Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin（2/x） with infinite collapses within the finite region[-1, 1] to some representative iterative chaotic maps with ...Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin（2/x） with infinite collapses within the finite region[-1, 1] to some representative iterative chaotic maps with finite collapses （e.g., Logistic map, Tent map, and Chebyshev map）, a new adaptive mutative scale chaos optimization algorithm （AMSCOA） is proposed by using the chaos model x = sin（2/x）. In the optimization algorithm, in order to ensure its advantage of speed convergence and high precision in the seeking optimization process, some measures are taken： 1） the searching space of optimized variables is reduced continuously due to adaptive mutative scale method and the searching precision is enhanced accordingly; 2） the most circle time is regarded as its control guideline. The calculation examples about three testing functions reveal that the adaptive mutative scale chaos optimization algorithm has both high searching speed and precision.展开更多
In order to avoid such problems as low convergent speed and local optimalsolution in simple genetic algorithms, a new hybrid genetic algorithm is proposed. In thisalgorithm, a mutative scale chaos optimization strateg...In order to avoid such problems as low convergent speed and local optimalsolution in simple genetic algorithms, a new hybrid genetic algorithm is proposed. In thisalgorithm, a mutative scale chaos optimization strategy is operated on the population after agenetic operation. And according to the searching process, the searching space of the optimalvariables is gradually diminished and the regulating coefficient of the secondary searching processis gradually changed which will lead to the quick evolution of the population. The algorithm hassuch advantages as fast search, precise results and convenient using etc. The simulation resultsshow that the performance of the method is better than that of simple genetic algorithms.展开更多
This paper proposes a new search strategy using mutative scale chaos optimization algorithm （MSCO） for model selection of support vector machine （SVM）. It searches the parameter space of SVM with a very high effic...This paper proposes a new search strategy using mutative scale chaos optimization algorithm （MSCO） for model selection of support vector machine （SVM）. It searches the parameter space of SVM with a very high efficiency and finds the optimum parameter setting for a practical classification problem with very low time cost. To demonstrate the performance of the proposed method it is applied to model selection of SVM in ultrasonic flaw classification and compared with grid search for model selection. Experimental results show that MSCO is a very powerful tool for model selection of SVM, and outperforms grid search in search speed and precision in ultrasonic flaw classification.展开更多
目的分析淋巴结转移性结直肠癌中DNA错配修复基因(mismatch repair,MMR)系统MLH1(Mut L homolog1)和MSH2(Mut S homolog 2)基因的表达水平及临床意义。方法选取2015年6月至2017年4月收治的120例淋巴结转移性结直肠癌患者为研究对象,同...目的分析淋巴结转移性结直肠癌中DNA错配修复基因(mismatch repair,MMR)系统MLH1(Mut L homolog1)和MSH2(Mut S homolog 2)基因的表达水平及临床意义。方法选取2015年6月至2017年4月收治的120例淋巴结转移性结直肠癌患者为研究对象,同期选取120例无淋巴结转移的结直肠癌患者为对照;通过免疫组化法、实时荧光定量PCR法(q RT-PCR)、Western blot法,分别检测两组正常癌旁组织及病灶组织中MLH1、MSH2蛋白阳性表达缺失率,MLH1、MSH2 m RNA及蛋白表达水平。结果两组患者病灶组织MLH1、MSH2蛋白阳性表达缺失率均高于癌旁组织,而MLH1、MSH2 m RNA及蛋白相对表达水平均低于癌旁组织,差异均有统计学意义(P均<0.05);淋巴结转移性结直肠癌组病灶组织MLH1、MSH2蛋白阳性表达缺失率均高于无淋巴结转移组,MLH1、MSH2 m RNA及蛋白相对表达水平均低于无淋巴结转移组,差异均有统计学意义(P均<0.05);两组癌旁组织MLH1、MSH2蛋白阳性表达缺失率、MLH1、MSH2 m RNA及蛋白相对表达水平比较差异均无统计学意义(P均>0.05);MLH1、MSH阳性表达缺失率与淋巴结转移性结直肠癌患者的肿瘤直径、浸润深度、分化程度及淋巴结转移数有密切关系(P均<0.01),而与年龄无关(P>0.05)。结论淋巴结转移性结直肠癌中MLH1、MSH2表达水平显著降低,推测其在结直肠癌由无淋巴结转移进展为发生淋巴结转移中具有重要作用。展开更多
基金Hunan Provincial Natural Science Foundation of China (No. 06JJ50103)the National Natural Science Foundationof China (No. 60375001)
文摘Based on results of chaos characteristics comparing one-dimensional iterative chaotic self-map x = sin（2/x） with infinite collapses within the finite region[-1, 1] to some representative iterative chaotic maps with finite collapses （e.g., Logistic map, Tent map, and Chebyshev map）, a new adaptive mutative scale chaos optimization algorithm （AMSCOA） is proposed by using the chaos model x = sin（2/x）. In the optimization algorithm, in order to ensure its advantage of speed convergence and high precision in the seeking optimization process, some measures are taken： 1） the searching space of optimized variables is reduced continuously due to adaptive mutative scale method and the searching precision is enhanced accordingly; 2） the most circle time is regarded as its control guideline. The calculation examples about three testing functions reveal that the adaptive mutative scale chaos optimization algorithm has both high searching speed and precision.
