Polylactic acid(PLA)is a potential polymer material used as a substitute for traditional plastics,and the accurate molecular weight distribution range of PLA is strictly required in practical applications.Therefore,ex...Polylactic acid(PLA)is a potential polymer material used as a substitute for traditional plastics,and the accurate molecular weight distribution range of PLA is strictly required in practical applications.Therefore,exploring the relationship between synthetic conditions and PLA molecular weight is crucially important.In this work,direct polycondensation combined with overlay sampling uniform design(OSUD)was applied to synthesize the low molecular weight PLA.Then a multiple regression model and two artificial neural network models on PLA molecular weight versus reaction temperature,reaction time,and catalyst dosage were developed for PLA molecular weight prediction.The characterization results indicated that the low molecular weight PLA was efficiently synthesized under this method.Meanwhile,the experimental dataset acquired from OSUD successfully established three predictive models for PLA molecular weight.Among them,both artificial neural network models had significantly better predictive performance than the regression model.Notably,the radial basis function neural network model had the best predictive accuracy with only 11.9%of mean relative error on the validation dataset,which improved by 67.7%compared with the traditional multiple regression model.This work successfully predicted PLA molecular weight in a direct polycondensation process using artificial neural network models combined with OSUD,which provided guidance for the future implementation of molecular weight-controlled polymer's synthesis.展开更多
Sampling is a bridge between continuous-time and discrete-time signals,which is import-ant to digital signal processing.The fractional Fourier transform(FrFT)that serves as a generaliz-ation of the FT can characterize...Sampling is a bridge between continuous-time and discrete-time signals,which is import-ant to digital signal processing.The fractional Fourier transform(FrFT)that serves as a generaliz-ation of the FT can characterize signals in multiple fractional Fourier domains,and therefore can provide new perspectives for signal sampling and reconstruction.In this paper,we review recent de-velopments of the sampling theorem associated with the FrFT,including signal reconstruction and fractional spectral analysis of uniform sampling,nonuniform samplings due to various factors,and sub-Nyquist sampling,where bandlimited signals in the fractional Fourier domain are mainly taken into consideration.Moreover,we provide several future research topics of the sampling theorem as-sociated with the FrFT.展开更多
Landscape pattern is a widely used concept for the demonstration of landscape characteristic features. The integral spatial distribution trend of landscape elements is interested point in the landscape ecological rese...Landscape pattern is a widely used concept for the demonstration of landscape characteristic features. The integral spatial distribution trend of landscape elements is interested point in the landscape ecological research, especially in those of complex secondary forest regions with confusing mosaics of land cover. Trend surface analysis which used in community and population ecological researches was introduced to reveal the landscape pattern. A reasonable and reliable approach for application of trend surface analysis was provided in detail. As key steps of the approach, uniform grid point sampling method was developed. The efforts were also concentrated at an example of Guandishan forested landscape. Some basic rules of spatial distribution of landscape elements were exclaimed. These will be benefit to the further study in the area to enhance the forest sustainable management and landscape planning.展开更多
Cuckoo search （CS）, inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses L6vy flights random walk （LFRW） and biased/selective random walk （BSRW） to search for new solutions....Cuckoo search （CS）, inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses L6vy flights random walk （LFRW） and biased/selective random walk （BSRW） to search for new solutions. In this study, we seek a simple strategy to set the scaling factor in LFRW, which can vary the scaling factor to achieve better performance. However, choosing the best scaling factor for each problem is intractable. Thus, we propose a varied scal- ing factor （VSF） strategy that samples a value from the range [0,1] uniformly at random for each iteration. In addition, we integrate the VSF strategy into several advanced CS vari- ants. Extensive experiments are conducted on three groups of benchmark functions including 18 common test functions, 25 functions proposed in CEC 2005, and 28 functions intro- duced in CEC 2013. Experimental results demonstrate the ef- fectiveness of the VSF strategy.展开更多
基金funded by the Zhejiang Provincial Natural Science Foundation of China(LD21B060001)the National Natural Science Foundation of China(22078296,21576240).
文摘Polylactic acid(PLA)is a potential polymer material used as a substitute for traditional plastics,and the accurate molecular weight distribution range of PLA is strictly required in practical applications.Therefore,exploring the relationship between synthetic conditions and PLA molecular weight is crucially important.In this work,direct polycondensation combined with overlay sampling uniform design(OSUD)was applied to synthesize the low molecular weight PLA.Then a multiple regression model and two artificial neural network models on PLA molecular weight versus reaction temperature,reaction time,and catalyst dosage were developed for PLA molecular weight prediction.The characterization results indicated that the low molecular weight PLA was efficiently synthesized under this method.Meanwhile,the experimental dataset acquired from OSUD successfully established three predictive models for PLA molecular weight.Among them,both artificial neural network models had significantly better predictive performance than the regression model.Notably,the radial basis function neural network model had the best predictive accuracy with only 11.9%of mean relative error on the validation dataset,which improved by 67.7%compared with the traditional multiple regression model.This work successfully predicted PLA molecular weight in a direct polycondensation process using artificial neural network models combined with OSUD,which provided guidance for the future implementation of molecular weight-controlled polymer's synthesis.
基金supported in part by the National Natural Foundation of China(NSFC)(Nos.62027801 and U1833203)the Beijing Natural Science Foundation(No.L191004).
文摘Sampling is a bridge between continuous-time and discrete-time signals,which is import-ant to digital signal processing.The fractional Fourier transform(FrFT)that serves as a generaliz-ation of the FT can characterize signals in multiple fractional Fourier domains,and therefore can provide new perspectives for signal sampling and reconstruction.In this paper,we review recent de-velopments of the sampling theorem associated with the FrFT,including signal reconstruction and fractional spectral analysis of uniform sampling,nonuniform samplings due to various factors,and sub-Nyquist sampling,where bandlimited signals in the fractional Fourier domain are mainly taken into consideration.Moreover,we provide several future research topics of the sampling theorem as-sociated with the FrFT.
文摘Landscape pattern is a widely used concept for the demonstration of landscape characteristic features. The integral spatial distribution trend of landscape elements is interested point in the landscape ecological research, especially in those of complex secondary forest regions with confusing mosaics of land cover. Trend surface analysis which used in community and population ecological researches was introduced to reveal the landscape pattern. A reasonable and reliable approach for application of trend surface analysis was provided in detail. As key steps of the approach, uniform grid point sampling method was developed. The efforts were also concentrated at an example of Guandishan forested landscape. Some basic rules of spatial distribution of landscape elements were exclaimed. These will be benefit to the further study in the area to enhance the forest sustainable management and landscape planning.
文摘Cuckoo search （CS）, inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses L6vy flights random walk （LFRW） and biased/selective random walk （BSRW） to search for new solutions. In this study, we seek a simple strategy to set the scaling factor in LFRW, which can vary the scaling factor to achieve better performance. However, choosing the best scaling factor for each problem is intractable. Thus, we propose a varied scal- ing factor （VSF） strategy that samples a value from the range [0,1] uniformly at random for each iteration. In addition, we integrate the VSF strategy into several advanced CS vari- ants. Extensive experiments are conducted on three groups of benchmark functions including 18 common test functions, 25 functions proposed in CEC 2005, and 28 functions intro- duced in CEC 2013. Experimental results demonstrate the ef- fectiveness of the VSF strategy.
