基于改进INFO-Bi-LSTM模型的SO_(2)排放质量浓度预测

针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进INFO-Bi-LSTM模型)。采用Circle混沌映射和反向学习产生高质量初始化种群,引入自适应t分布提升INFO算法跳出局部最优解和全局搜索的能力。选取改进INFO-Bi-LSTM模型和多种预测模型对炉内外联合脱硫过程中4种典型工况下的SO_(2)排放质量浓度进行预测,将预测结果进行验证对比。结果表明:改进INFO算法的寻优能力得到提升,并且改进INFO-Bi-LSTM模型精度更高,更加适用于SO_(2)排放质量浓度的预测,可为变工况下的脱硫控制提供控制理论支撑。

改进的T^2-BIC说话人二级分割算法

针对传统T2-BIC算法累积误差较大、召回率不高的问题,提出一种改进的T2-BIC说话人二级分割算法。第1级采用改进的滑动窗口检测搜索窗中的T2统计量峰值,利用贝叶斯信息准则(BIC)对峰值进行确认,第2级利用分步解决的思想处理由于BIC可信度过低而漏选的分割点。实验结果表明,与同类算法相比,该算法分割效果较好,准确率、召回率和综合性能都有所提高。

An Integrated Use of Advanced T2 Statistics and Neural Network and Genetic Algorithm in Monitoring Process Disturbance

Integrated use of statistical process control (SPC) and engineering process control (EPC) has better performance than that by solely using SPC or EPC. But integrated scheme has resulted in the problem of “Window of Opportunity” and autocorrelation. In this paper, advanced T2 statistics model and neural networks scheme are combined to solve the above problems: use T2 statistics technique to solve the problem of autocorrelation;adopt neural networks technique to solve the problem of “Window of Opportunity” and identification of disturbance causes. At the same time, regarding the shortcoming of neural network technique that its algorithm has a low speed of convergence and it is usually plunged into local optimum easily. Genetic algorithm was proposed to train samples in this paper. Results of the simulation ex-periments show that this method can detect the process disturbance quickly and accurately as well as identify the dis-turbance type.

Simple Insulin Dose Adjustment Using 3-3-1 Algorithm in Japanese Patients with Type 2 Diabetes: Start Kanazawa Study (Self-Titration Aggressive Algorithm with Glargine Trial)

We implemented a 3-3-1 algorithm in order to provide safe and simple self-titration in patients who newly initiated BOT as well as who were already on BOT and evaluated its utility in clinical setting. A total of 46 patients, 21 patients in the newly-initiated group and 25 patients in the existing BOT group performed dose adjustment using 3-3-1 algorithm. HbA1c was significantly improved 4 weeks after the initiation from 8.5% ± 1.2% at baseline to 7.3% ± 0.7% at the final evaluation (p 0.01, vs. Baseline). The average daily insulin units increased throughout the study period from 10.1 ± 6.7 at baseline to 14.6 ± 8.9 units at the final evaluation. Weight didn’t significantly change throughout the study (p = 0.12). The incidents of hypoglycemia were 0.8/month during the insulin dose self-adjustment period and 0.4/month during the follow-up period. The 3-3-1 algorithm using insulin glargine provided a safe and simple dose adjustment and demonstrated its utility in patients who were newly introduced to insulin treatment as well as who were already on BOT.

Design of Sharp 2D Multiplier-Less Circularly Symmetric FIR Filter Using Harmony Search Algorithm and Frequency Transformation

In this paper, we present a novel and efficient method for the design of a sharp, two dimensional (2D) wideband, circularly symmetric, FIR filter. First of all, a sharp one dimensional (1D) infinite precision FIR filter is designed using the Frequency Response Masking (FRM) technique. This filter is converted into a multiplier-less filter by representing it in the Canonic Signed Digit (CSD) space. The design of the FRM filter in the CSD space calls for the use of a discrete optimization technique. To this end, a new optimization approach is proposed using a modified Harmony Search Algorithm (HSA). HSA is modified in such a way that, in every exploitation and exploration phase, the candidate solutions turns out to be integers. The 1D FRM multiplier-less filter, is in turn transformed to the 2D equivalent using the recently proposed multiplier-less transformations namely, T1 and T2. These transformations are successful in generating circular contours even for wideband filters. Since multipliers are the most power consuming elements in a 2D filter, the multiplier-less realization calls for reduced power consumption as well as computation time. Significant reduction in the computational complexity and computation time are the highlights of our proposed design technique. Besides, the proposed discrete optimization using modified HSA can be used to solve optimization problems in other engineering disciplines, where the search space consists of integers.

An algorithm for multi-exponential inversion of T_2 spectrum in nuclear magnetic resonance

NMR logging can provide the permeability parameter and abundant stratigraphical information such as total porosity,oil,gas and water saturation,oil viscosity,etc. And these physical parameters can be obtained by T2 spectrum inversion. NMR inversion is an important part in logging interpretation. The authors describe a multi-exponential inversion algorithm,solid iteration redress technique( SIRT),and apply the algorithm in real data and compare the results with those based on singular value decomposition( SVD). It shows that SIRT algorithm is easier to be understood and implemented,and the time spent in SIRT is much shorter than that of SVD algorithm. And the non-negative property of T2 spectrum is much easier to be implemented. It can match the results based on SVD very well. SIRT algorithm can be used in T2 spectrum inversion for NMR analysis.

