ID 原文 译文
1183 DKCHER 算法是基于超扩展规则的求差知识编译算法。 DKCHER is a knowledge compilation algorithm of computing difference based on hyper extension rule.
1184 本文首先研究了 DKCHER 算法的执行流程，并定义了互补量的概念， We study on the executing process of DKCHER algorithm in this paper, and define the concept of complementary amount.
1185 然后设计了启发式策略 MACR(maximum complementary amount of clauses with middle result)，用于动态选择与中间结果互补量最大的子句。 We design MACR (maximum complementary amount of clauses with middle result)heuristics based on complementary a-mount, which is used to dynamically select the clause of maximum complementary amount with middle result.
1186 针对互补展开过程，设计了动态启发式策略 CAL(optimal sequence sortedby complementary amount of literals)，将互补展开中的文字按照与输入公式互补量的大小进行排序并展开。 For comple-mentary unfolding in DKCHER, we design dynamic heuristics CAL (optimal sequence sorted by complementary amount ofliterals), which sort the literals in complementary unfolding based on their complementary amounts.
1187 将上述两种启发式策略与 DKCHER 算法相结合，分别设计了 MACR_DKCHER 算法、CAL_DKCHER 算法和 MACR_CAL_DKCHER算法。 Combining the above two heuristic methods with DKCHER, MACR_DKCHER algorithm, CAL_DKCHER algorithm and MACR_CAL_DKCHERalgorithm are designed.
1188 实验结果表明，MACR 启发式策略能够提升 DKCHER 算法的编译效率和编译质量， Experimentally, MACR heuristics improves the compilation efficiency and compilation quality ofDKCHER.
1189 编译效率最高可提升 9 倍，编译质量最高可提升 1.9 倍; MACR heuristics can improve the efficiency of DKCHER by 9 times in the best case.
1190 CAL 启发式策略在子句数和变量数比值较大的实例上，能够提高 DKCHER 算法的编译效率，但会降低 DKCHER 算法的编译质量; CAL heuristics can signifi-cantly improve the compilation efficiency of DKCHER on the instances with big ratio of clause number with variable num-ber.
1191 MACR_CAL 启发式最高可将 DKCHER 算法的编译效率提高 12 倍，但会导致 DKCHER 算法的编译质量有所降低。 MACR_CAL heuristics can improve the efficiency of DKCHER by 12 times in the best case. But MACR_CAL heuris-tics reduces the compilation quality of DKCHER.
1192 频控阵(frequency diverse array)雷达存在角度和距离定位模糊的问题， Frequency diverse array radar has the problem of ambiguity in angle and range localization.