final solutions obtained.展开更多
文摘Estimation of the rock mass modulus of deformation(Em)is one of the most important design parameters in designing many structures in and on rock.This parameter can be obtained by in situ tests,empirical relations between deformation modulus and rock mass classifcation,and estimating from laboratory tests results.In this paper,a back analysis calculation is performed to present an equation for estimation of the rock mass modulus of deformation using genetic programming(GP)and numerical modeling.A database of 40,960 datasets,including vertical stress(rz),horizontal to vertical stresses ratio(k),Poisson’s ratio(m),radius of circular tunnel(r)and wall displacement of circular tunnel on the horizontal diameter(d)for input parameters and modulus of deformation for output,was established.The selected parameters are easy to determine and rock mass modulus of deformation can be obtained from instrumentation data of any size circular galleries.The resulting RMSE of 0.86 and correlation coeffcient of97%of the proposed equation demonstrated the capability of the computer program(CP)generated by GP.
基金supported by the Natural Science Foundation of China (60970047)the Natural Science Foundation of Shandong Province (Y2008G19)the Key Science-Technology Project of Shandong Province (2007GG10001002, 2008GG10001026)
文摘Web image retrieval is a challenging task. One central problem of web image retrieval is to rank a set of images according to how well they meet the user information need. The problem of learning to rank has inspired numerous approaches to resolve it in the text information retrieval, related work for web image retrieval, however, are still limited. We focus on the problem of learning to rank images for web image retrieval, and propose a novel ranking model, which employs a genetic programming architecture to automatically generate an effective ranking function, by combining various types of evidences in web image retrieval, including text information, image visual content features, link structure analysis and temporal information. The experimental results show that the proposed algorithms are capable of learning effective ranking functions for web image retrieval. Significant improvement in relevancy obtained, in comparison to some other well-known ranking techniques, in terms of MAP, NDCG@n and D@n.
基金supported by the National Natural Science Foundation of China (No.42172343)。
文摘Currently,deep drilling operates under extreme conditions of high temperature and high pressure,demanding more from subterranean power motors.The all-metal positive displacement motor,known for its robust performance,is a critical choice for such drilling.The dimensions of the PDM are crucial for its performance output.To enhance this,optimization of the motor's profile using a genetic algorithm has been undertaken.The design process begins with the computation of the initial stator and rotor curves based on the equations for a screw cycloid.These curves are then refined using the least squares method for a precise fit.Following this,the PDM's mathematical model is optimized,and motor friction is assessed.The genetic algorithm process involves encoding variations and managing crossovers to optimize objective functions,including the isometric radius coefficient,eccentricity distance parameter,overflow area,and maximum slip speed.This optimization yields the ideal profile parameters that enhance the motor's output.Comparative analyses of the initial and optimized output characteristics were conducted,focusing on the effects of the isometric radius coefficient and overflow area on the motor's performance.Results indicate that the optimized motor's overflow area increased by 6.9%,while its rotational speed reduced by 6.58%.The torque,as tested by Infocus,saw substantial improvements of38.8%.This optimization provides a theoretical foundation for improving the output characteristics of allmetal PDMs and supports the ongoing development and research of PDM technology.
文摘Aim To determine the global optimal solution for a mine ventilation network under given network topology and airway characteristics. Methods\ The genetic algorithm was used to find the global optimal solution of the network. Results\ A modified genetic algorithm is presented with its characteristics and principle. Instead of working on the conventional bit by bit operation, both the crossover and mutation operators are handled in real values by the proposed algorithms. To prevent the system from turning into a premature problem, the elitists from two groups of possible solutions are selected to reproduce the new populations. Conclusion\ The simulation results show that the method outperforms the conventional nonlinear programming approach whether from the viewpoint of the number of iterations required to find the optimum solutions or from the final solutions obtained.
