Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have dev...Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.展开更多
Based on the Bayesian information criterion, this paper proposes the improved local linear prediction method to predict chaotic time series. This method uses spatial correlation and temporal correlation simultaneously...Based on the Bayesian information criterion, this paper proposes the improved local linear prediction method to predict chaotic time series. This method uses spatial correlation and temporal correlation simultaneously. Simulation results show that the improved local linear prediction method can effectively make multi-step and one-step prediction of chaotic time series and the multi-step prediction performance and one-step prediction accuracy of the improved local linear prediction method are superior to those of the traditional local linear prediction method.展开更多
In this paper, we propose an adaptive strategy based on the linear prediction of queue length to minimize congestion in Barabaisi-Albert （BA） scale-free networks. This strategy uses local knowledge of traffic condit...In this paper, we propose an adaptive strategy based on the linear prediction of queue length to minimize congestion in Barabaisi-Albert （BA） scale-free networks. This strategy uses local knowledge of traffic conditions and allows nodes to be able to self-coordinate their accepting probability to the incoming packets. We show that the strategy can delay remarkably the onset of congestion and systems avoiding the congestion can benefit from hierarchical organization of accepting rates of nodes. Furthermore, with the increase of prediction orders, we achieve larger values for the critical load together with a smooth transition from free-flow to congestion.展开更多
The problem of blind adaptive equalization of underwater single-input multiple-output (SIMO) acoustic channels was analyzed by using the linear prediction method.Minimum mean square error (MMSE) blind equalizers with ...The problem of blind adaptive equalization of underwater single-input multiple-output (SIMO) acoustic channels was analyzed by using the linear prediction method.Minimum mean square error (MMSE) blind equalizers with arbitrary delay were described on a basis of channel identification.Two methods for calculating linear MMSE equalizers were proposed.One was based on full channel identification and realized using RLS adaptive algorithms,and the other was based on the zero-delay MMSE equalizer and realized using LMS and RLS adaptive algorithms,respectively.Performance of the three proposed algorithms and comparison with two existing zero-forcing (ZF) equalization algorithms were investigated by simulations utilizing two underwater acoustic channels.The results show that the proposed algorithms are robust enough to channel order mismatch.They have almost the same performance as the corresponding ZF algorithms under a high signal-to-noise (SNR) ratio and better performance under a low SNR.展开更多
Numerical simulations are presented about the effects of gas rarefaction on hypersonic flow field.Due to the extremely difficult experiment,limited wind-tunnel conditions and high cost,most problems in rarefied flow r...Numerical simulations are presented about the effects of gas rarefaction on hypersonic flow field.Due to the extremely difficult experiment,limited wind-tunnel conditions and high cost,most problems in rarefied flow regime are investigated through numerical methods,in which the direct simulation Monte-Carlo(DSMC)method is widely adopted.And the unstructured DSMC method is employed here.Flows around a vertical plate at a given velocity 7 500 m/s are simulated.For gas rarefaction is judged by the free-stream Knudsen number(Kn),two vital factors are considered:molecular number density and the plate′s length.Cases in which Kn varies from 0.035 to13.36 are simulated.Flow characters in the whole rarefied regime are described,and flow-field structure affected by Knis analyzed.Then,the dimensionless position D*of a certain velocity in the stagnation line is chosen as the marker of flow field to measure its variation.Through flow-field tracing and least-square numerical method analyzing,it is proved that hypersonic rarefied flow field expands outward linearly with the increase of 1/2Kn.An empirical method is proposed,which can be used for the prediction of the hypersonic flow-field structure at a given inflow velocity,especially the shock wave position.展开更多
