THE EXISTENCE AND LOCAL UNIQUENESS OF MULTI-PEAK SOLUTIONS TO A CLASS OF KIRCHHOFF TYPE EQUATIONS

In this paper,we study the existence and local uniqueness of multi-peak solutions to the Kirchhoff type equations-(ε^(2)a+εb∫_(R^(3))|■u|^(2))△u+V(x)u=u^(p),u>0 in R^(3),which concentrate at non-degenerate critical points of the potential function V(x),where a,b>0,1<p<5 are constants,andε>0 is a parameter.Applying the Lyapunov-Schmidt reduction method and a local Pohozaev type identity,we establish the existence and local uniqueness results of multi-peak solutions,which concentrate at{a_(i)}1≤i≤k,where{a_(i)}1≤i≤k are non-degenerate critical points of V(x)asε→0.

THE EXISTENCE AND LOCAL UNIQUENESS OF MULTI-PEAK POSITIVE SOLUTIONS TO A CLASS OF KIRCHHOFF EQUATION

In the present paper,we consider the nonlocal Kirchhoff problem-(ε^2a+εb∫|■u|^2)Δu+u=Q(x)u^p,u>0 in R^3,,where a,b>0,1<p<5 andε>0 is a parameter.Under some assumptions on Q(x),we show the existence and local uniqueness of positive multi-peak solutions by LyapunovSchmidt reduction method and the local Pohozaev identity method,respectly.

MULTI-PEAK MATCH INTENSITY RATIO METHOD OF QUANTI-TATIVE X-RAY DIFFRACTION PHASE ANALYSIS

A new method for quantitative phase analysis is proposed by using X-ray diffraction multi-peak match intensity ratio. This method can obtain the multi-peak match intensity ratio among each phase in the mixture sample by using all diffraction peak data in the mixture sample X-ray diffraction spectrum and combining the relative intensity distribution data of each phase standard peak in JCPDS card to carry on the least square method regression analysis. It is benefit to improve the precision of quantitative phase analysis that the given single line ratio which is usually adopted is taken the place of the multi-peak match intensity ratio and is used in X-ray diffraction quantitative phase analysis of the mixture sample. By analyzing four-group mixture sample, adopting multi-peak match intensity ratio and X-ray diffraction quantitative phase analysis principle of combining the adiabatic and matrix flushing method, it is tested that the experimental results are identical with theory.

Stimulated emission and multi-peaked absorption in a four level N-type atom

Absorption and refraction of the inner transition F2 ←→F3 of the closed four level N-type atom have been investigated under a weak field. The outer transitions F1←→F3 and F2←→F4 are resonantly interacted with drive field with frequency ωc and Rabi frequency Ωc, and saturation field with ωs and Ωs, respectively. For the suitable Rabi frequencies Ωc and Ωs, we obtain the Mellow absorption spectrum of probe field. The reason is that the drive field excites the atom to the upper level F3 and simultaneously the saturation field takes the atom out of the lower level F2, leading to the stimulated emission. Meanwhile, due to the dynamic energy splitting induced by the drive and saturation fields, the two- and four-peaked absorption spectra are observed. At the zero off-resonance detuning of probe field, we also find the transfer of dispersion from negative to positive with an increment of Ωs. Finally, the refractive index enhancement is predicted for a wide spectral region.

Absolutely Direct Frequency Measurement of Two-Photon Transition Using Multi-Peak Fitting Approach

The optical frequency comb has been widely used in precision measurement. In this study, a multi-peak fitting approach is first proposed to fit the two-photon transition spectrum which overlaps with the neighboring transition in Rb-87. The multi-peak fitting approach is used to eliminate the frequency shift affected by the neighboring transition. With locking the carrier envelope offset frequency at 1/4 repetition frequency, the transition frequency is measured to be 770569132739.9 +/- 5.8 kHz, which agrees well with the previous result recommended by Comite International des Poids et Mesures.

Non-existence of Multi-peak Solutions to the Schrödinger-Newton System with L2-constraint

In this paper, we are concerned with the the Schrödinger-Newton system with L^(2)-constraint. Precisely, we prove that there cannot exist multi-peak normalized solutions concentrating at k different critical points of V(x) under certain assumptions on asymptotic behavior of V(x) and its first derivatives near these points. Especially, the critical points of V(x) in this paper must be degenerate.The main tools are a local Pohozaev type of identity and the blow-up analysis. Our results also show that the asymptotic behavior of concentrated points to Schrödinger-Newton problem is quite different from the classical Schrödinger equations, which is mainly caused by the nonlocal term.

