ID 原文 译文
39646 为了解决大气环境极限承载力的计算问题，提出了大气环境极限承载力计算公式，并根据城市能源规划构建以“污染指标-能源”达标为约束的系统动力学模型，即PI-E-SD(Pollution Indicator-Energy-System Dynamics)模型。 In order to solve the calculation problem of the ultimate carrying capacity of the atmospheric environment, the calculation formula of the ultimate carrying capacity of the atmospheric environment is proposed, and the system dynamics model with the ‘pollution index-energy' compliance as the constraint is constructed according to the urban energy planning, namely the PI-E-SD(Pollution Indicator-Energy-System Dynamics) model.
39647 采用线性回归方法确定了污染指标，解决了指标不统一的问题； In this model, the linear regression method is used to determine the pollution index, which solves the non-uniformity problem.
39648 采用SD(System Dynamics)建模方法，构建了“能源-经济-环境”模拟系统，量化政府措施使得预测结果较为准确； The SD-modeling method is used to construct the “energy-economy-environment” simulation system, so that the government measures can be quantified to make the prediction result more accurate.
39649 通过改变控制因素调控极限承载力，便于快速寻找环境优化方案。 By adjusting the control factors to limit the ultimate carrying capacity, it is easy to quickly find an environmental optimization plan.
39650 结果表明，该模型具有良好的适应性可为不同城市在制定节能环保政策时提供参考。 The results show that the model has good adaptability and can provide reference for different cities in formulating energy conservation and environmental protection policies.
39651 为研究手枪弹入靶参数对带软防护人体钝击效应影响情况，基于人体上躯干数字模型，建立了手枪弹钝击带软防护人体上躯干的有限元计算模型，分别以3种入靶速度撞击心脏、肝脏、肺脏和胃4个部位，基于有限元法对手枪弹钝击带软防护人体上躯干的冲击响应进行数值计算， In order to research the blunt impact effect of target-entry parameters of pistol bullets, the finite element models of the soft upper body of the pistol blunt with a soft-protected human body are developed. By hitting the heart, lung, liver and stomach at three target-entry velocities, the impact response of pistol bullet impacting on human torso with soft armor is numerically calculated by finite element method.
39652 仿真结果定量揭示了手枪弹在不同入靶速度和位置下，钝性带防弹衣的人体产生损伤的压力传递机制及入靶参数对钝击效应影响规律，为软防护冲击效应分析与损伤评估提供了基本数据。 The simulation results quantitatively reveal the pressure transmission mechanism of the human body with blunt body armor at different target speeds and positions and the law of blunt impact response at different target entry parameters. The basic data are provided for impact effect analysis and damage assessment with soft armor.
39653 通过分析应急指挥模拟演练平台现状及发展需求，并结合大多数应急指挥案例场景的共性特点，设计提出了一种基于试验与训练使能体系结构(Test and Training Enabling Architecture， TENA)的应急指挥模拟演练平台架构，可多粒度、组件化地扩充灾害事故、承灾主体、上下级联动指挥组织机构、救援力量、自然环境等各类仿真模型，接入各类演练支撑和分析评估工具以及外部三维仿真、虚拟现实/增强现实装备模拟器等异构系统， Based on the analysis of the current situation and development needs of the emergency command simulation exercise platform and the common characteristics of most emergency command case scenarios, an emergency command simulation exercise platform architecture based on TENA(Test and Training Enabling Architecture) is designed and put forward, which can expand various simulation models such as disaster accidents, disaster-bearing subjects, higher-lower linkage command organizations, rescue forces, natural environment, etc. in a multi-granularity and modular manner, and interface with various exercise support and analysis evaluation tools, as well as heterogeneous systems such as external three-dimensional simulation, virtual reality/augmented reality equipment simulator, etc.
39654 跨地域实现指挥演练平台快速集成和实施，支撑验证指挥调度、资源调配等方面决策活动，能够为应急指挥辅助决策系统开发提供支撑。 It can realize rapid integration and implementation of command exercise platforms across regions, support and verify decision-making activities in command scheduling, resource allocation, etc., and can provide support for the development of emergency command assistant decision-making systems.
39655 针对情绪机器人的自动语音情感识别在不同类型人群之间的语音特征差异，提出了一种用于语音情感识别的随机森林，结合卷积特征学习对情绪化社交机器人系统进行了初步的仿真实验， Focus on the different speech features of different types of people in the automatic speech emotion recognition of emotional robots, a random forest for speech emotion recognition is proposed, and a preliminary simulation experiment of emotional social robot system based on convolution feature learning is carried out.