对杉木屑进行不同成型直径、含水率及压缩速度条件下的冷态压缩成型试验,分析多个影响因素对木屑成型试样的松弛密度、抗压强度及比能耗的影响.通过单因素影响试验分析表明,在含水率为16%和成型直径为10 -12 mm 时能获得较好的成型参数...对杉木屑进行不同成型直径、含水率及压缩速度条件下的冷态压缩成型试验,分析多个影响因素对木屑成型试样的松弛密度、抗压强度及比能耗的影响.通过单因素影响试验分析表明,在含水率为16%和成型直径为10 -12 mm 时能获得较好的成型参数,压缩速度为40 mm/min 时,可获得较大的松弛密度和抗压强度,但比能耗相对较大.通过设计三因素三水平正交试验,运用多指标综合加权评分法对试验结果进行分析,权重系数综合考虑松弛密度、抗压强度和比能耗的重要与次要程度,结果表明：木屑最佳成型因素水平组合为成型直径10 mm、含水率16%、压缩速度40 mm/min,此时木屑试样松弛密度、抗压强度和比能耗分别为0.91 g/cm^3、315 N 和30.20 J/g,综合加权评分值最高.展开更多
Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is of...Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model(GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatialGLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran's I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.展开更多
基金Supported by the National High Technology Research and Development Program of China(863 Program)(No.2012AA092303)the Public Science and Technology Research Funds Projects of Ocean(No.20155014)+2 种基金the Shanghai Leading Academic Discipline Projectthe Funding Program for Outstanding Dissertation in Shanghai Ocean UniversitySupported by SHOU International Center for Marine Studies and Shanghai 1000 Talent Program
文摘Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model(GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatialGLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran's I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.
