Generalizations of mixed weighted power mean inequality

Tarnavas established mixed weighted power mean inequality in 1999. A separation of weighted power mean inequslity was derived in this paper. As its applications, some separations of other inequalities were given.

Sharp power mean bounds for Seiffert mean

In this paper, we find the greatest value p = log 2/（log Tr - log 2） = 1.53.- and the least value q -- 5/3 - 1.66.. such that the double inequality Mp（a,b） 〈 T（a,b） 〈 Mq（a,b） holds for all a, b 〉 0 with a # b. Here, Mp（a, b） and T（a, b） are the p-th power and Seiffertmeans of two positive numbers a and b, respectively.

Sharps Bounds for Power Mean in Terms of Contraharmonic Mean

In this research work, we consider the below inequalities: (1.1). The researchers attempt to find an answer as to what are the best possible parameters α, β that (1.1) can be held? The main tool is the optimization of some suitable functions that we seek to find out. Without loss of generality, we have assumed that a > b and let for 1) and a < b, (t small) for 2) to determine the condition for α and β to become f(t) ≤ 0 and g(t) ≥ 0.

光伏波动平抑下改进K-means的电池储能动态分组控制策略

针对电池储能系统(battery energy storage system,BESS)进行光伏波动平抑时寿命损耗高及荷电状态(state of charge,SOC)一致性差的问题,提出了光伏波动平抑下改进K-means的BESS动态分组控制策略。首先,采用最小最大调度方法获取光伏并网指令。其次,设计了改进侏儒猫鼬优化算法(improved dwarf mongoose optimizer,IDMO),并利用它对传统K-means聚类算法进行改进,加快了聚类速度。接着,制定了电池单元动态分组原则,并根据电池单元SOC利用改进K-means将其分为3个电池组。然后,设计了基于充放电函数的电池单元SOC一致性功率分配方法,并据此提出BESS双层功率分配策略,上层确定电池组充放电顺序及指令,下层计算电池单元充放电指令。对所提策略进行仿真验证,结果表明,所设计的IDMO具有更高的寻优精度及更快的寻优速度。所提BESS平抑光伏波动策略在有效平抑波动的同时,降低了BESS运行寿命损耗并提高了电池单元SOC的均衡性。

基于K-means++与ELM的短期风电功率预测模型研究

风能的波动性对风电产业的迅速发展带来了巨大挑战,准确可靠的短期风电功率预测对满足电网调度以及降低度电成本具有重要意义。文中提出了一种基于K-means++聚类分析和极限学习机ELM的短期风电功率预测方法,同时使用数值天气预报(NWP)数据与SCADA系统的历史监测数据,实现了对未来72 h的短期风电功率预测。文中通过K-means++聚类算法将NWP数据划分为数量不等的簇,使用ELM对每个簇的数据分别建立NWP数据与SCADA功率数据间的映射模型。完成模型训练后,根据数据与各聚类中心点之间的距离选择最佳预测模型。实验结果表明,与常用的经典模型相比,其预测结果精度更高,具有更高的预测性能。

基于K-means聚类和极限学习机组合算法的短期光伏功率预测

考虑光伏功率的预测精度强依赖于天气模态和气候条件等因素影响,提出了基于极限学习机组合算法的短期光伏功率预测方法。首先,基于K-means聚类算法进行天气分型,分为4个季节下晴天、多云天气、阴雨天气共12组不同天气类别。其次,针对天气分型结果,基于极限学习机ELM、遗传算法改进的极限学习机GA-ELM、鸟群算法改进的极限学习机BSA-ELM3种算法构建光伏功率预测模型。最后,以某光伏电站数据进行所提模型验证。预测结果表明,BSA-ELM预测精度最高,12种天气预测精度达到90%左右,各季节中预测精度最高的天气类型均为晴天,多云天气精度高于阴雨天气精度,可为含高比例光伏并网的新型电力系统安全稳定运行提供有效数据支撑。

基于KLPP-K-means-BiLSTM的台区短期电力负荷预测

随着智能电网的发展,各场景的用电更加多元化,而准确的台区负荷预测是确保相关电力部门制定合适检修任务的关键,同时为有序用电、电网经济运行提供重要参考。为了挖掘台区负荷的特征以提高台区负荷预测的精度,提出了一种基于核主元分析与局部保持投影降维、K均值聚类算法(K-means)以及双向长短时记忆网络(BiLSTM)的台区电力负荷预测方法。首先利用核局部保持投影(KLPP)对台区多特征负荷数据进行降维以提取主要特征信息;然后采取K-means聚类算法将相似特征的数据归类成各自的簇集;最后针对聚类后的各典型类型,有针对性地训练BiLSTM,并选取中国某高校低压台区负荷作为算例与其他经典预测方法进行对比分析,结果表明所提方法更拟合实际负荷走向,有效提升了预测效果。

基于改进K-means算法的电力营销档案信息管理系统

为满足档案管理用户需求,实现不同营销档案管理信息分类,提出改进K-means算法的电力营销档案信息管理系统。设计电能信息收编、客户缴费管理、营销报表管理及系统开发等子系统功能;利用改进的K-means方法定义系统算法,引入权重概念,将元素分配到和中心点距离最近的簇中,实现档案分类统计。仿真实验证明,该系统可实现不同营销档案的准确分类,减少响应延时,提高系统吞吐量,满足电力营销档案管理用户需求。

