Macrobenthic communities in the surrounding waters of Changli were investigated during spring and summer in2016.Differences in species quantity,abundance and biomass,the dominant species and species diversity index of...Macrobenthic communities in the surrounding waters of Changli were investigated during spring and summer in2016.Differences in species quantity,abundance and biomass,the dominant species and species diversity index of macrobenthos were analyzed.The results showed that58macrobenthos species were identified in spring,and92macrobenthos species were identified in summer.The composition of dominant species seasonally varied;however,most of them were species belonging to Polychaeta.The abundance of macrobenthos in summer was slightly higher than that in spring,while the biomass in summer was significantly smaller than that in spring.Bray-Curtis cluster analysis and multi-dimentional scaling(MDS)analysis indicated that macrobenthic communities were divided into three communities in spring,and two in summer.The abundance-biomass comparison(ABC)curve method was used to monitor the disturbance of environmental pollution for macrobenthic community.The results showed that the macrobenthos in this area received serious disturbance from environmental pollution.展开更多
Category-based statistic language model is an important method to solve the problem of sparse data.But there are two bottlenecks:1) The problem of word clustering.It is hard to find a suitable clustering method with g...Category-based statistic language model is an important method to solve the problem of sparse data.But there are two bottlenecks:1) The problem of word clustering.It is hard to find a suitable clustering method with good performance and less computation.2) Class-based method always loses the prediction ability to adapt the text in different domains.In order to solve above problems,a definition of word similarity by utilizing mutual information was presented.Based on word similarity,the definition of word set similarity was given.Experiments show that word clustering algorithm based on similarity is better than conventional greedy clustering method in speed and performance,and the perplexity is reduced from 283 to 218.At the same time,an absolute weighted difference method was presented and was used to construct vari-gram language model which has good prediction ability.The perplexity of vari-gram model is reduced from 234.65 to 219.14 on Chinese corpora,and is reduced from 195.56 to 184.25 on English corpora compared with category-based model.展开更多
基金supported by Ecological Restoration Technique in Typical Bay (No. TKS160226)Tianjin Municipal Science and Technology Planning Project (15ZCZDSF00620)
文摘Macrobenthic communities in the surrounding waters of Changli were investigated during spring and summer in2016.Differences in species quantity,abundance and biomass,the dominant species and species diversity index of macrobenthos were analyzed.The results showed that58macrobenthos species were identified in spring,and92macrobenthos species were identified in summer.The composition of dominant species seasonally varied;however,most of them were species belonging to Polychaeta.The abundance of macrobenthos in summer was slightly higher than that in spring,while the biomass in summer was significantly smaller than that in spring.Bray-Curtis cluster analysis and multi-dimentional scaling(MDS)analysis indicated that macrobenthic communities were divided into three communities in spring,and two in summer.The abundance-biomass comparison(ABC)curve method was used to monitor the disturbance of environmental pollution for macrobenthic community.The results showed that the macrobenthos in this area received serious disturbance from environmental pollution.
基金Project(60763001) supported by the National Natural Science Foundation of ChinaProject(2010GZS0072) supported by the Natural Science Foundation of Jiangxi Province,ChinaProject(GJJ12271) supported by the Science and Technology Foundation of Provincial Education Department of Jiangxi Province,China
文摘Category-based statistic language model is an important method to solve the problem of sparse data.But there are two bottlenecks:1) The problem of word clustering.It is hard to find a suitable clustering method with good performance and less computation.2) Class-based method always loses the prediction ability to adapt the text in different domains.In order to solve above problems,a definition of word similarity by utilizing mutual information was presented.Based on word similarity,the definition of word set similarity was given.Experiments show that word clustering algorithm based on similarity is better than conventional greedy clustering method in speed and performance,and the perplexity is reduced from 283 to 218.At the same time,an absolute weighted difference method was presented and was used to construct vari-gram language model which has good prediction ability.The perplexity of vari-gram model is reduced from 234.65 to 219.14 on Chinese corpora,and is reduced from 195.56 to 184.25 on English corpora compared with category-based model.
