基于多层感知器的气液两相流流型识别方法

通过对电阻层析成像数据采集原理和深度学习网络的研究,提出了一种基于阵列电阻值和多层感知器深度学习网络相结合的流型识别方法。利用电阻层析成像系统中的16个电极传感器来获取流型样本数据,并构建出流型识别数据库,然后对多层感知器深度学习网络进行训练,获得可以识别不同流型的网络。实验结果表明,采用阵列电阻值结合多层感知器网络对流型进行学习和识别的方法,流型识别准确率可以达到95%,解决了流型图像生成过程与数据特征预选过程中流型特征损失的问题,流型识别性能得到了提高。     

基于峰谷分时电价的虚拟电厂日前申报及运行优化

鉴于分布式能源的出力性质为间歇性和波动性,影响电网安全高效运行,而虚拟电厂可解决此问题。对虚拟电厂进行申报-调度两阶段建模,以包含分布式电源(光电、风电和燃气轮机)和储能系统(储能电池)两大类分布式能源的虚拟电厂为例,基于光照强度及风速等不确定因素,研究峰谷分时电价下日前市场虚拟电厂的出力申报和运行调度策略并利用风险价值模型进行风险管理。结果表明,申报出力时,当电价激励足够高时储能电池方会参与出力,成功起到削峰填谷的作用;运行调度时,平衡出力偏差方面,储能电池发挥主要作用,且虚拟电厂运行调度策略具有一定的经济效益。     

一种军棋机器博弈的多棋子协同博弈方法

针对在军棋博弈不完全信息对弈中，面对棋子不同价值、不同位置、不同搭配所产生的不同棋力，传统的单子意图搜索算法，不能满足棋子之间的协同性与沟通性，同时也缺乏对敌方的引诱与欺骗等高级对抗能力。本文提出一种结合UCT搜索策略的高价值棋子博弈方法，实现高价值棋子协同博弈的策略。实战经验表明:高价值多棋子军棋协同博弈策略优于单棋子军棋博弈策略。     

花椒风味油的制取及品质研究

以花椒果皮为原料,采用大豆油热浸法制取花椒风味油。以花椒风味油的酸价、过氧化值和感官评分为考察指标,通过单因素实验和正交实验优化制取工艺条件。采用顶空固相微萃取-气相色谱-质谱联用技术对花椒风味油和大豆油中挥发性风味成分进行测定。结果表明:制取花椒风味油的最佳工艺条件为浸提温度95℃、浸提时间20 min、花椒果皮添加量15%,在此条件下制取的花椒风味油香气浓郁、麻味足、色泽好且感官评分最高,其酸价(KOH)为0. 40 mg/g,过氧化值为5. 07 mmol/kg,感官评分为9. 1。花椒风味油中维生素E总量为1 869. 86 mg/kg,远高于大豆油中的742. 07 mg/kg;甾醇含量相较于大豆油几乎不变;脂肪酸组成与大豆油的基本相同;花椒风味油中共鉴定出9类83种挥发性风味成分,大豆油中共鉴定出8类25种挥发性风味成分,花椒风味油中挥发性风味成分主要是烯烃类和醇类(相对含量86. 99%),大豆油中主要是烯烃类和醛类(相对含量87. 26%);花椒风味油中醇类18种,占总量的40. 97%,大豆油中醇类仅1种,占总量的1. 74%;花椒风味油中醛类物质含量仅为1. 91%,而大豆油中醛类物质含量为12. 69%。     

自动捕捉平衡系数试验电流工具设计

在电梯平衡系数传统测量方法中,存在电梯轿厢和对重平衡点难以判断、人为因素导致测量误差偏大、测量不准导致效率低等问题,为解决这些问题,设计出一款基于光电传感器和霍尔传感器的电流自动捕捉工具,除能够高效准确识别电梯轿厢和对重平衡点的位置外,还能通过无线信号传输处理,利用钳形电流表精确捕捉平衡点位置的电流值。经测试使用,该工具系统消除了在平衡系数测量过程中捕捉电流值的人为因素影响,并解决了无机房不能准确判断平衡点问题,有效的提高了检验工作的准确性和效率。     