文摘In order to avoid such problems as low convergent speed and local optimalsolution in simple genetic algorithms, a new hybrid genetic algorithm is proposed. In thisalgorithm, a mutative scale chaos optimization strategy is operated on the population after agenetic operation. And according to the searching process, the searching space of the optimalvariables is gradually diminished and the regulating coefficient of the secondary searching processis gradually changed which will lead to the quick evolution of the population. The algorithm hassuch advantages as fast search, precise results and convenient using etc. The simulation resultsshow that the performance of the method is better than that of simple genetic algorithms.
基金Project supported by National High-Technology Research and De-velopment Program of China (Grant No .863-2001AA602021)
文摘This paper proposes a new search strategy using mutative scale chaos optimization algorithm （MSCO） for model selection of support vector machine （SVM）. It searches the parameter space of SVM with a very high efficiency and finds the optimum parameter setting for a practical classification problem with very low time cost. To demonstrate the performance of the proposed method it is applied to model selection of SVM in ultrasonic flaw classification and compared with grid search for model selection. Experimental results show that MSCO is a very powerful tool for model selection of SVM, and outperforms grid search in search speed and precision in ultrasonic flaw classification.
文摘目的分析淋巴结转移性结直肠癌中DNA错配修复基因(mismatch repair,MMR)系统MLH1(Mut L homolog1)和MSH2(Mut S homolog 2)基因的表达水平及临床意义。方法选取2015年6月至2017年4月收治的120例淋巴结转移性结直肠癌患者为研究对象,同期选取120例无淋巴结转移的结直肠癌患者为对照;通过免疫组化法、实时荧光定量PCR法(q RT-PCR)、Western blot法,分别检测两组正常癌旁组织及病灶组织中MLH1、MSH2蛋白阳性表达缺失率,MLH1、MSH2 m RNA及蛋白表达水平。结果两组患者病灶组织MLH1、MSH2蛋白阳性表达缺失率均高于癌旁组织,而MLH1、MSH2 m RNA及蛋白相对表达水平均低于癌旁组织,差异均有统计学意义(P均<0.05);淋巴结转移性结直肠癌组病灶组织MLH1、MSH2蛋白阳性表达缺失率均高于无淋巴结转移组,MLH1、MSH2 m RNA及蛋白相对表达水平均低于无淋巴结转移组,差异均有统计学意义(P均<0.05);两组癌旁组织MLH1、MSH2蛋白阳性表达缺失率、MLH1、MSH2 m RNA及蛋白相对表达水平比较差异均无统计学意义(P均>0.05);MLH1、MSH阳性表达缺失率与淋巴结转移性结直肠癌患者的肿瘤直径、浸润深度、分化程度及淋巴结转移数有密切关系(P均<0.01),而与年龄无关(P>0.05)。结论淋巴结转移性结直肠癌中MLH1、MSH2表达水平显著降低,推测其在结直肠癌由无淋巴结转移进展为发生淋巴结转移中具有重要作用。
