PSO-ELM在低压系统短路电流峰值预测中的应用

在短路电流早期检测的基础上,提出一种基于粒子群优化极端学习机(PSO-ELM)的短路电流峰值预测方法.利用短路电流暂态特性分析确定预测模型的输入特征量,采用粒子群算法对极端学习机的输入权值和隐层偏置进行优化,最后,将提出的预测算法应用于低压多层级实验平台,并且与传统BP、 ELM算法进行比较.实验结果表明,基于PSO-ELM模型的短路电流峰值预测方法能够在全相角范围内准确地预测短路电流峰值,可作为低压多层级系统全选择性保护的短路故障预测算法.     

基于粒子群优化算法的最优极限学习机

针对极限学习机隐含层神经元个数选取的问题,提出以粒子群优化算法搜索最佳隐含层神经元个数,用极限学习机模型的测试准确率作为粒子群优化算法适应值的方法(PSO-ELM)。基于手写数字数据集digits分别对比了随机设置隐含层神经元个数的极限学习机、用粒子群算法优化的极限学习机输入权重和隐层偏置的极限学习机(PSO-ELM)、传统的BP算法以及SVM算法对手写数字的识别率,对比结果表明,粒子群优化算法得到的隐含层神经元个数在极限学习机中拥有较高的准确率。     

基于黑洞粒子群和多层级SVM的低压交流系统短路故障类型辨识

针对低压交流系统的短路故障诊断问题,提出一种基于黑洞粒子群(BHPSO)和多层级SVM的低压交流系统短路故障类型辨识方法。首先,基于故障前后0.5ms电流信号小波变换分解,采用小波细节分量标准差构建故障特征向量。其次,采用黑洞粒子群算法对SVM的核参数和惩罚因子进行参数优化以构建多层级SVM分类器实现低压交流系统短路故障类型辨识。最后,基于TMS320F28335 DSP将故障类型辨识决策模型加以硬件化技术实现。通过低压交流系统短路实验证实本方法准确率高,且在噪声干扰、负荷电流变化等工况下均有较好的鲁棒性。     

基于PSO-ELM模型的短期电力系统负荷预测

为了提高电力负荷预测的精确度、降低预测误差,提出了一种基于粒子群优化的极限学习机(PSO-ELM)模型。通过粒子群算法对极限学习机的参数进行寻优,最后通过PSO-ELM模型和传统ELM模型预测结果的相对误差比对,改进模型将相对误差降低在1%左右,提升了学习速率和预测精度,为电网运行和电力分配提供了决策保障。     

极限学习机在采空区自然发火预测中的应用

针对采空区煤炭自然发火的预测问题,从温度、标志气体浓度以及钻孔参数3个方面选取了8个相关因素,利用Logistic回归分析从中提取出5个相对重要的因素作为预测模型的输入,运用极限学习机算法进行预测,并采用粒子群算法对极限学习机的输入权值及隐含层阈值作优化选取,以提高其泛化能力及预测精度,以此建立了PSO-ELM自然发火预测模型.选用28组训练样本和12组检验样本进行模型的预测实验,结果表明,基于Logistic回归分析筛选指标后的PSO-ELM模型有较高的预测精度,是预测采空区自然发火的一个有效方法.     

基于PSO-ELM的中国石油股票价格预测建模

为了提高股票价格预测的精度,针对中国石油股票价格预测问题,提出了粒子群算法(Particle Swarm Optimization,PSO)优化极限学习机(Extreme Learning Machine,ELM)的股票价格预测模型。通过粒子群算法对极限学习机的权值以及阈值参数进行优化,构建PSO-ELM预测模型,并将其用于中国石油股票价格预测。仿真实验表明,与ELM、PSO-BP、DE-ELM相比,其预测均方误差分别下降了1.84%、1.07%、0.97%,拟合优度决定系数R2为0.974 3,即PSO-ELM有着较高的预测精度。为了给股票投资者更好的投资建议,对PSO-ELM模型分别进行股价短期、中期、长期的预测,结果表明PSO-ELM模型短期预测精度较高,随着时间的推移预测的精度有所下降。     

