基于词性特征的明喻识别及要素抽取方法

比喻是一种利用事物之间的相似点建立关系的修辞方式。明喻是比喻中最常见的形式,具有明显的喻词,例如"像",用于关联本体和喻体。近年来高考语文散文类鉴赏题中多有考查明喻句的试题,为了解答此类鉴赏题,需要识别比喻句中的本体和喻体要素。该文提出了基于词性特征的明喻识别及要素抽取方法。首先将句子中词向量化表示与词性特征向量化表示进行融合,将融合后的向量输入到BiLSTM中进行训练,然后利用CRF解码出全局最优标注序列;最后得到明喻识别和要素抽取的结果。公开数据集上的实验结果表明,该方法优于已有的单任务方法;同时也将该文方法应用于北京高考语文鉴赏题中比喻句的识别与要素抽取,验证了方法的可行性。     

A practical assessment of risk-averse approaches in production lot-sizing problems

ABSTRACT

This paper presents an empirical assessment of four state-of-the-art risk-averse approaches to deal with the capacitated lot-sizing problem under stochastic demand. We analyse two mean-risk models based on the semideviation and on the conditional value-at-risk risk measures, and alternate first and second-order stochastic dominance approaches. The extensive computational experiments based on different instances characteristics and on a case-study suggest that CVaR exhibits a good trade-off between risk and performance, followed by the semideviation and first-order stochastic dominance approach. For all approaches, enforcing risk-aversion helps to reduce the cost-standard deviation substantially, which is usually accomplished via increasing production rates. Overall, we can say that very risk-averse decision-makers would be willing to pay an increased price to have a much less risky solution given by CVaR. In less risk-averse settings, though, semideviation and first-order stochastic dominance can be appealing alternatives to provide significantly more stable production planning costs with a marginal increase of the expected costs.     

两段式热脱焦油煤气炉在环形加热炉上的开发应用

介绍了两段式煤气发生炉热脱焦油煤气在无缝钢管环形加热炉上的开发与应用 ,以及两段式煤气发生炉热脱焦油煤气站的设计和采用热脱焦油煤气代替重油所产生的经济效益     

Second-law-based thermodynamic analysis of two-stage and mechanical-subcooling refrigeration cycles

Thermodynamic analysis of HFC-134a vapor-compression refrigeration cycles is investigated by both the first and second laws of thermodynamics. Second-law analysis is carried out for both two-stage and mechanical-subcooling refrigeration cycles. The analysis is performed on each of the system components to determine their individual contribution to the overall system irreversible losses. It is found that most of the losses are due to a low compressor efficiency. Irreversibilities of expansion valves and condenser are also significant. In addition, it is shown that the optimum inter-stage pressure for two-stage and mechanical-subcooling refrigeration systems is very close to the saturation pressure corresponding to the arithmetic mean of the refrigerant condensation and evaporation temperatures. These results are compared with the existing practice in the industry. Furthermore, theoretical results of a two-stage refrigeration system performance are also compared with experimental values for a CFC-22 system.     

Two-stage fatigue loading of woven carbon fibre reinforced laminates

A brief review of the models used to predict the cumulative fatigue damage in FRP composites is presented. Two‐stage fatigue loading of a [0/90,± 45₂,0/90]_s quasi‐ isotropic woven carbon fibre/epoxy resin laminate was evaluated at stress ratio R = 0.05 and the failure mechanisms investigated using x‐radiography after each loading stage. The results are presented in terms of fatigue strength and damage growth and are compared with those in the literature. A low‐to‐high loading sequence is more damaging than a high‐to‐low one and the Palmgren‐Miner linear damage rule may no longer be valid for this kind of material, as previously reported.     

基于BA-WPHM的滚动轴承两阶段剩余寿命预测方法

为了提高滚动轴承剩余寿命预测的准确性,根据滚动轴承运行过程的两阶段性特点,提出了一种基于蝙蝠算法(BA)和威布尔比例风险模型(WPHM)的滚动轴承两阶段剩余寿命预测方法。首先,构建基于WPHM的剩余寿命预测模型;其次,提出了两阶段极大似然估计法,建立新的似然函数,并利用BA算法进行求解,以提高参数估计的准确性;最后,建立BA-WPHM模型对滚动轴承进行剩余寿命预测。案例分析表明,相比于Newton-Raphson算法、自组织分层猴群算法(SHMA)和独特的自适应粒子群算法(UAPSO),提出的方法参数估计的准确性更高,剩余寿命的预测精度优于支持向量回归(SVR)方法,验证了所提方法的有效性,为滚动轴承维修决策的可行性提供了依据。     

基于改进U-net和CNN的绝缘子自爆检测方法研究

针对绝缘子自爆故障人工检测效率低,成本高的问题,基于改进U-net和卷积神经网络（CNN）模型,提出一种可有效识别绝缘子自爆故障的双阶段目标检测算法。首先,在语义分割阶段使用改进U-net模型,通过翻倍提高图像分辨率的方法有效提高图像分割精度。其次,在图像分类阶段提出更适合所提问题且有效提高分类准确度的新型CNN模型。最后,使用无人机拍摄的绝缘子图片为实验数据进行实验。实验结果表明所提算法识别精度较高。     

高比例可再生能源渗透下多虚拟电厂多时间尺度协调优化调度

考虑可再生能源出力、电力负荷和电价等一系列不确定性因素,提出了高比例可再生能源渗透下的多虚拟电厂日内两阶段优化调度模型。该模型通过对多虚拟电厂中运行设备小时级时间尺度和分钟级时间尺度的协调优化,达到分级消除系统中随机和扰动因素的影响,实现高比例可再生能源的安全消纳。并且在多虚拟电厂优化调度模型中,借助Markowitz均值-方差理论,提出利润函数的风险刻画,准确描述不确定性的影响。最后,通过算例分析,说明所提出模型可有效降低决策风险和不确定性因素的影响。     

考虑调峰辅助服务的虚拟电厂运营模式

针对虚拟电厂(VPP)内部风光资源的不确定性给其参与调峰市场带来影响的问题,对以VPP为主体参与调峰市场开展研究.采取VPP同时参与直接电力交易市场与调峰市场的运营模式,计及风光出力不确定性的影响,提出基于条件风险价值理论的VPP日前优化运行模型;利用Shapley值法对各成员联合运行后取得的期望成本进行合理分配.算例仿真验证了所提运行策略的有效性与合理性.