The Negative Binomial Multiple Change Point Algorithm is a hybrid change detection and estimation approach that works well for overdispersed and equidispersed count data. This simulation study assesses the performance...The Negative Binomial Multiple Change Point Algorithm is a hybrid change detection and estimation approach that works well for overdispersed and equidispersed count data. This simulation study assesses the performance of the NBMCPA under varying sample sizes and locations of true change points. Various performance metrics are calculated based on the change point estimates and used to assess how well the model correctly identifies change points. Errors in estimation of change points are obtained as absolute deviations of known change points from the change points estimated under the algorithm. Algorithm robustness is evaluated through error analysis and visualization techniques including kernel density estimation and computation of metrics such as change point location accuracy, precision, sensitivity and false positive rate. The results show that the model consistently detects change points that are present and does not erroneously detect changes where there are none. Change point location accuracy and precision of the NBMCPA increases with sample size, with best results for medium and large samples. Further model accuracy and precision are highest for changes located in the middle of the dataset compared to changes located in the periphery.展开更多
Forest carbon sinks are crucial for mitigating urban climate change.Their effectiveness depends on the balance between gross carbon losses and gains.However,quantitative and continuous monitoring of forest change/dist...Forest carbon sinks are crucial for mitigating urban climate change.Their effectiveness depends on the balance between gross carbon losses and gains.However,quantitative and continuous monitoring of forest change/disturbance carbon fluxes is still insufficient.To address this gap,we integrated an improved spatial carbon bookkeeping(SBK)model with the continuous change detection and classification(CCDC)algorithm,long-term Landsat observations,and ground measurements to track carbon emissions,uptakes,and net changes from forest cover changes in the Yangtze River Delta(YRD)of China from 2000 to 2020.The SBK model was refined by incorporating heterogeneous carbon response functions.Our results reveal that carbon emissions(-3.88 Tg C·year^(-1))were four times greater than carbon uptakes(0.93 Tg C·year^(-1))from forest cover changes in the YRD during 2000-2020,despite a net forest cover gain of 10.95×10^(4) ha.These findings indicate that the carbon effect per hectare of forest cover loss is approximately 4.5 times that of forest cover gain.The asymmetric carbon effect suggests that forest cover change may act as a carbon source even with net-zero or net-positive forest cover change.Furthermore,carbon uptakes from forest gains in the YRD during 2000-2020 could only offset 0.28% of energy-related carbon emissions from 2000 to 2019.Urban and agricultural expansions accounted for 37% and 10% of carbon emissions,respectively,while the Grain for Green Project contributed to 45% of carbon uptakes.Our findings underscore the necessity of understanding the asymmetric carbon effects of forest cover loss and gain to accurately assess the capacity of forest carbon sinks.展开更多
Heat exchangers are widely used in the process engineering such as the chemical industries, the petroleum industries, and the HVAC applications etc. An optimally designed heat exchanger cannot only help the optimizati...Heat exchangers are widely used in the process engineering such as the chemical industries, the petroleum industries, and the HVAC applications etc. An optimally designed heat exchanger cannot only help the optimization of the equipment size but also the reduction of the power consumption. In this paper, a new optimization approach called algorithms of changes (AOC) is proposed for design and optimization of the shell-tube heat exchanger. This new optimization technique is developed based on the concept of the book of changes (I Ching) which is one of the oldest Chinese classic texts. In AOC, the hexagram operations in I Ching are generalized to binary string case and an iterative process, which imitates the I Ching inference, is defined. Before applying the AOC to the heat exchanger design problem, the new optimization method is examined by the benchmark optimization problems such as the global optimization test functions and the travelling salesman problem (TSP). Based on the TSP results, the AOC is shown to be superior to the genetic algorithms (GA). The AOC is then used in the optimal design of heat exchanger. The shell inside diameter, tube outside diameter, and baffles spacing are treated as the design (or optimized) variables. The cost of the heat exchanger is arranged as the objective function. For the heat exchanger design problem, the results show that the AOC is comparable to the GA method. Both methods can find the optimal solution in a short period of time.展开更多
文摘The Negative Binomial Multiple Change Point Algorithm is a hybrid change detection and estimation approach that works well for overdispersed and equidispersed count data. This simulation study assesses the performance of the NBMCPA under varying sample sizes and locations of true change points. Various performance metrics are calculated based on the change point estimates and used to assess how well the model correctly identifies change points. Errors in estimation of change points are obtained as absolute deviations of known change points from the change points estimated under the algorithm. Algorithm robustness is evaluated through error analysis and visualization techniques including kernel density estimation and computation of metrics such as change point location accuracy, precision, sensitivity and false positive rate. The results show that the model consistently detects change points that are present and does not erroneously detect changes where there are none. Change point location accuracy and precision of the NBMCPA increases with sample size, with best results for medium and large samples. Further model accuracy and precision are highest for changes located in the middle of the dataset compared to changes located in the periphery.