基于粒子群优化极限学习机数据预测模型研究

极限学习机(Extreme Learning Machine,ELM)是一种新型的前馈神经网络,该网络由广义逆直接求出输出层权重,使得其具有误差小、速度快的优点。但针对具体问题,ELM不能自动寻找到最佳的网络结构,从而造成该算法模型针对复杂、无规律性的数据精度及稳定性较差。为了提高极限学习机的泛化能力和预测精度,提出利用粒子群优化极限学习机算法对不同数据进行预测。使用粒子群算法(particle swarm optimization,PSO)选择最优的隐含层偏差和输入权值矩阵,计算出输出权值矩阵,从而提高ELM的精度及稳定性。并通过PSO-ELM和ELM分别对复杂程度不同的汽油辛烷值和交通流量数据进行算法预测比较发现,PSO-ELM优化算法对无规律性、复杂程度高的数据可以获得更高的精度,提高了数据预测的拟合能力。实验结果表明,PSO-ELM对于非线性、无规律性等复杂特性的数据预测具有一定的可行性和有效性。     

基于PSO-ELM的双目视觉摄像机标定

针对极限学习机( extreme learning machine,ELM)在隐层节点数较少时标定精度较低的问题,利用粒子群优化算法( particle swarm optimization,PSO)与极限学习机相结合的方法对双目视觉摄像机进行标定。在标定过程中,ELM直接描述图像信息与三维信息之间的非线性关系,然后利用PSO优化ELM的输入权值与隐层阈值。实验结果表明,与ELM相比较,基于粒子群极限学习机( PSO-ELM)的双目视觉摄像机标定方法能仅用较少隐层节点数获得较高精度。     

基于PSO-ELM的射频功率放大器行为建模

为了有效地解决原始极限学习机算法中由于网络输入参数选择的随机性而引起的在射频功放行为建模应用中的建模精度不理想以及不稳定的问题,粒子群优化的极限学习机算法首次被引入到射频功率放大器的行为建模当中.利用粒子群优化方法来选择原始极限学习机算法中单隐藏层前馈神经网络的输入参数(包括输入权重和偏置).对E类射频功放的行为建模实验结果表明,粒子群优化的极限学习机可以有效改进原始极限学习机对射频功率放大器的外部行为的建模和预测能力.     

基于POS-ELM的孤立性肺结节诊断方法研究

在肺结节诊断方法研究中,传统机器学习诊断方法存在诊断性能不稳定的问题。为了提高孤立性肺结节的识别准确率,提出基于粒子群优化(particle swarm optimization,PSO)参数的极限学习机(extreme learning machine,ELM)辅助诊断方法。首先采用PSO选取ELM最佳的初始权重ω和偏置b;然后利用最佳参数ω和b对ELM进行训练;再利用PSO-ELM对通过稀疏自编码得到的肺结节特征进行分类识别。实验中,将传统机器学习算法与本文方法进行对比,结果表明,利用粒子群优化算法进行优化的极限学习机在孤立性肺结节诊断方面具有较高识别准确率和稳定的分类性能,可以作为一种有效的肺结节诊断工具。     

Markedness and its Interpretation in Language Use

Language markedness is a common phenomenon in languages, and is reflected from hearing, vision and sense, i.e. the variation in the three aspects such as phonology, morphology and semantics. This paper focuses on the interpretation of markedness in language use following the three perspectives, i.e. pragmatic interpretation, psychological interpretation and cognitive interpretation, with an aim to define the function of markedness.     

