Taking the nonlinear nature of runoff system into account,and combining auto-regression method and multi-regression method,a Nonlinear Mixed Regression Model (NMR) was established to analyze the impact of temperature ...Taking the nonlinear nature of runoff system into account,and combining auto-regression method and multi-regression method,a Nonlinear Mixed Regression Model (NMR) was established to analyze the impact of temperature and precipitation changes on annual river runoff process. The model was calibrated and verified by using BP neural network with observed meteorological and runoff data from Daiying Hydrological Station in the Chaohe River of Hebei Province in 1956–2000. Compared with auto-regression model,linear multi-regression model and linear mixed regression model,NMR can improve forecasting precision remarkably. Therefore,the simulation of climate change scenarios was carried out by NMR. The results show that the nonlinear mixed regression model can simulate annual river runoff well.展开更多
Changes in tree mortality due to severe drought can alter forest structure,composition,dynamics,ecosystem services,carbon fl uxes,and energy interactions between the atmosphere and land surfaces.We utilized long-term(...Changes in tree mortality due to severe drought can alter forest structure,composition,dynamics,ecosystem services,carbon fl uxes,and energy interactions between the atmosphere and land surfaces.We utilized long-term(2000‒2017,3 full inventory cycles)Forest Inventory and Analysis(FIA)data to examine tree mortality and biomass loss in drought-aff ected forests for East Texas,USA.Plots that experienced six or more years of droughts during those censuses were selected based on 12-month moderate drought severity[Standardized Precipitation Evaporation Index(SPEI)-1.0].Plots that experienced other disturbances and inconsistent records were excluded from the analysis.In total,222 plots were retained from nearly 4000 plots.Generalized nonlinear mixed models(GNMMs)were used to examine the changes in tree mortality and recruitment rates for selected plots.The results showed that tree mortality rates and biomass loss to mortality increased overall,and across tree sizes,dominant genera,height classes,and ecoregions.An average mortality rate of 5.89%year−1 during the study period could be incited by water stress created by the regional prolonged and episodic drought events.The overall plot and species-group level recruitment rates decreased during the study period.Forest mortality showed mixed results regarding basal area and forest density using all plots together and when analyzed the plots by stand origin and ecoregion.Higher mortality rates of smaller trees were detected and were likely compounded by densitydependent factors.Comparative analysis of drought-induced tree mortality using hydro-meteorological data along with drought severity and length gradient is suggested to better understand the eff ects of drought on tree mortality and biomass loss around and beyond East Texas in the southeastern United States.展开更多
The multi-stream heat exchanger network synthesis (HENS) problem can be formulated as a mixed integer nonlinear programming model according to Yee et al. Its nonconvexity nature leads to existence of more than one opt...The multi-stream heat exchanger network synthesis (HENS) problem can be formulated as a mixed integer nonlinear programming model according to Yee et al. Its nonconvexity nature leads to existence of more than one optimum and computational difficulty for traditional algorithms to find the global optimum. Compared with deterministic algorithms, evolutionary computation provides a promising approach to tackle this problem. In this paper, a mathematical model of multi-stream heat exchangers network synthesis problem is setup. Different from the assumption of isothermal mixing of stream splits and thus linearity constraints of Yee et al., non-isothermal mixing is supported. As a consequence, nonlinear constraints are resulted and nonconvexity of the objective function is added. To solve the mathematical model, an algorithm named GA/SA (parallel genetic/simulated annealing algorithm) is detailed for application to the multi-stream heat exchanger network synthesis problem. The performance of the proposed approach is demonstrated with three examples and the obtained solutions indicate the presented approach is effective for multi-stream HENS.展开更多
Commercial airline companies are continuously seeking to implement strategies for minimizing costs of fuel for their flight routes as acquiring jet fuel represents a significant part of operating and managing expenses...Commercial airline companies are continuously seeking to implement strategies for minimizing costs of fuel for their flight routes as acquiring jet fuel represents a significant part of operating and managing expenses for airline activities.A nonlinear mixed binary mathematical programming model for the airline fuel task is presented to minimize the total cost of refueling in an entire flight route problem.The model is enhanced to include possible discounts in fuel prices,which are performed by adding dummy variables and some restrictive constraints,or by fitting a suitable distribution function that relates prices to purchased quantities.The obtained fuel plan explains exactly the amounts of fuel in gallons to be purchased from each airport considering tankering strategy while minimizing the pertinent cost of the whole flight route.The relation between the amount of extra burnt fuel taken through tinkering strategy and the total flight time is also considered.A case study is introduced for a certain flight rotation in domestic US air transport route.The mathematical model including stepped discounted fuel prices is formulated.The problem has a stochastic nature as the total flight time is a random variable,the stochastic nature of the problem is realistic and more appropriate than the deterministic case.The stochastic style of the problem is simulated by introducing a suitable probability distribution for the flight time duration and generating enough number of runs to mimic the probabilistic real situation.Many similar real application problems are modelled as nonlinear mixed binary ones that are difficult to handle by exact methods.Therefore,metaheuristic approaches are widely used in treating such different optimization tasks.In this paper,a gaining sharing knowledge-based procedure is used to handle the mathematical model.The algorithm basically based on the process of gaining and sharing knowledge throughout the human lifetime.The generated simulation runs of the example are solved using the proposed algorithm,and the resulting distribution outputs for the optimum purchased fuel amounts from each airport and for the total cost and are obtained.展开更多
基金Under the auspices of National Natural Science Foundation of China (No. 50809004)
文摘Taking the nonlinear nature of runoff system into account,and combining auto-regression method and multi-regression method,a Nonlinear Mixed Regression Model (NMR) was established to analyze the impact of temperature and precipitation changes on annual river runoff process. The model was calibrated and verified by using BP neural network with observed meteorological and runoff data from Daiying Hydrological Station in the Chaohe River of Hebei Province in 1956–2000. Compared with auto-regression model,linear multi-regression model and linear mixed regression model,NMR can improve forecasting precision remarkably. Therefore,the simulation of climate change scenarios was carried out by NMR. The results show that the nonlinear mixed regression model can simulate annual river runoff well.
