As an S-shaped curve,the logistic curve has both high and low limit,which provides advantages in modelling the influences of environmental factors on biogeological processes.However,although the logistic curve and its...As an S-shaped curve,the logistic curve has both high and low limit,which provides advantages in modelling the influences of environmental factors on biogeological processes.However,although the logistic curve and its transformations have drawn much attention in theoretical modelling,it is often used as a classification method to determine a true or false condition,and is less often applied in simulating the real data set.Starting from the basic theory of the logistic curve,with observed data sets,this paper explored the new application scenarios such as modelling the time series of environmental factors,modelling the influence of environmental factors on biogeological processes and modelling the theoretical curve in ecology area.By comparing the performance of traditional model and the logistic model,the results indicated that logistic modelling worked as well as traditional equations.Under certain conditions,such as modelling the influence of temperature on ecosystem respiration,the logistic model is more realistic than the widely applied Lloyd-Taylor formulation under extreme conditions.These cases confirmed that the logistic curve was capable of simulating nonlinear influences of multiple factors on biogeological processes such as carbon dynamic.展开更多
In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 （Internet Protocol ...In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 （Internet Protocol version 4） addresses, this paper proposes a forecasting model by using S curve （logistic curve）. The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions （i.e., Barabasi-Albert method） is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabasi-Albert method commonly used in current network research.展开更多
为研究鲜猪肉在不同储藏温度下主要腐败菌及其总挥发性盐基氮(TVB-N)含量随时间的变化规律,找出其变化函数模型。选取(-3±0.5)、(0±0.5)、(4±0.5)、(10±0.5)℃四个储藏温度组,每组设置0、10、20、34、48、72、96 h ...为研究鲜猪肉在不同储藏温度下主要腐败菌及其总挥发性盐基氮(TVB-N)含量随时间的变化规律,找出其变化函数模型。选取(-3±0.5)、(0±0.5)、(4±0.5)、(10±0.5)℃四个储藏温度组,每组设置0、10、20、34、48、72、96 h 7个不同的储藏时间,测定鲜猪肉细菌菌落总数、大肠杆菌等6个微生物指标和TVB-N含量,对各指标的时间序列值在4个储藏温度组间进行配对T检验,并建立Logistic生长曲线函数模型。结果表明:不同储藏温度组鲜猪肉各指标间存在极显著差异;各指标在不同储藏温度下与自变量时间t的Logistic生长曲线函数的决定系数R2均大于0.9;以总挥发性盐基氮含量为指标,得出理论上(0±0.5)℃储藏不超过76 h的为鲜猪肉,超过76 h不超过121 h的为次鲜肉。综合分析,鲜猪肉建议(0±0.5)℃储藏为宜,储藏时间不超过121 h。研究结果可为鲜猪肉储藏保鲜提供参考。展开更多
基金This study was jointly funded by the National Key Research and Development Program of China(2016YFE0109600)China Geological Survey projects(1212010611402,DD20189503).
文摘As an S-shaped curve,the logistic curve has both high and low limit,which provides advantages in modelling the influences of environmental factors on biogeological processes.However,although the logistic curve and its transformations have drawn much attention in theoretical modelling,it is often used as a classification method to determine a true or false condition,and is less often applied in simulating the real data set.Starting from the basic theory of the logistic curve,with observed data sets,this paper explored the new application scenarios such as modelling the time series of environmental factors,modelling the influence of environmental factors on biogeological processes and modelling the theoretical curve in ecology area.By comparing the performance of traditional model and the logistic model,the results indicated that logistic modelling worked as well as traditional equations.Under certain conditions,such as modelling the influence of temperature on ecosystem respiration,the logistic model is more realistic than the widely applied Lloyd-Taylor formulation under extreme conditions.These cases confirmed that the logistic curve was capable of simulating nonlinear influences of multiple factors on biogeological processes such as carbon dynamic.
基金Project supported by the National Natural Science Foundation of China (Grant No. 70871082)the Shanghai Leading Academic Discipline Project (Grant No. S30504)
文摘In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 （Internet Protocol version 4） addresses, this paper proposes a forecasting model by using S curve （logistic curve）. The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions （i.e., Barabasi-Albert method） is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabasi-Albert method commonly used in current network research.
