SAS Proc Mixed过程是SAS软件专为线性混合模型的分析而设计的统计过程,广泛应用于动物遗传改良,但在林业上的应用很少。文章就该过程在林业双列杂交、自由授粉子代测定和裂区试验设计等方面的利用,举例对分析程序、输出结果等作介绍。...SAS Proc Mixed过程是SAS软件专为线性混合模型的分析而设计的统计过程,广泛应用于动物遗传改良,但在林业上的应用很少。文章就该过程在林业双列杂交、自由授粉子代测定和裂区试验设计等方面的利用,举例对分析程序、输出结果等作介绍。该过程能对试验因子作最佳线性无偏预测(best linear unbiased prediction,BLUP),大大提高统计分析的准确性;并能自动适应多个误差效应的混合线性模型检验,与Proc GLM过程相比,Proc Mixed过程更简洁易用、分析效率高。展开更多
While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using po...While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using polypropylene and polyester fibers was evaluated and two models namely regression and artificial neural network(ANN) were used to predict the fatigue life based on the fibers parameters. As ANN contains many parameters such as the number of hidden layers which directly influence the prediction accuracy, genetic algorithm(GA) was used to solve optimization problem for ANN. Moreover, the trial and error method was used to optimize the GA parameters such as the population size. The comparison of the results obtained from regression and optimized ANN with GA shows that the two-hidden-layer ANN with two and five neurons in the first and second hidden layers, respectively, can predict the fatigue life of fiber-reinforced HMA with high accuracy(correlation coefficient of 0.96).展开更多
This paper presents a novel computational procedure for the maximum dry density of mixed soils containing oversize particles.At first,the large-scale compaction test data for mixed soils are analyzed by an artificial ...This paper presents a novel computational procedure for the maximum dry density of mixed soils containing oversize particles.At first,the large-scale compaction test data for mixed soils are analyzed by an artificial neural network to determine the main factors affecting the compaction.These factors are then imposed on a genetic programming method and a new mathematical equation emerges.The new equation has more conformity with the experimental data in comparison with the previous correction methods.Besides,the mixed soil dry density is associated with most base soil and oversize fraction specifications.With regard to the sensitivity analyses,if the mixed soil contains high percentages of oversize fraction,the mixed soil composition is governed by the specification of oversized grains,such as specific gravity and the maximum grain size and by increasing these factors,the mixed soil dry density is increased.In mixed soil with a low content of oversize,the base soil specification mainly controls the compaction behavior of mixed soil.Furthermore,if the base soil is inherently compacted with greater dry density,adding the oversize slightly improves the mixed soil dry density.In contrast,adding oversized grains to the base soil with a lower dry density produces a mixed soil with greater dry density.By increasing the maximum grain size difference between the oversize fraction and base soil,the dry density of mixed soil is enhanced.展开更多
文摘While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using polypropylene and polyester fibers was evaluated and two models namely regression and artificial neural network(ANN) were used to predict the fatigue life based on the fibers parameters. As ANN contains many parameters such as the number of hidden layers which directly influence the prediction accuracy, genetic algorithm(GA) was used to solve optimization problem for ANN. Moreover, the trial and error method was used to optimize the GA parameters such as the population size. The comparison of the results obtained from regression and optimized ANN with GA shows that the two-hidden-layer ANN with two and five neurons in the first and second hidden layers, respectively, can predict the fatigue life of fiber-reinforced HMA with high accuracy(correlation coefficient of 0.96).
文摘This paper presents a novel computational procedure for the maximum dry density of mixed soils containing oversize particles.At first,the large-scale compaction test data for mixed soils are analyzed by an artificial neural network to determine the main factors affecting the compaction.These factors are then imposed on a genetic programming method and a new mathematical equation emerges.The new equation has more conformity with the experimental data in comparison with the previous correction methods.Besides,the mixed soil dry density is associated with most base soil and oversize fraction specifications.With regard to the sensitivity analyses,if the mixed soil contains high percentages of oversize fraction,the mixed soil composition is governed by the specification of oversized grains,such as specific gravity and the maximum grain size and by increasing these factors,the mixed soil dry density is increased.In mixed soil with a low content of oversize,the base soil specification mainly controls the compaction behavior of mixed soil.Furthermore,if the base soil is inherently compacted with greater dry density,adding the oversize slightly improves the mixed soil dry density.In contrast,adding oversized grains to the base soil with a lower dry density produces a mixed soil with greater dry density.By increasing the maximum grain size difference between the oversize fraction and base soil,the dry density of mixed soil is enhanced.