文摘Changes in tree mortality due to severe drought can alter forest structure,composition,dynamics,ecosystem services,carbon fl uxes,and energy interactions between the atmosphere and land surfaces.We utilized long-term(2000‒2017,3 full inventory cycles)Forest Inventory and Analysis(FIA)data to examine tree mortality and biomass loss in drought-aff ected forests for East Texas,USA.Plots that experienced six or more years of droughts during those censuses were selected based on 12-month moderate drought severity[Standardized Precipitation Evaporation Index(SPEI)-1.0].Plots that experienced other disturbances and inconsistent records were excluded from the analysis.In total,222 plots were retained from nearly 4000 plots.Generalized nonlinear mixed models(GNMMs)were used to examine the changes in tree mortality and recruitment rates for selected plots.The results showed that tree mortality rates and biomass loss to mortality increased overall,and across tree sizes,dominant genera,height classes,and ecoregions.An average mortality rate of 5.89%year−1 during the study period could be incited by water stress created by the regional prolonged and episodic drought events.The overall plot and species-group level recruitment rates decreased during the study period.Forest mortality showed mixed results regarding basal area and forest density using all plots together and when analyzed the plots by stand origin and ecoregion.Higher mortality rates of smaller trees were detected and were likely compounded by densitydependent factors.Comparative analysis of drought-induced tree mortality using hydro-meteorological data along with drought severity and length gradient is suggested to better understand the eff ects of drought on tree mortality and biomass loss around and beyond East Texas in the southeastern United States.
基金Supported by the Deutsche Forschungsgemeinschaft (DFG No. RO294/9).
文摘The multi-stream heat exchanger network synthesis (HENS) problem can be formulated as a mixed integer nonlinear programming model according to Yee et al. Its nonconvexity nature leads to existence of more than one optimum and computational difficulty for traditional algorithms to find the global optimum. Compared with deterministic algorithms, evolutionary computation provides a promising approach to tackle this problem. In this paper, a mathematical model of multi-stream heat exchangers network synthesis problem is setup. Different from the assumption of isothermal mixing of stream splits and thus linearity constraints of Yee et al., non-isothermal mixing is supported. As a consequence, nonlinear constraints are resulted and nonconvexity of the objective function is added. To solve the mathematical model, an algorithm named GA/SA (parallel genetic/simulated annealing algorithm) is detailed for application to the multi-stream heat exchanger network synthesis problem. The performance of the proposed approach is demonstrated with three examples and the obtained solutions indicate the presented approach is effective for multi-stream HENS.
基金The research is funded by Deanship of Scientific Research at King Saud University research group number RG-1436-040.
文摘Commercial airline companies are continuously seeking to implement strategies for minimizing costs of fuel for their flight routes as acquiring jet fuel represents a significant part of operating and managing expenses for airline activities.A nonlinear mixed binary mathematical programming model for the airline fuel task is presented to minimize the total cost of refueling in an entire flight route problem.The model is enhanced to include possible discounts in fuel prices,which are performed by adding dummy variables and some restrictive constraints,or by fitting a suitable distribution function that relates prices to purchased quantities.The obtained fuel plan explains exactly the amounts of fuel in gallons to be purchased from each airport considering tankering strategy while minimizing the pertinent cost of the whole flight route.The relation between the amount of extra burnt fuel taken through tinkering strategy and the total flight time is also considered.A case study is introduced for a certain flight rotation in domestic US air transport route.The mathematical model including stepped discounted fuel prices is formulated.The problem has a stochastic nature as the total flight time is a random variable,the stochastic nature of the problem is realistic and more appropriate than the deterministic case.The stochastic style of the problem is simulated by introducing a suitable probability distribution for the flight time duration and generating enough number of runs to mimic the probabilistic real situation.Many similar real application problems are modelled as nonlinear mixed binary ones that are difficult to handle by exact methods.Therefore,metaheuristic approaches are widely used in treating such different optimization tasks.In this paper,a gaining sharing knowledge-based procedure is used to handle the mathematical model.The algorithm basically based on the process of gaining and sharing knowledge throughout the human lifetime.The generated simulation runs of the example are solved using the proposed algorithm,and the resulting distribution outputs for the optimum purchased fuel amounts from each airport and for the total cost and are obtained.
