Considering chaotic time series multi-step prediction, multi-step direct prediction model based on partial least squares （PLS） is proposed in this article, where PLS, the method for predicting a set of dependent var...Considering chaotic time series multi-step prediction, multi-step direct prediction model based on partial least squares （PLS） is proposed in this article, where PLS, the method for predicting a set of dependent variables forming a large set of predictors, is used to model the dynamic evolution between the space points and the corresponding future points. The model can eliminate error accumulation with the common single-step local model algorithm~ and refrain from the high multi-collinearity problem in the reconstructed state space with the increase of embedding dimension. Simulation predictions are done on the Mackey-Glass chaotic time series with the model. The satisfying prediction accuracy is obtained and the model efficiency verified. In the experiments, the number of extracted components in PLS is set with cross-validation procedure.展开更多
In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the PO...In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the POMDP framework. The elements of the POMDP model are analyzed and described. The state transfer law in the model can be described by the method of interactive multiple model (IMM) due to the diversity of the target motion law, which is used to switch the motion model to accommodate target maneuvers, and hence improving the tracking accuracy. The simulation results show that the model can achieve efficient planning for the UAV route, and effective tracking for the target. Furthermore, the path planned by this model is more reasonable and efficient than that by using the single state transition law.展开更多
在气候变化背景下,模拟土壤侵蚀的时空演变特征并探讨其与气候因子之间的响应,对于应对气候变化和防灾减灾具有重要意义。现有研究主要聚焦于气候变化、坡度及植被恢复等因素对黄土高原土壤侵蚀的影响,但较少同时考虑各驱动因子之间的...在气候变化背景下,模拟土壤侵蚀的时空演变特征并探讨其与气候因子之间的响应,对于应对气候变化和防灾减灾具有重要意义。现有研究主要聚焦于气候变化、坡度及植被恢复等因素对黄土高原土壤侵蚀的影响,但较少同时考虑各驱动因子之间的相互作用及其对土壤侵蚀的直接与间接影响。基于气象站点、土地利用/土地覆被和土壤质地等数据,采用Theil⁃Sen Median趋势和Mann⁃Kendal检验对气候因子的时空变化特征进行了分析,利用InVEST(Integrated Valuation of Ecosystem Services and Tradeoffs)模型模拟了1990年、2000年、2010年和2020年黄土高原土壤侵蚀的时空分布,并通过最优参数地理探测器和偏最小二乘结构方程模型在考虑自然因子和植被因子的基础上,重点对气候因子对土壤侵蚀的影响强度和路径进行分析。结果表明:气候因子时空变化具有阶段性和区域性,降水量在1990—2000年以-55.96 mm/10a的速率下降,而2000—2020年以53.99 mm/10a的速率上升;研究期内年降水量、降水强度指数、大雨日数、强降水量、平均气温和最低气温的增长率分别为26.15 mm/10a、0.26 mm d^(-1)10a^(-1)、0.56 d/10a、15.21 mm/10a、0.32℃/10a和0.40℃/10a。从空间上看,1990—2000年降水量减少区域为86.36%,而2000年以后增加区域达97.42%;2000—2020年,极端降水指标在整个研究区基本为增加;气温上升区域主要分布在东、西部,气候变化呈现明显的暖湿化趋势且降水的极端性增强。1990—2020年,黄土高原土壤侵蚀模数呈现先减少再增加趋势,2020年土壤侵蚀量为2.19亿t。最优参数地理探测器分析显示,坡度、降水和植被覆盖是土壤侵蚀的主要驱动因素,其中降水量对土壤侵蚀的解释力从1990年的0.11在2020年增至0.18。结合偏最小二乘结构方程模型分析结果,温度主要通过影响降水间接影响土壤侵蚀,降水和自然因子对土壤侵蚀有直接正贡献,而植被因子对土壤侵蚀有直接负贡献,但2020年比2010年降低0.02。因此,在气候暖湿化和降水极端化趋势下,其对土壤侵蚀的影响不可忽视,在未来的土壤侵蚀防控和可持续发展中,需将气候适应和区域发展相结合,以应对未来气候变化的挑战。展开更多
文摘Considering chaotic time series multi-step prediction, multi-step direct prediction model based on partial least squares （PLS） is proposed in this article, where PLS, the method for predicting a set of dependent variables forming a large set of predictors, is used to model the dynamic evolution between the space points and the corresponding future points. The model can eliminate error accumulation with the common single-step local model algorithm~ and refrain from the high multi-collinearity problem in the reconstructed state space with the increase of embedding dimension. Simulation predictions are done on the Mackey-Glass chaotic time series with the model. The satisfying prediction accuracy is obtained and the model efficiency verified. In the experiments, the number of extracted components in PLS is set with cross-validation procedure.