基于多策略混合改进MVO算法的光伏多峰MPPT研究

光伏阵列的电功率输出在局部遮荫工况下具有多峰特性,且随外界环境的变化而变化.为实现高效电能输出,利用多元宇宙优化(MVO)算法在解决低维度、小规模优化问题中的突出优势进行最大功率点跟踪(MPPT),并融合多种策略对其存在的缺陷进行改进.采用拉丁超立方抽样策略初始化宇宙种群,并对按照轮盘赌策略随机交换的宇宙实施柯西变异,提高宇宙种群的多样性.同时引入莱维飞行式量子粒子群优化(QPSO)算法,且对虫洞存在概率及旅行距离率进行自适应调整,以增强算法的全局勘探及局部开发能力.Matlab仿真结果表明,相比其他算法,采用该算法的MPPT时间减少了45%以上,精度亦有所提高,从而具有更优的MPPT性能,可有效提高光伏发电效率.

双碳时代下多源生物质热化学转化资源化利用研究进展

生物质是唯一的可再生碳资源,具有来源广泛、储量丰富等显著优势,利用先进的生物质热化学转化技术,可获得多种高值燃料、化学品和碳基材料,进而实现对化石资源的部分替代,在新能源领域具有重要的战略地位和发展前景。尽管生物质能源化利用技术已取得长足发展,但伴随社会与科技飞速进步,生物质的范畴已不再局限于传统农林废弃物,而是涵盖了农林源、工业源和生活源等多种来源的有机废弃物。复杂组成结构和差异化热分解特性为生物质的高选择性和大规模转化带来严重阻碍,如何实现其高值资源化利用仍面临诸多挑战。论述了生物质热化学转化技术发展现状,从多源生物质组成与热分解特性出发,针对热转化产物品质低和选择性差等问题,对比分析了当前选择性热解制备高值产物、热解重整制氢、新型气化等多种前沿资源化利用技术的最新研究成果与发展趋势。然而,要推动双碳时代下多源生物质热化学转化技术的进一步发展,仍需重点关注以下方面。首先,规模化利用是未来发展的必然趋势,开发高效的催化工艺与反应装备至关重要。通过突破催化剂效率瓶颈与循环再生技术,降低催化运行成本,同时研发新型热转化反应设备,优化传热与抗结焦性能,实现目标产物的定向富集,配合高效的原料收储运策略,从全流程提升生物质热化学转化工业化生产经济性。其次,全组分转化是实现生物质高值利用的关键。通过深入研究生物质不同特征组分分解机理和协同转化机制,开发耦合多重预处理、定向热转化和精准分离冷凝等技术,将生物质原料转化为富含高值化学品的生物油、高品质可燃气和高性能炭材料,实现热解多联产综合利用,有效提高技术资源产出率。最后,多能互补也是未来重要发展方向。通过将生物质与其他清洁能源与电力进行有效整合,充分发挥生物质热分解产物的长周期化学储能特性,构建灵活的多能互补供应体系,实现新能源产业的多维发展与经济效益提升。

基于改进布谷鸟搜索算法的光伏最大功率点跟踪策略

实际工程中,光伏阵列在随机变化的环境中会出现局部遮光的情况,从而导致光伏阵列的功率-电压特性曲线会呈现多峰值状态,传统的最大功率点跟踪(maximum power point tracking, MPPT)算法易陷入局部最优解,追踪速度和精准度无法得到满足。针对这一问题,提出一种基于布谷鸟搜索算法(cuckoo search algorithm, CS)和电导增量法(conductivity increment method, CI)结合的光伏MPPT算法,在算法前期利用布谷鸟搜索算法将大步长和小步长交替使用使得全局搜索能力增强,找到全局最大功率点所处区域附近;在后期,采用步长小、控制精度高的CI进行局部寻优,快速准确地锁定到最大功率点。在MATLAB/Simulink中搭建仿真模型,并与原始布谷鸟搜索算法和粒子群优化(particle swam optimization, PSO)算法进行比较。仿真结果表明,将CS与CI结合的算法使得收敛速度更快,精度更高,稳定状态时功率曲线的波动更小。

多情景下中型航空公司碳排放预测研究

在国际国内减碳的大背景下,文章选择国内某中型航空公司作为研究对象,首先利用ICAO碳排放计算法,依据航班进程的两个阶段(LTO和CCD阶段),对2015—2019年的碳排放量状况进行计算分析,再通过设置不减碳情景、基础减碳情景、快速减碳情景和理想减碳情景4个民航发展情景,使用基于Python语言的蒙特卡洛模拟方法,以2021年为基准,对该航空公司2022—2035年内的碳排放进行仿真预测。结果表明:由于中型航空公司的发展需求,4种情况下都无法完成碳排放总量达峰,但其每万架次碳排放量明显降低,表明碳减排措施的有效性。最后从国内外理论研究和现实应用的角度出发,为中型航空公司提出了多条低碳发展建议,以助力我国民航业早日实现碳达峰、碳中和的重要目标。

