【摘要】 为了构建围堰监测预警的人工智能模型，保障围堰安全高效运行，提出一种用于处理受约束非线性单调算子方程的混合三项共轭梯度算法。搜索方向由Hestenes-Stiefel (HS)和无记忆Broyden-Fletcher-Goldfarb-Shanno(BFGS)计算的方向组合而成。在没有任何附加条件的情况下，搜索方向拥有充分下降性和信赖域性。在温和的假设条件下，证明了该方法的全局收敛性。该算法可解决机器学习问题，实验结果也验证了所提方法的优越性。更多还原

【Abstract】 In order for an artificial intelligence model for monitoring and early warning of cofferdam to be constructed, and the safe and efficient operation of the cofferdam to be ensured, a hybrid triple conjugate gradient algorithm was proposed in this paper for dealing with constrained nonlinear monotone operator equations. The search directions are combined from those computed by Hestenes-Stiefel(HS) and memoryless Broyden-Fletcher-Goldfarb-Shanno(BFGS). In the absence of any additional conditions, the search direction possesses sufficient descent and trust domain properties.Global convergence of the method is proved under mild assumptions. The algorithm solves the machine learning problem and the experimental results validate the superiority of the proposed method.更多还原