基金supported by the Aeronautical Science Foundation of China(20135153031 20135553035 2017ZC53033)
文摘In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the POMDP framework. The elements of the POMDP model are analyzed and described. The state transfer law in the model can be described by the method of interactive multiple model (IMM) due to the diversity of the target motion law, which is used to switch the motion model to accommodate target maneuvers, and hence improving the tracking accuracy. The simulation results show that the model can achieve efficient planning for the UAV route, and effective tracking for the target. Furthermore, the path planned by this model is more reasonable and efficient than that by using the single state transition law.
文摘在气候变化背景下,模拟土壤侵蚀的时空演变特征并探讨其与气候因子之间的响应,对于应对气候变化和防灾减灾具有重要意义。现有研究主要聚焦于气候变化、坡度及植被恢复等因素对黄土高原土壤侵蚀的影响,但较少同时考虑各驱动因子之间的相互作用及其对土壤侵蚀的直接与间接影响。基于气象站点、土地利用/土地覆被和土壤质地等数据,采用Theil⁃Sen Median趋势和Mann⁃Kendal检验对气候因子的时空变化特征进行了分析,利用InVEST(Integrated Valuation of Ecosystem Services and Tradeoffs)模型模拟了1990年、2000年、2010年和2020年黄土高原土壤侵蚀的时空分布,并通过最优参数地理探测器和偏最小二乘结构方程模型在考虑自然因子和植被因子的基础上,重点对气候因子对土壤侵蚀的影响强度和路径进行分析。结果表明:气候因子时空变化具有阶段性和区域性,降水量在1990—2000年以-55.96 mm/10a的速率下降,而2000—2020年以53.99 mm/10a的速率上升;研究期内年降水量、降水强度指数、大雨日数、强降水量、平均气温和最低气温的增长率分别为26.15 mm/10a、0.26 mm d^(-1)10a^(-1)、0.56 d/10a、15.21 mm/10a、0.32℃/10a和0.40℃/10a。从空间上看,1990—2000年降水量减少区域为86.36%,而2000年以后增加区域达97.42%;2000—2020年,极端降水指标在整个研究区基本为增加;气温上升区域主要分布在东、西部,气候变化呈现明显的暖湿化趋势且降水的极端性增强。1990—2020年,黄土高原土壤侵蚀模数呈现先减少再增加趋势,2020年土壤侵蚀量为2.19亿t。最优参数地理探测器分析显示,坡度、降水和植被覆盖是土壤侵蚀的主要驱动因素,其中降水量对土壤侵蚀的解释力从1990年的0.11在2020年增至0.18。结合偏最小二乘结构方程模型分析结果,温度主要通过影响降水间接影响土壤侵蚀,降水和自然因子对土壤侵蚀有直接正贡献,而植被因子对土壤侵蚀有直接负贡献,但2020年比2010年降低0.02。因此,在气候暖湿化和降水极端化趋势下,其对土壤侵蚀的影响不可忽视,在未来的土壤侵蚀防控和可持续发展中,需将气候适应和区域发展相结合,以应对未来气候变化的挑战。
