一种基于混合决策树的调度知识获取算法*

提出了一种基于混合决策树的调度知识获取算法。将模拟退火算法融入遗传算法中,作为一种具有自适应变概率的变异操作,构成一种混合优化方法。利用这种混合方法求解在不同调度目标下制造系统的最优特征子集,同时确定控制决策树规模的最优参数;使用决策树评价混合方法中染色体编码的适应度,在得到不同调度目标下的最优特征子集和最优决策树参数后,生成调度知识。仿真实验结果表明,该算法在性能上优于其他算法。     

电力配电网单相接地故障选线技术的发展

作为供电系统中的重要部分,电力配电网的重要性毋庸置疑。从实际情况来看单相接地故障是配电网建设与使用过程中经常出现的问题,要求专业人员提高对选线环节的重视,选择应用多种科学的选线方法以从根本上降低单相接地故障的发生风险。本文阐述了常见的几种故障选线方法,并就每一种线型的特性进行了分析。     

负荷功率模型的最优特征选择研究

负荷功率呈现时空多样的变化特性,其影响因素众多,构建负荷功率模型的关键之一是确定模型的输入特征量。文中着重研究短期负荷功率模型的特征选择,旨在从历史负荷、气象、日期等众多特征中选出最优特征集。首先,采用最大信息系数、基于支持向量机的递归特征消除法和随机森林3种不同特征选择方法分别对输入特征集进行选择;然后,根据对比分析结果提出基于遗传算法的最优特征集搜索策略,选定XGBoost预测模型的误差指标作为适应性函数进行迭代优化搜索;最终,确定负荷功率模型的最优特征输入集。采用某地区220 kV变电站母线负荷数据进行算例分析,对比各方法所选特征集作为功率模型输入得到的负荷预测效果,验证了文中方法的有效性和准确性。     

磷酸浓缩氟吸收问题的探讨

将我国现有的几种磷酸浓缩流程和实际应用效果进行比较 ,并从氟吸收机理分析探讨氟吸收级数与吸收效率的关系 ;氟硅酸浓度、温度与吸收效率的关系 ;吸收设备和雾沫分离器选型等     

Tasting green leaf volatiles by larvae and adults of Colorado potato beetle,Leptinotarsa decemlineata

Larvae and adults of the Colorado potato beetle,Leptinotarsa decemlineata (Say), are shown to have galeal gustatory cells that are highly sensitive to distillate of potato leaf extracts, (E)-2-hexen-1-ol, (E)-2-hexenal, and other saturated and unsaturated six-carbon alcohols. In larvae and adults, the sensory response patterns elicited by leaf homogenate, leaf distillate and a mixture of these two extracts differ in subtle ways. Beetle larvae feed most readily on Millipore disks treated with leaf homogenate and the mixture, but they did not feed on disks treated with leaf distillate. The differences in behavioral response and sensory input are used to derive a potential gustatory code that may stimulate different levels of feeding. This code may be disrupted by compounds present in nonhost leaves, thus leading to reduced feeding. Possible interactions of sapid leaf volatiles, amino acids, sugars, and potentially deterrent plant compounds are discussed.     

PRO/Ⅱ软件在硫磺回收中的二次开发应用

硫磺回收装置的设备需要有较大的操作弹性。针对其过程气进口压力低，手工计算难于进行严格的全程压降计算，现以PRO／Ⅱ软件为开发平台，通过扩充数据库和建立模拟流程，成功地将其用于硫磺回收装置的设备选型和核算，为工程设计提供了先进的计算手段。     

Maximum principle for mean-field jump–diffusion stochastic delay differential equations and its application to finance

This paper investigates a stochastic optimal control problem with delay and of mean-field type, where the controlled state process is governed by a mean-field jump–diffusion stochastic delay differential equation. Two sufficient maximum principles and one necessary maximum principle are established for the underlying system. As an application, a bicriteria mean–variance portfolio selection problem with delay is studied to demonstrate the effectiveness and potential of the proposed techniques. Under certain conditions, explicit expressions are provided for the efficient portfolio and the efficient frontier, which are as elegant as those in the classical mean–variance problem without delays.     

ESTIMATION OF THE PREDICTION ERROR VARIANCE AND AN R2 MEASURE BY AUTOREGRESSIVE MODEL FITTING

Abstract. For predicting the future values of a stationary process { x_t } ( t = 0, pL 1, pL 2,…) on the basis of its past, two key parameters are the variance V ( h ), h ≥ 1, of the h -step prediction error and Z ( h ) ={ R (0) - V ( h )}/ R (0), the corresponding measure, in an R ² sense, of the predictability of the process from its past, where R (0) denotes the process variance. The estimation of V ( h ) and Z ( h ) from a realization of T consecutive observations of { x_t } is considered, without requiring that the process follows a finite parameter model. Three different autoregressive estimators are examined and are shown to be asymptotically equivalent in the sense that as T ∝ they have the same asymptotic normal distribution. The question of bias in estimating these parameters is also examined and a bias correction is proposed. Finite sample behaviour is investigated by a simulation study.     

Efficient data selection for speech recognition based on prior confidence estimation using speech and monophone models

This paper proposes an efficient speech data selection technique that can identify those data that will be well recognized. Conventional confidence measure techniques can also identify well-recognized speech data. However, those techniques require a lot of computation time for speech recognition processing to estimate confidence scores. Speech data with low confidence should not go through the time-consuming recognition process since they will yield erroneous spoken documents that will eventually be rejected. The proposed technique can select the speech data that will be acceptable for speech recognition applications. It rapidly selects speech data with high prior confidence based on acoustic likelihood values and using only speech and monophone models. Experiments show that the proposed confidence estimation technique is over 50 times faster than the conventional posterior confidence measure while providing equivalent data selection performance for speech recognition and spoken document retrieval.     

离子选择电极法测定陶瓷工业废水的含氟量

本文采用氟离子选择电极法,该法具有测定简便、快速、灵敏、选择性好、可测定浑浊、有色样品等优点,最低检出浓度为0.05mg/L,适用浓度范围宽,在测定含陶瓷工业废水氟量中取得良好效果。