机器学习驱动锅炉燃烧优化技术的现状与展望

伴随可再生能源发电装机容量快速增加,深度调峰过程中负荷多变、燃烧失稳等不稳定工况对火电机组的燃烧优化控制提出了更高要求,快速发展的人工智能技术与深度学习算法为锅炉参数预测建模及优化提供了重要手段。在机器学习算法方面,总结了特征筛选与建模算法的研究现状,提出了传统统计学方法与线性降维方法的科学解释性较差且不能很好地辨识高维数据,结合深度学习算法的特征筛选方法在处理复杂的火电机组数据时优势更明显;对比了多种神经网络在NO_(x)排放浓度建模中的优缺点,其中长短期记忆神经网络与卷积神经网络在处理时序数据时效果更好、集成模型通过组合不同学习器的优势可提高整个模型的泛化能力和鲁棒性。在预测模型的应用方面,通过对SCR脱硝系统建立预测模型可以方便运行人员模拟并修正可调参数,同时作为软测量手段监测燃烧系统运行状态;引入NO_(x)排放浓度预测模型的前馈控制和模型预测控制等先进控制手段可有效改善火电机组传统PID控制效果较差的问题;在多目标优化中NO_(x)脱除效率通常与锅炉效率或脱硝成本共同作为优化目标,以期实现经济效益与社会效益的和谐统一。

多种能源融合发展战略研究

我国能源强国和“双碳”战略目标的实现,需要加速构建现代能源体系,加快转变能源发展方式和提高能源生产保障能力;多种能源融合是解决各能源分系统割裂、调整优化能源格局、提高能源清洁利用效率的有效解决方案。本文在分析多种能源融合发展现有模式的基础上,总结了国外多种能源融合发展的趋势、我国多种能源融合的发展现状和瓶颈;对标能源强国建设的清洁、高效等特征,提出了集能源转换、互补、再利用以及零碳生产生活功能于一体的新型多能融合模式,进而提出了多种能源融合的基本发展路径。研究建议,立足资源禀赋、建立支撑多种能源融合发展的中长期规划,加快突破多种能源融合关键核心技术、提高装备可靠性,加强“多种能源融合”相关人才培养,优化多种能源融合产业链结构,以更好推进我国多种能源融合发展的规划、建设与实践。

基于混沌多目标粒子群算法的综合能源调度

目的针对当前综合能源系统中资源协同优化效率不足、微网运行经济性和环保性差的问题,提出了一种计及风电储能及不稳定因素的微网优化调度方法。方法该方法在微网负荷侧需求响应对新能源消纳影响的基础上,以消纳新能源和削峰填谷为目的,提出了优化负荷曲线的方案;然后,考虑微网调度侧风电出力的不稳定性以及微网内部设备的耦合,进行优化调度以降低微网运行成本、减少环境惩罚费用并提高风电消纳平稳性;最后,采用混沌多目标粒子群算法对优化问题进行求解,并在风电不稳定度占比0%、5%、10%和15%时进行了算例仿真分析。结果当风电不稳定度为10%和加入风电储能,系统运行成本和环境治理费用最少,比方案1和无风电储能少6919.4元,风电平稳量也提高38 kWh。在电热冷网中,负荷侧加入需求响应后,系统得到稳定运行和能源合理利用,可以很好地满足负荷侧用能需求。从算法对比中,混沌多目标粒子群算法加入自适应权重和变异率后,具有较强的全局搜索能力和更好的准确性。结论该方法通过合理设置风电不稳定度能够有效降低运行成本和环境惩罚费用,提高风电稳定性,其次,负荷侧的需求响应可以一定程度地削峰填谷和消纳新能源。

Hybrid algorithm combining genetic algorithm with back propagation neural network for extracting the characteristics of multi-peak Brillouin scattering spectrum

In this study, a hybrid algorithm combining genetic algorithm （GA） with back propagation （BP） neural network （GA-BP） was proposed for extracting the characteristics of multi-peak Brillouin scattering spectrum. Simulations and experimental results show that the GA-BP hybrid algorithm can accurately identify the position and amount of peaks in multi-peak Brillouin scattering spectrum. Moreover, the proposed algorithm obtains a fitting degree of 0.9923 and a mean square error of 0.0094. Therefore, the GA-BP hybrid algorithm possesses a good fitting precision and is suitable for extracting the characteristics of multi-peak Brillouin scattering spectrum.