For conservative linear homogeneous nonholonomic systems, there exists a cotangent bundle with the symplectic structure dπμ∧ dξμ, in which the motion equations of the system can be written into the form of the ca...For conservative linear homogeneous nonholonomic systems, there exists a cotangent bundle with the symplectic structure dπμ∧ dξμ, in which the motion equations of the system can be written into the form of the canonical equations by the set of quasi-coordinates πμand quasi-momenta ξμ. The key to construct this cotangent bundle is to define a set of suitable quasi-coordinates πμby a first-order linear mapping, so that the reduced configuration space of the system is a Riemann space with no torsion. The Hamilton–Jacobi method for linear homogeneous nonholonomic systems is studied as an application of the quasi-canonicalization. The Hamilton–Jacobi method can be applied not only to Chaplygin nonholonomic systems, but also to non-Chaplygin nonholonomic systems. Two examples are given to illustrate the effectiveness of the quasi-canonicalization and the Hamilton–Jacobi method.展开更多
目的科学评价芙蓉李果实成熟期间的营养品质,建立色度值表观特征与营养品质的关系。方法以福建省主栽品种芙蓉李为研究对象,对其成熟期间果糖、葡萄糖、蔗糖、苹果酸、奎尼酸、琥珀酸、柠檬酸、富马酸、矢车菊素-3-芸香糖苷、矢车菊素-3...目的科学评价芙蓉李果实成熟期间的营养品质,建立色度值表观特征与营养品质的关系。方法以福建省主栽品种芙蓉李为研究对象,对其成熟期间果糖、葡萄糖、蔗糖、苹果酸、奎尼酸、琥珀酸、柠檬酸、富马酸、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷、多酚、黄酮、类胡萝卜素等13个品质指标进行分析和综合评价。结果芙蓉李成熟期间,各品质指标的含量变化存在显著差异(P<0.05),综合运用相关分析、因子分析、绝对因子分析-多元线性回归(absolute principal component scores-multiple linear regression,APCS-MLR)分析筛选可反映芙蓉李综合品质的主要指标。因子分析提取出3个主因子,贡献率分别为52.677%、23.468%、11.649%,累计贡献率为87.794%。综合APCS-MLR等数理统计分析,主因子1主要对果糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷贡献较大,贡献率分别为53.00%、73.85%、55.54%;主因子2主要对蔗糖、富马酸、果糖、柠檬酸的贡献率较大,分别为28.26%、18.70%、16.14%、15.59%;主因子3主要对多酚(29.13%)和黄酮(28.28%)有较大贡献率;选取3个主因子总贡献率高于60%的果糖、葡萄糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷作为综合品质评价的主要指标。分别对已筛选出的4个主要评价指标与色度值进行多元线性逐步回归分析,建立4个主要指标与色度值的表观预测模型,各模型均具有较好的拟合度,预测值与实测值的均方根误差较小;进一步验证结果表明,通过色度值对4个指标的预测具有较高的可靠性和准确性。结论本研究筛选出的主要指标及预测模型可更加简单、便捷地评价芙蓉李果实成熟期间的综合品质。展开更多
基金This research was funded by the National Natural Science Foundation of China(grant no.32271881).
文摘Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.
文摘Based on the Bayesian information criterion, this paper proposes the improved local linear prediction method to predict chaotic time series. This method uses spatial correlation and temporal correlation simultaneously. Simulation results show that the improved local linear prediction method can effectively make multi-step and one-step prediction of chaotic time series and the multi-step prediction performance and one-step prediction accuracy of the improved local linear prediction method are superior to those of the traditional local linear prediction method.
基金Project supported by the National Natural Science Foundation of China (Grant No. 60672095)the Fundamental Research Funds for the Central Universities of China (Grant No. KYZ201300)+1 种基金the Natural Science Foundation of Jiangsu Province, China (Grant No. BK2013000)the Youth Sci-Tech Innovation Fund of Nanjing Agricultural University, China (Grant No. KJ2010024)
文摘In this paper, we propose an adaptive strategy based on the linear prediction of queue length to minimize congestion in Barabaisi-Albert （BA） scale-free networks. This strategy uses local knowledge of traffic conditions and allows nodes to be able to self-coordinate their accepting probability to the incoming packets. We show that the strategy can delay remarkably the onset of congestion and systems avoiding the congestion can benefit from hierarchical organization of accepting rates of nodes. Furthermore, with the increase of prediction orders, we achieve larger values for the critical load together with a smooth transition from free-flow to congestion.
基金Supported by the National Natural Science Foundation of China under Grant No.60372086the Foundation for the Author of National Excellent Doctoral Dissertation of China under Grant No.200753
文摘The problem of blind adaptive equalization of underwater single-input multiple-output (SIMO) acoustic channels was analyzed by using the linear prediction method.Minimum mean square error (MMSE) blind equalizers with arbitrary delay were described on a basis of channel identification.Two methods for calculating linear MMSE equalizers were proposed.One was based on full channel identification and realized using RLS adaptive algorithms,and the other was based on the zero-delay MMSE equalizer and realized using LMS and RLS adaptive algorithms,respectively.Performance of the three proposed algorithms and comparison with two existing zero-forcing (ZF) equalization algorithms were investigated by simulations utilizing two underwater acoustic channels.The results show that the proposed algorithms are robust enough to channel order mismatch.They have almost the same performance as the corresponding ZF algorithms under a high signal-to-noise (SNR) ratio and better performance under a low SNR.
