河南省是中国的农业大省,已经进入乡村振兴战略实施的重要阶段,农业高质量发展是推动乡村振兴的重要抓手,所以推动河南省农业高质量发展尤为紧迫。文章在研究河南省农业发展现状基础上,通过搜集数据,基于2012年~2021年的河南省农业发展的数据建立指标体系,从农业生产、经济效益和生态环境三个方面来测度农业高质量发展水平,运用熵值法对河南农业高质量发展影响数据进行测度分析。结果表明:2012年~2021年的河南省农业高质量发展综合评分呈上升趋势。为了推进农业高质量发展,河南省应该要通过完善设施建设,农业创新和农业可持续发展等方面来实现农业发展,根据相关实现路径来实现农业高质量发展的目标。Henan Province is a major agricultural province in China and has entered an important stage of implementing the rural revitalization strategy. Agricultural high-quality development is an important lever to promote rural revitalization, so promoting high-quality agricultural development in Henan Province is particularly urgent. Based on the study of the current situation of agricultural development in Henan Province, this paper collects data and establishes an index system based on the data of agricultural development in Henan Province from 2012 to 2021. It measures the level of agricultural high-quality development from three aspects of agricultural production, economic benefits, and ecological environment, and uses the entropy method to measure and analyze the impact data of Henan’s agricultural high-quality development. The results show that the comprehensive score of Henan’s agricultural high-quality development from 2012 to 2021 has an upward trend. To promote high-quality agricultural development, Henan should achieve agricultural development by improving infrastructure, agricultural innovation, and sustainable agricultural development, and achieve the goal of high-quality agricultural development by following relevant implementation paths.
针对现有基于深度确定性策略梯度(deep deterministic policy gradient,DDPG)算法的再入制导方法计算精度较差,对强扰动条件适应性不足等问题,在DDPG算法训练框架的基础上,提出一种基于长短期记忆-DDPG(long short term memory-DDPG,LST...
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针对现有基于深度确定性策略梯度(deep deterministic policy gradient,DDPG)算法的再入制导方法计算精度较差,对强扰动条件适应性不足等问题,在DDPG算法训练框架的基础上,提出一种基于长短期记忆-DDPG(long short term memory-DDPG,LSTM-DDPG)的再入制导方法。该方法采用纵、侧向制导解耦设计思想,在纵向制导方面,首先针对再入制导问题构建强化学习所需的状态、动作空间;其次,确定决策点和制导周期内的指令计算策略,并设计考虑综合性能的奖励函数;然后,引入LSTM网络构建强化学习训练网络,进而通过在线更新策略提升算法的多任务适用性;侧向制导则采用基于横程误差的动态倾侧反转方法,获得倾侧角符号。以美国超音速通用飞行器(common aero vehicle-hypersonic,CAV-H)再入滑翔为例进行仿真,结果表明:与传统数值预测-校正方法相比,所提制导方法具有相当的终端精度和更高的计算效率优势;与现有基于DDPG算法的再入制导方法相比,所提制导方法具有相当的计算效率以及更高的终端精度和鲁棒性。
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