计及深度调峰的风-光-水-火-抽蓄多能源联网系统优化调度研究

多种能源联网运行逐步成为未来电力系统发展的方向,多能源联网系统的优化调度是应对规模化新能源并网消纳的重要手段。文中建立了计及火电机组深度调峰成本的风-光-水-火-抽蓄联网系统成本模型和考虑调峰主动性的风-光-水-火-抽蓄联网系统日前优化调度模型。针对多能源耦合系统结构复杂的情况,提出了分层优化调度的模型求解策略。上层模型以净负荷波动最小为优化目标,得到等效负荷曲线;下层模型根据上层模型的调度结果,以调峰运行的经济性最优和新能源弃电率最低为目标函数,计及调峰主动性,求解考虑火电机组深度调峰煤耗特性的含新能源系统的经济调度问题。仿真算例表明所建模型实现了多能源联网系统的互补运行,提升了火电机组的深度调峰能力,降低新能源弃电率和系统运行成本。

基于自适应尺度变换与特征融合的目标跟踪

针对传统核相关滤波算法在目标被遮挡或发生运动模糊时跟踪效果不佳的情况,为了达到运动目标的实时稳定跟踪,提高跟踪系统的精度和成功率,提出一种基于核相关滤波的具有尺度自适应和特征融合的目标跟踪方法。首先在特征提取过程中,通过在原有的方向梯度直方图特征后添加颜色特征来提高目标特征的识别能力,即将HOG特征与CN特征相融合,然后构建尺度金字塔来进行尺度估计以达到目标的尺度自适应,最后通过多峰值检测机制实现模型的更新。通过在OTB2015数据集中进行测试,算法的精确率和成功率有了进一步提升,该算法能够准确地识别出目标,并对目标进行有效跟踪。

Demodulation of the multi-peak fiber Bragg grating sensor based on partial wavelength scan

Until now, a high-efficiency demodulation method for fiber Bragg grating(FBG) sensors has been a challenge.In this Letter, by employing multi-peak FBGs, an FBG sensor with a partial wavelength scan is proposed and initially demonstrated. By demodulating a near-symmetrical multi-peak FBG and an asymmetrical multi-peak FBG in the strain experiment, sensor sensitivities of 1.02 pm/με and 1.01 pm/με are measured for the interrogation system, respectively. The average demodulation deviations for the two sensors are 1.81% and 0.4%,respectively. The proposed method is expected to realize high-efficiency and low-cost FBG interrogators.

A stereo matching algorithm using multi-peak candidate matches and geometric constraints

Gray cross correlation matching technique is adopted to extract candidate matches with gray cross correlation coefficients less than some certain range of maximal correlation coefficient called multi-peak candidate matches. Multi-peak candidates are extracted corresponding to three closest feature points at first. The corresponding multi-peak candidate matches are used to construct the model polygon. Correspondence is determined based on the local geometric relations between the three feature points and the multi-peak candidates. The disparity test and the global consistency checkout are applied to eliminate the remaining ambiguous matches that are not removed by the local geometric relational test. Experimental results show that the proposed algorithm is feasible and accurate.

Multi-peak solitons in PT-symmetric Bessel optical lattices with defects

This paper presents a theoretical analysis of the existence and stability of multi-peak solitons in parity-time-symmetric Bessel optical lattices with defects in nonlinear media. The results demonstrate that there always exists a critical propagation constant μc for the existence of multi-peak solitons regardless of whether the nonlinearity is self-focusing or self-defocusing. In self-focusing media, multi-peak solitons exist when the propagation constant μ 〉 μc. In the self-defocusing case, solitons exist only when μ 〈 μc. Only low-power solitons can propagate stably when random noise perturbations are present. Positive defects help stabilize the propagation of multi-peak solitons when the nonlinearity is self-focusing. When the nonlinearity is self-defocusing, however, multi-peak solitons in negative defects have wider stable regions than those in positive defects.

改进密度峰值聚类的多源数据异常值检测算法

多源数据集中的数据类杂、数据量大,其中异常数据识别困难。针对多源数据异常值检测准确率低、稳定性差的问题,提出一种基于改进峰值密度聚类算法(NDPC算法)的多源数据处理方法,并在该算法的基础上构建出NDPC-SVM多源数据异常检测模型。模型首先使用数据预处理的方式对多源姿态图像数据进行数字化转换,以提高数据的可操作性;然后采用差分隐私保护算法对数据进行加密保护,并构建出隐私数据查询机制,提高数据的隐私性;接着利用NDPC算法对数据进行聚类处理,提高模型构建的鲁班性;最后利用交叉验证的方式优化构建出NDPC-SVM多源数据异常检测模型。消融仿真结果表明,四类优化算法的叠加显著的提高了异常数据检测的准确率与稳定性。对比仿真结果表明,与基线聚类算法模型相比,NDPC-SVM模型的准确率高达93.14%,召回率平均提升了2.48,综合性能上升了3.35%。因此,基于NDPC算法构建的NDPC-SVM多源数据异常检测模型在解决多源数据处理难度大的同时,提升了异常值检测的准确性与稳定性。