基金supported by the Natural Science Foundation of Zhejiang Province(No.ZCLQN25C0301)the National Key Research and Development Program of China(No.2016YFC0502700)the General Program of Education Department of Zhejiang(No.23056209-F).
文摘Forest carbon sinks are crucial for mitigating urban climate change.Their effectiveness depends on the balance between gross carbon losses and gains.However,quantitative and continuous monitoring of forest change/disturbance carbon fluxes is still insufficient.To address this gap,we integrated an improved spatial carbon bookkeeping(SBK)model with the continuous change detection and classification(CCDC)algorithm,long-term Landsat observations,and ground measurements to track carbon emissions,uptakes,and net changes from forest cover changes in the Yangtze River Delta(YRD)of China from 2000 to 2020.The SBK model was refined by incorporating heterogeneous carbon response functions.Our results reveal that carbon emissions(-3.88 Tg C·year^(-1))were four times greater than carbon uptakes(0.93 Tg C·year^(-1))from forest cover changes in the YRD during 2000-2020,despite a net forest cover gain of 10.95×10^(4) ha.These findings indicate that the carbon effect per hectare of forest cover loss is approximately 4.5 times that of forest cover gain.The asymmetric carbon effect suggests that forest cover change may act as a carbon source even with net-zero or net-positive forest cover change.Furthermore,carbon uptakes from forest gains in the YRD during 2000-2020 could only offset 0.28% of energy-related carbon emissions from 2000 to 2019.Urban and agricultural expansions accounted for 37% and 10% of carbon emissions,respectively,while the Grain for Green Project contributed to 45% of carbon uptakes.Our findings underscore the necessity of understanding the asymmetric carbon effects of forest cover loss and gain to accurately assess the capacity of forest carbon sinks.
基金supported by Science and Technology Development Fund of Macao SAR (Grant No. 033/2008/A2)Research Grant of University of Macao, China (Grant No. RG081/09-10S/TSC/FST)
文摘Heat exchangers are widely used in the process engineering such as the chemical industries, the petroleum industries, and the HVAC applications etc. An optimally designed heat exchanger cannot only help the optimization of the equipment size but also the reduction of the power consumption. In this paper, a new optimization approach called algorithms of changes (AOC) is proposed for design and optimization of the shell-tube heat exchanger. This new optimization technique is developed based on the concept of the book of changes (I Ching) which is one of the oldest Chinese classic texts. In AOC, the hexagram operations in I Ching are generalized to binary string case and an iterative process, which imitates the I Ching inference, is defined. Before applying the AOC to the heat exchanger design problem, the new optimization method is examined by the benchmark optimization problems such as the global optimization test functions and the travelling salesman problem (TSP). Based on the TSP results, the AOC is shown to be superior to the genetic algorithms (GA). The AOC is then used in the optimal design of heat exchanger. The shell inside diameter, tube outside diameter, and baffles spacing are treated as the design (or optimized) variables. The cost of the heat exchanger is arranged as the objective function. For the heat exchanger design problem, the results show that the AOC is comparable to the GA method. Both methods can find the optimal solution in a short period of time.