Monitoring Freeway Incident Detection Using a Hotelling T2 Control Chart

In real-life freeway transportation system, a few number of incident observation （very rare event） is available while there are large numbers of normal condition dataset. Most of researches on freeway incident detection have considered the incident detection problem as classification one. However, because of insufficiency of incident events, most of previous researches have utilized simulated incident events to develop freeway incident detection models. In order to overcome this drawback, this paper proposes a wavelet-based Hotelling 7a control chart for freeway incident detection, which integrates a wavelet transform into an abnormal detection method. Firstly, wavelet transform extracts useful features from noisy original traffic observations, leading to reduce the dimensionality of input vectors. Then, a Hotelling T2 control chart describes a decision boundary with only normal traffic observations with the selected features in the wavelet domain. Unlike the existing incident detection algorithms, which require lots of incident observations to construct incident detection models, the proposed approach can decide a decision boundary given only normal training observations. The proposed method is evaluated in comparison with California algorithm, Minnesota algorithm and conventional neural networks. The experimental results present that the proposed algorithm in this paper is a promising alternative for freeway automatic incident detections.

基于改进麻雀算法的最大2维熵分割方法

为了提高最大2维熵分割的性能,提出了基于改进麻雀算法的最大2维熵分割方法,可减小运算量并且缩短计算时间。首先,融合反向学习策略和自适应t分布变异,引入精英粒子,以扩大算法搜索范围,增加算法后期局部搜索能力;其次,使用萤火虫机制,对最优解进行扰动变异,进一步增加种群多样性;最后,采用提出的改进麻雀算法寻找图像最大2维熵,得到最优阈值分割图像。结果表明,4幅图像的平均运行时间为0.3695s,远低于基础2维熵算法的1.7547s和基础2维Otsu算法的5.7936s。所提出的改进麻雀算法的全局搜索和局部寻优能力相比原麻雀算法有较大改善,缩短了传统最大2维熵图像分割方法的运行时间,在峰值信噪比和结构相似度指标上均得到提升,具有一定的应用价值。

RSA加密方式中Montgomery算法的研究与改进

运算安全和运算效率问题是目前RSA加密体制的关键问题。实际应用中RSA密码算法加密、解密运算均为模幂运算,即Memod N。将模幂运算转换为一系列模乘运算便于硬件实现,并且可以进行并行运行,提高运算效率。本文主要通过对Montgomery算法进行研究,然后提出改进的高基Montgomery算法来提高RSA密码算法的运算速度和执行效率。

An unsupervised clustering method for nuclear magnetic resonance transverse relaxation spectrums based on the Gaussian mixture model and its application

To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed to obtain the quantitative pore structure information from the NMR T;spectrums based on the Gaussian mixture model(GMM). Firstly, We conducted the principal component analysis on T;spectrums in order to reduce the dimension data and the dependence of the original variables. Secondly, the dimension-reduced data was fitted using the GMM probability density function, and the model parameters and optimal clustering numbers were obtained according to the expectation-maximization algorithm and the change of the Akaike information criterion. Finally, the T;spectrum features and pore structure types of different clustering groups were analyzed and compared with T;geometric mean and T;arithmetic mean. The effectiveness of the algorithm has been verified by numerical simulation and field NMR logging data. The research shows that the clustering results based on GMM method have good correlations with the shape and distribution of the T;spectrum, pore structure, and petroleum productivity, providing a new means for quantitative identification of pore structure, reservoir grading, and oil and gas productivity evaluation.

基于GF(2^8)域上的机密文件分解分存与恢复

在(t,n)门限方案的基础上提出一种新的基于有限域GF(28)的方案:将机密文件中连续的t个字节分为一组,分组构造GF(28)域上的(t-1)次多项式,每组多项式生成n个不同的点分别存入n个文件中;当需要再现机密文件时,从n个文件任选至少t个文件并抽取同序号的数据利用拉格朗日插值重构(t-1)次多项式,继而获得机密文件的t个数据,实现机密文件的恢复.计算实例以及编程实验分析表明:这一方案是合理与可行的,与传统基于插值多项式的秘密分享方法相比,所提方法在运行效率上有所提升了,更适合大文件数据.