融合充放电曲线特征与改进K-means聚类的退役锂电池分选方法

为提高退役锂电池分选重组的一致性,提出一种融合电压曲线与能量曲线的数值特征与形态特征,并运用欧氏距离和形态距离进行K-means聚类的分选方法。通过试验获取退役锂电池充放电曲线,融合电压曲线和能量曲线作为分选依据;采用欧式距离度量融合曲线的数值差异;利用分位数方法将融合曲线转化为描述曲线形态变化的特征序列,运用最长公共子序列算法提取特征序列的形态距离用来度量融合曲线的形态差异;以融合曲线的欧式距离和特征序列的形态距离为度量判据,采用改进K-means聚类算法对退役锂电池进行聚类。结果表明:相较于电压曲线或容量曲线分选,采用融合曲线分选,容量、充电电压、放电电压一致性最大提高约23%、93%、16%。相较于欧式距离方法,采用改进K-means算法,容量、充电电压、放电电压一致性最大分别提高了约67%、40%、51%。

基于改进K-means算法的分布式小水利发电集群划分方法

随着大规模分布式电源的接入,将复杂的分布式发电集群划分为通信维度较低、控制方式较简单的区域,是实现分布式发电集群灵活并网和优化调度的重要方式。文章提出一种基于改进K-means算法的分布式小水利发电集群划分方法,旨在利用改进K-means算法更有效地处理大规模数据集,自动识别最佳的集群划分,从而减少主观干预,通过更精确的划分,可以最大限度地提高小水利发电利用效率。

On the Fourth Power Mean of the Character Sums Over Short Intervals

The main purpose of this paper is to study the mean value properties of the character sums over the interval [1,p/8） by using the mean value theorems of the Dirichlet L-functions, and give an interesting mean value formula for this study.

On the Sixth Power Mean of the Two-term Exponential Sums

The main purpose of this article is to study the calculating problem of the sixth power mean of the two-term exponential sums,and give an interesting calculating formula for it.At the same time,the paper also provides a new and effective method for the study of the high order power mean of the exponential sums.

电网需求侧资源动态分布式k-means聚类算法

为有效聚合电网需求侧资源,合理、高效利用电网资源,提出基于分布式k-means的电网需求侧资源动态聚类算法。通过基于置信半径的分布式k-means算法聚类采集到的电网需求侧资源数据,在模糊C均值进化神经网络中,以聚类得到的电网需求侧资源数据为输入向量,输出电网需求侧资源场景,依据场景存在概率,以电网侧资源日均峰谷差最小、DG消纳程度最高与日均负荷波动率最小为目标函数,以电网需求侧资源曲线波动率与负荷互补为约束条件,构建电网需求侧资源多场景聚类模型,经动态改变惯性因子(DCW)粒子群算法求解模型后,实现电网需求侧资源多场景聚类。试验结果表明:该方法可实现电网需求侧资源动态聚类,应用该方法聚类不同场景电网需求侧资源时的日负荷率较低,聚类效果较好,可满足实际电力需求侧资源动态聚类工作的需要。

基于K-means算法和积灰损耗系数的西北地区光伏电站清洗策略建模分析

针对当前西北地区光伏场站缺乏科学合理的清洗策略来清除组件表面积灰的问题,提出基于K-means算法和积灰损耗系数的光伏电站清洗策略模型。利用K-means算法对场站提供的日志发电数据进行聚类得到晴天数据样本,利用该样本数据拟合发电能力损耗曲线求解积灰损耗系数,联立清洗成本建立清洗策略模型。文章利用西北地区某光伏场站的发电数据对模型进行了验证,分析结果表明模型准确性较高,也为西北地区光伏电站清洗策略的研究提供了新思路。

On the Fourth Power Mean of the Generalized Quadratic Gauss Sums

The main purpose of this paper is to use elementary methods and properties of the classical Gauss sums to study the computational problem of one kind of fourth power mean of the generalized quadratic Gauss sums mod q （a positive odd number）, and give an exact computational formula for it.

On the Hybrid Power Mean Involving the Two-Term Exponential Sums and Polynomial Character Sums

The main purpose of this paper is using the analytic method and the properties of trigonometric sums and character sums to study the computational problem of one kind hybrid power mean involving two-term exponential sums and polynomial character sums.Then the authors give some interesting calculating formulae for them.

Does Being a Big Power Mean Paying a Big Bill? Japan's UN funding proposal appears to disguise political motives

Japan, which is increasingly frustrated that it has not been granted a permanent seat on the UN Security Council, has found a new outlet of displeasure against the world body. On March 10, Japan proposed to the UN General Assembly budget committee,

RIGHT MEAN FOR THEα-z BURES-WASSERSTEIN QUANTUM DIVERGENCE

The optimization problem to minimize the weighted sum ofα-z Bures-Wasserstein quantum divergences to given positive definite Hermitian matrices has been solved.We call the unique minimizer theα-z weighted right mean,which provides a new non-commutative version of generalized mean(H?lder mean).We investigate its fundamental properties,and give many interesting operator inequalities with the matrix power mean including the Cartan mean.Moreover,we verify the trace inequality with the Wasserstein mean and provide bounds for the Hadamard product of two right means.

The Fourth Power Mean of the General 3-dimensional Kloostermann Sums mod p

The main purpose of this paper is using the analytic methods, the solutions of the congruence equation mod p and the properties of Gauss sums to study the computational problem of one kind fourth power mean of the general 3-dimensional Kloostermann sums mod p, and give a sharp asymptotic formula for it.

ON THE GENERAL k-TH KLOOSTERMAN SUMS AND ITS FOURTH POWER MEAN

The main purpose of this paper is to study the asymptotic property of the fourth power mean of the general k-th Kloosterman sums, and give an interesting asymptotic formula.