The paper solves the eigenvalues of a symmetric matrix by using three novel algorithms developed in the m-dimensional affine Krylov subspace. The n-dimensional eigenvector is superposed by a constant shifting vector and an m-vector. In the first algorithm, the m-vector is derived as a function of eigenvalue by maximizing the Rayleigh quotient to generate the first characteristic equation, which, however, is not easy to determine the eigenvalues since its roots are not of simple ones, exhibiting turning points, spikes, and even no intersecting point to the zero line. To overcome that difficulty by the first algorithm, we propose the second characteristic equation through a new quotient with the inner product of the shifting vector to the eigen-equation. The Newton method and the fictitious time integration method are convergent very fast due to the simple roots of the second characteristic equation. For both symmetric and nonsymmetric eigenvalue problems solved by the third algorithm, we develop a simple iterative detection method to maximize the Euclidean norm of the eigenvector in terms of the eigen-parameter, of which the peaks of the response curve correspond to the eigenvalues. Through a few finer tunings to the smaller intervals sequentially, a very accurate eigenvalue and eigenvector can be obtained. The efficiency and accuracy of the proposed iterative algorithms are verified and compared to the Lanczos algorithm and the Rayleigh quotient iteration method.

Coastal countries began to develop green energy, and offshore wind power equipment in coastal areas was gradually built. Since coastal wind power generation often requires carrying out maintenance between wind turbines with the assistance of service operation vessels, this situation may cause coastal areas to be prone to people falling into the water. However, traditional maritime search and rescue plans take a long time to gather information from man overboard incidents. In order to minimize injuries to people in distress, the maritime search and rescue process must be as short as possible. Despite that all the search and rescue plans are based on the concept of the shortest path, the efficient plans must not only consider the distance but also consider the cost of search and rescue. Therefore, this study established a set of practices applicable to the on-site commander (OSC) to dispatch rescue ships, as well as the planning of maritime search and rescue route models. Based on the easy-to-observe state of the target in distress, the model is analyzed and calculated by Floyd–Warshall algorithm and Grey relational analysis so as to sort the rescue plan and optimize the effect of the search and rescue route at sea. According to the simulation analysis, when the man overboard incident occurs in the coastal area, the OSC can immediately use this model to plan the best search and rescue route and dispatch a reasonable number of rescue ships.

In this paper, the numerical solutions of the backward and forward non-homogeneous wave problems are derived to address the nonlocal boundary conditions. When boundary conditions are not set on the boundaries, numerical instability occurs, and the solution may have a significant boundary error. For this reason, it is challenging to solve such nonlinear problems by conventional numerical methods. First, we derive a nonlocal boundary shape function (NLBSF) from incorporating the Pascal triangle as free functions; hence, the new, two-parameter Pascal bases are created to automatically satisfy the specified conditions for the solution. To satisfy the wave equation in the domain by the collocation method, the solution of the forward nonlocal wave problem can be quickly obtained with high precision. For the backward nonlocal wave problem, we construct the corresponding NLBSF and Pascal bases, which exactly implement two final time conditions, a left-boundary condition and a nonlocal boundary condition; in addition, the numerical method for the backward nonlocal wave problem under two-side, nonlocal boundary conditions is also developed. Nine numerical examples, including forward and backward problems, are tested, demonstrating that this scheme is more effective and stable. Even for boundary conditions with a large noise at final time, the solution recovered in the entire domain for the backward nonlocal wave problem is accurate and stable. The accuracy and efficiency of the method are validated by comparing the estimation results with the existing literature.

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