LCR:局部收敛速度
“Local Convergence Rate”在学术和工程领域常被缩写为LCR(Local Convergence Rate),这种简写形式便于快速书写与交流。该术语广泛应用于数学优化、机器学习及数值分析等综合性学科中,用以描述迭代算法在接近最优解时的收敛快慢程度。其中文释义为“局部收敛速度”,特指算法在局部区域内逼近目标值的效率指标。
Local Convergence Rate具体释义
Local Convergence Rate的英文发音
例句
- The proposed algorithm not only has global convergence but also local convergence rate.
- 由此得到的算法不仅具有整体收敛性,而且保持快速的局部超线性收敛速率。
- We lay particular emphasis on analysis of global and local convergence and rate of convergence.
- 侧重于收敛的速率和整体、局部分析。
- ( iii ) The local quadratic convergence rate is proved under the condition that the solution is BD-regular;
- (ⅲ)在解是BD-正则条件下,证明了算法的局部二次收敛性;
- The global convergence results of the proposed algorithm are proved while maintaining fast local superlinear convergence rate is established by performing a two-piece update of two-side projected reduced Hessian.
- 在合理的条件下,算法具有整体收敛性且两块校正的双边既约Hessian投影法将保持超线性收敛速率。
- Benefiting from coevolution, probability of trapping in local minimum is reduced and convergence rate is improved. 2.
- 由于采用了协同进化机制,降低了陷入局部极小的可能性,提高了搜索效率。
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