文摘Numerical simulations are presented about the effects of gas rarefaction on hypersonic flow field.Due to the extremely difficult experiment,limited wind-tunnel conditions and high cost,most problems in rarefied flow regime are investigated through numerical methods,in which the direct simulation Monte-Carlo(DSMC)method is widely adopted.And the unstructured DSMC method is employed here.Flows around a vertical plate at a given velocity 7 500 m/s are simulated.For gas rarefaction is judged by the free-stream Knudsen number(Kn),two vital factors are considered:molecular number density and the plate′s length.Cases in which Kn varies from 0.035 to13.36 are simulated.Flow characters in the whole rarefied regime are described,and flow-field structure affected by Knis analyzed.Then,the dimensionless position D*of a certain velocity in the stagnation line is chosen as the marker of flow field to measure its variation.Through flow-field tracing and least-square numerical method analyzing,it is proved that hypersonic rarefied flow field expands outward linearly with the increase of 1/2Kn.An empirical method is proposed,which can be used for the prediction of the hypersonic flow-field structure at a given inflow velocity,especially the shock wave position.
基金National Natural Science Foundation of China(Grant Nos.11972177,11972122,11802103,11772144,11872030,and 11572034)the Scientific Research Starting Foundation for Scholars with Doctoral Degree of Guangdong Medical University(Grant Nos.B2019042 and B2019021).
文摘For conservative linear homogeneous nonholonomic systems, there exists a cotangent bundle with the symplectic structure dπμ∧ dξμ, in which the motion equations of the system can be written into the form of the canonical equations by the set of quasi-coordinates πμand quasi-momenta ξμ. The key to construct this cotangent bundle is to define a set of suitable quasi-coordinates πμby a first-order linear mapping, so that the reduced configuration space of the system is a Riemann space with no torsion. The Hamilton–Jacobi method for linear homogeneous nonholonomic systems is studied as an application of the quasi-canonicalization. The Hamilton–Jacobi method can be applied not only to Chaplygin nonholonomic systems, but also to non-Chaplygin nonholonomic systems. Two examples are given to illustrate the effectiveness of the quasi-canonicalization and the Hamilton–Jacobi method.
文摘目的科学评价芙蓉李果实成熟期间的营养品质,建立色度值表观特征与营养品质的关系。方法以福建省主栽品种芙蓉李为研究对象,对其成熟期间果糖、葡萄糖、蔗糖、苹果酸、奎尼酸、琥珀酸、柠檬酸、富马酸、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷、多酚、黄酮、类胡萝卜素等13个品质指标进行分析和综合评价。结果芙蓉李成熟期间,各品质指标的含量变化存在显著差异(P<0.05),综合运用相关分析、因子分析、绝对因子分析-多元线性回归(absolute principal component scores-multiple linear regression,APCS-MLR)分析筛选可反映芙蓉李综合品质的主要指标。因子分析提取出3个主因子,贡献率分别为52.677%、23.468%、11.649%,累计贡献率为87.794%。综合APCS-MLR等数理统计分析,主因子1主要对果糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷贡献较大,贡献率分别为53.00%、73.85%、55.54%;主因子2主要对蔗糖、富马酸、果糖、柠檬酸的贡献率较大,分别为28.26%、18.70%、16.14%、15.59%;主因子3主要对多酚(29.13%)和黄酮(28.28%)有较大贡献率;选取3个主因子总贡献率高于60%的果糖、葡萄糖、矢车菊素-3-芸香糖苷、矢车菊素-3-葡萄糖苷作为综合品质评价的主要指标。分别对已筛选出的4个主要评价指标与色度值进行多元线性逐步回归分析,建立4个主要指标与色度值的表观预测模型,各模型均具有较好的拟合度,预测值与实测值的均方根误差较小;进一步验证结果表明,通过色度值对4个指标的预测具有较高的可靠性和准确性。结论本研究筛选出的主要指标及预测模型可更加简单、便捷地评价芙蓉李果实成熟期间的综合品质。
