computerized design of under-ground mining method d一x!0 eo一kuong fongfo shejl deJ一suanjl fongfa地下采矿方法设计的计算机方法(c omPuter-ized design of underground mining method)用计算机和优化技术完成地下采矿方法设计的一种手段。由于地下采矿方
This algorithm is a coordinate-wise “steepest descent” method, which shows the greediness of the algorithm. The following theorem shows the validity of the algorithm. Theorem 3.19 Suppose that the same linear extension is chosen in Step 1 of greedy algorithms I and II. Then, starting from ...
Some experimental results are given to show that our greedy method works well in general cases and can achieve the same performance as the previously proposed method, that can only be used in some restricted cases.doi:10.1080/02533839.1996.9677776Chang, Chin‐Chen...
4. General Structure of Greedy Algorithm 5. Pair Work 1. A Short-Sighted Algorithm Greedy algorithm is another method of finding out the optimal solution, or the nearly optimal one of a task. Unlike DP, however, the Greedy algorithm may not always be able to find out the GLOBAL optimum,...
If a greedy algorithm can be proven to yield the global optimum for a given problem class, it typically becomes the method of choice because it is faster than other optimization methods like dynamic programming. Examples of such greedy algorithms are Kruskal's algorithm and Prim's algorithm for...
Stability and convergence of a local discontinuous Galerkin finite element method for the general Lax equation New topology in residuated lattices Optimality and duality in set-valued optimization utilizing limit sets An improved Schwarz Lemma at the boundary Initial layer problem of the Boussinesq...
We study a logistic model-based active learning procedure for binary classification problems, in which we adopt a batch subject selection strategy with a modified sequential experimental design method. Moreover, accompanying the proposed subject selection scheme, we simultaneously conduct a greedy variable...
This paper begins by discussing the theories oflearning, before discussing why Empirical Model-ling is an appropriate method of constructing educa-tional models. Current educational technologies areoften felt to be limited in scope for developmentand adaptation to personal needs. In contrast models...
The greedy algorithm to produce n-dimensional subspaces Xn to approximate a compact set F contained in a Hilbert space was introduced in the context of reduced basis method in [12], [13]. The same algorithm works for a general Banach space and in this context was studied in [4]. In thi...
The method uses a discrete model and satisfies all these constraints by backtracking at each step. In order to make full use of the capabilities of the machine tool, it is desirable to solve the problem with jerk constraints on each axis, because the drivers of the axes of a CNC machine ...