中国区域大气加权平均温度垂直递减率格网模型

大气加权平均温度(T m)是全球导航卫星系统(GNSS)反演大气水汽(PWV)的关键参数。然而,已有经验T m模型难以捕获T m的日周期变化,限制了其在高时间分辨率GNSS-PWV监测中的应用。利用大气再分析资料可获取高时间分辨率的T m信息,但需使用高精度的T m垂直递减率模型对其进行高程改正。针对已有T m垂直递减率模型建模仅使用单一格网点数据等不足,本文引入滑动窗口算法,利用2012—2016年的MERRA-2再分析资料建立了顾及时变垂直递减率的中国区域水平分辨率分别为1°×1.25°、2°×2.5°和4°×5°的T m垂直递减率格网模型(简称“CTm-H1、CTm-H2和CTm-H3模型”)。联合2017年的MERRA-2、GGOS大气格网数据和探空站资料,对CTm-H模型进行精度检验,并与中国区域统一的T m垂直递减率模型(简称“统一模型”)进行比较分析。结果表明:①以MERRA-2格网数据为参考值,通过CTm-H模型将MERRA-2地表格网数据改正到分层格网数据各层高度处检验,CTm-H 3个模型性能相当,在两种T m数据高程差异较大时,CTm-H模型表现出显著的优势,相比于统一模型,精度(RMS值)整体提高了30%。②以探空站资料为参考值,通过CTm-H模型将MERRA-2地表格网数据和GGOS大气格网产品分别改正到探空站高度处检验,与统一模型相比,CTm-H 3个模型的精度整体分别提高了3%和5%,且CTm-H和统一模型的精度相比于未顾及垂直改正提升较大,尤其在中国西部地区表现出显著的优势。总体而言,CTm-H 3个模型在中国区域均具有较高的精度,不需要实测气象参数即可提供中国区域近地空间范围内(本文指0~10 km的高程范围)任意位置实时高精度的T m高程改正值,因此,它在中国区域的实时高精度GNSS水汽探测中具有重要的应用。

基于卡拉汉数值仿真的限流熔断器暂态计算

高压限流熔断器因其限制短路电流能力强、保护性能好而在电力系统中正得到广泛应用,但是熔断器保护动作引起的过电压往往容易对系统设备造成不利影响。为此,基于卡拉汉数值算法着重研究限流熔断器动作过程中的过电压及电流暂态。首先建立了高断力限流熔断器保护动作过程的非线性电阻模型;接着运用半隐格式的卡拉汉数值算法代替EMTP/ATP软件,计算得到了限流熔断器试验回路的熔断器过电压和开断电流波形,数值建模和仿真计算中还综合考虑了其过电压保护MOA避雷器的影响;最后得到了与热效应相关的熔化I2t和合闸相角关系曲线,这对于试验考核熔断器的性能具有指导意义。数值计算与现场实测的比较结果证明,卡拉汉数值算法具有较高的精确性和可靠性,编程实现简便,程序灵活适用,模拟结果准确,可以避免大量现场重复的试验工作,该研究结果对限流熔断器试验可提供实际的参考依据。

基于区间2型T-S模糊系统的自适应逆控制

复杂非线性系统存在强非线性和不确定性等问题,其建模与控制一直是个极具挑战的工作。自适应逆控制是一种有效的非线性系统控制方法,已经得到广泛的研究;2型模糊系统采用2型模糊集,相比于1型模糊系统,其能够提供更大的自由度,不确定性及非线性处理能力更强,能够采用较少的规则数取得较高的建模与控制精度。因此,本文将2型模糊系统理论与自适应逆控制相结合,提出了一种基于区间2型T-S模糊系统的自适应逆控制方法,实现对复杂非线性系统的有效建模与控制。首先通过离线输出输入数据映射得到非线性系统的离线2型模糊逆模型,然后将该离线区间2型模糊逆模型作为初始控制器,与被控对象串联,进行在线控制,并采用最小均方差(Least Mean Square,LMS)滤波算法在线修正2型模糊逆模型的结论参数,通过数字复制,更新逆模型控制器的参数。最后将该方法应用于两个仿真实例,结果表明本文方法控制精度高,不确定性处理能力强。

采用超临界二氧化碳动力循环回收燃气轮机排气余热的系统优化研究

采用超临界二氧化碳(S-CO_(2))动力循环回收燃气轮机排气余热可以提高系统性能,增加系统灵活性,减小系统体积。为此,本文采用遗传算法,以Taurus 60燃气轮机排气为热源对4种S-CO_(2)动力循环构型进行优化。结果表明,采用高、低温2级加热器布置的循环构型4输出净功最高,为3.20 MW,和单独的燃气轮机相比,可使系统热效率提高17.78百分点,是回收燃气轮机排气余热发电的优选构型。针对S-CO_(2)动力循环冷源损失较大的问题,进一步集成以液化天然气(LNG)为冷源的跨临界二氧化碳(T-CO_(2))动力循环回收S-CO_(2)动力循环冷源余热,可以进一步增加输出净功1.23 MW,使系统热效率进一步提高6.86百分点。对预冷器进行夹点分析可知,最小换热温差出现在预冷器热端,未出现夹点效应,满足设计要求。

节能算法在ZRP协议中的应用

引用基于判断因子的节能算法从能量角度上对ZRP协议加以改进,得到了一种新的路由协议T-ZRP。仿真结果表明,T-ZRP与传统的ZRP相比,减小了能量消耗,从而减少了失效节点。

投影算子的Faddeev型算法的改进

给出了投影算子PAT ,S与PT ,(A S⊥) ⊥ 的改进算法 .