Lower Paleozoic oil relationships within Williston Basin, Canada

The Williston Basin is a significant petroleum province, containing oil production zones that include the Middle Cambrian to Lower Ordovician, Upper Ordovician, Middle Devonian, Upper Devonian and Mississippian and within the Jurassic and Cretaceous. The oils of the Williston Basin exhibit a wide range of geochemical characteristics defined as "oil families", although the geochemical signature of the Cambrian Deadwood Formation and Lower Ordovician Winnipeg reservoired oils does not match any "oil family". Despite their close stratigraphic proximity, it is evident that the oils of the Lower Palaeozoic within the Williston Basin are distinct. This suggests the presence of a new "oil family" within the Williston Basin. Diagnostic geochemical signatures occur in the gasoline range chromatograms, within saturate fraction gas chromatograms and biomarker fingerprints. However, some of the established criteria and cross-plots that are currently used to segregate oils into distinct genetic families within the basin do not always meet with success, particularly when applied to the Lower Palaeozoic oils of the Deadwood and Winnipeg Formation.     

An Analysis of Catherine＇s Character——Wuthering Heights

Wuthering Heights, Emily Bronte＇s only novel, was published in December of 1847 under the pseudonym Ellis Bell. The book did not gain immediate success, but it is now thought one of the finest novels in the English language. Catherine is the key character of this masterpiece, because everybody and everything center on her though she had a short life. We can understand this masterpiece better if we know Catherine well.     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

Features of Women's language

Language is a means of verbal communication. People use language to communicate with each other. In the society, no two speakers are exactly alike in the way of speaking. Some differences are due to age, gender, statue and personality. Above all, gender is one of the obvious reasons. The writer of this paper tries to describe the features of women＇s language from these perspectives： pronunciation, intonation, diction, subjects, grammar and discourse. From the discussion of the features of women＇s language, more attention should be paid to language use in social context. What＇s more, the linguistic phenomena in a speaking community can be understood more thoroughly.     

Design and analysis of generic LBS application developing platform

Location based services is promising due to its novel working style and contents.A software platform is proposed to provide application programs of typical location based services and support new applications developing efficiently. The analysis shows that this scheme is easy implemented, low cost and adapt to all kinds of mobile nework system.     

橡胶颗粒沥青混合料低温抗裂性试验研究

以AC-13级配为基础,将橡胶颗粒代替部分集料掺入混合料中,以低温弯曲试验为评价方法对不同橡胶颗粒掺量下沥青混合料的低温抗裂性进行研究,并引入应变能密度值对混合料的低温抗裂性进行综合评价.试验结果表明:橡胶颗粒沥青混合料试件的破坏微应变均超过2 300,满足冬寒区的技术指标;无论是否掺加橡胶颗粒,随着温度的下降,沥青混合料破坏时的最大弯拉强度增大,弯拉应变降低,劲度模量增大;弯曲应变能密度在胶粒掺量为1%左右时具有较大的弯曲应变能密度值,此时橡胶颗粒沥青混合料具有较好的低温抗裂性.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

低渗透非均质砂岩油藏启动压力梯度研究

理论推导与室内实验相结合,建立了低渗透非均质砂岩油藏启动压力梯度确定方法。首先借助油藏流场与电场相似的原理,推导了非均质砂岩油藏启动压力梯度计算公式。其次基于稳定流实验方法,建立了非均质砂岩油藏启动压力梯度测试方法。结果表明:低渗透非均质砂岩油藏的启动压力梯度确定遵循两个等效原则。平面非均质油藏的启动压力梯度等于各级渗透率段的启动压力梯度关于长度的加权平均;纵向非均质油藏的启动压力梯度等于各渗透率层的启动压力梯度关于渗透率与渗流面积乘积的加权平均。研究成果可用于有效指导低渗透非均质砂岩油藏的合理井距确定,促进该类油藏的高效开发。     

On Tragic Consciousness In The Works By Ernest Hemingway

As an American modern novelist who were famous in the literary world, Hemingway was not a person who always followed the trend but a sharp observer. At the same time, he was a tragedy maestro, he paid great attention on existence, fate and end-result. The dramatis personae's tragedy of his works was an extreme limit by all means tragedy on the meaning of fearless challenge that failed. The beauty of tragedy was not produced on the destruction of life, but now this kind of value was in the impact activity. They performed for the reader about the tragedy on challenging for the limit and the death.