兴隆庄煤矿生态系统服务价值评估

以兖州矿区兴隆庄煤矿为例,基于1990-2018年间的遥感影像数据,从供给、调节、支持和文化4个方面对兴隆庄生态系统服务价值进行测算评估,并分析其动态变化度及敏感性。评估结果表明,总生态服务价值表现为先增加后减少,1990-2010年矿区生态系统服务总价值从18841.5万元增加至29034.2万元,主要原因是采煤塌陷导致耕地向塌陷水体转变以及林地面积的增加;2010-2018年生态总价值减少了2484.8万元,主要在于耕地大规模地转变为建设用地以及区域地下水位下降造成的水域面积减小。敏感性分析显示,耕地和水体是平原矿区生态系统服务价值最敏感的因素,耕地的敏感性指数由1990年的0.79降为2018年的0.28,说明其在生态服务价值中的影响逐年降低。     

会计信息质量的非线性模型对公司价值的影响

从时代性、行业性及人力资源价值等方面分析了非线性因素对会计信息质量的影响,认为高质量的会计信息应该反映公司价值,并尝试建立了一个非线性模型,据此大体测算公司价值。     

Attitude-behaviour dissonance regarding the importance of food preservation for customers

The aim of the study was to identify the importance of individual food product attributes (the use of preservatives, processing method, shelf-life period and nutritional value) as well as their relation to the purchase behaviour. To achieve this, consumer preferences were decomposed in conditions of full access to information, and data was compared with actual consumer behaviour related to making purchasing decisions in front of the store shelf. Based on data from 338 respondents, conjoint analysis and repeated ANOVA measurements were carried out, allowing to eliminate individual behavioural patterns. The results showed a dissonance between the consumers attitudes towards the attributes and their shopping behaviour. The processing method was the most important declared attribute for consumers, meanwhile this information was the least searched for during purchase. At the same time, shelf-life period marked as the least important was the main information searched for by consumers when shopping. The results also show a clear dislike towards the use of microwaves as a preservation method, while traditional thermal preservation was marked as the most positive for consumers. In addition, consumers were classified into 3 heterogeneous groups, identifying differences in the preferences of food attributes. The obtained results have practical value relating not only to the preferences of individual attributes, but also to their various variants. The results can be a guide for companies to properly label food products. The indicated dissonance illustrates the educational gap and related insufficient motivation to get to know the product before buying it. This is extremely important in connection with technological development and new food processing methods.     

Benchmark value determination of energy efficiency indexes for coal-fired power units based on data mining methods

The operational optimisation of coal-fired power units is important for saving energy and reducing losses in the electric power industry. One of the key issues is how to determine the benchmark values of the energy efficiency indexes of the units. Therefore, a new framework for determining these benchmark values is proposed, based on data mining methods. First, the energy efficiency key performance indicators (KPIs) associated with the net coal consumption rate (NCCR) were selected based on the domain knowledge. Second, the decision-making samples with minimal NCCR were acquired with the fuzzy C-means (FCM) clustering algorithm, and the corresponding clustering centres were employed as the benchmark values. Finally, based on the support vector regression (SVR) algorithm, the target values of the NCCR were obtained with the KPIs as input, and the energy saving potential was evaluated by comparing the target values with the historical values of the NCCR. An actual on-duty 1000 MW unit was taken as study unit, and the results show that the energy saving potential is remarkable when the operators adjust the KPIs based on the calculated benchmark values.     

汽车悬架球头拉杆冷成形技术

为提高生产效率、改变原来通过车削加工汽车悬架球头拉杆的方式,提出了一种球头拉杆的多工位冷镦成形工艺。基于DEFORM-3D软件建立了有限元模型,对球头拉杆的塑性成形过程进行了仿真,研究了预成形凸模入模角α、预成形凹模圆角R1、终成形凹模圆角R2以及终成形凹模入模角β等工艺参数对球头拉杆成形的影响,并进行了正交试验,以模具在球头拉杆成形过程中所受载荷及工件损伤值为优化目标,获得了合理的工艺参数组合。结果表明:在保证工件成形质量及模具寿命的前提下,当预成形凸模入模角α为30°、预成形凹模圆角R1为12 mm、终成形凹模圆角R2为3 mm、终成形凹模入模角β为60°时,模具载荷及工件损伤有显著的降低。采用优化后的参数进行试模生产,工件成形质量较好,验证了模拟结果的可信性,能够有效地指导工艺设计人员的设计工作。