PRI modulation recognition and sequence search under small sample prerequisite

Pulse repetition interval(PRI)modulation recognition and pulse sequence search are significant for effective electronic support measures.In modern electromagnetic environments,different types of inter-pulse slide radars are highly confusing.There are few available training samples in practical situations,which leads to a low recognition accuracy and poor search effect of the pulse sequence.In this paper,an approach based on bi-directional long short-term memory(BiLSTM)networks and the temporal correlation algorithm for PRI modulation recognition and sequence search under the small sample prerequisite is proposed.The simulation results demonstrate that the proposed algorithm can recognize unilinear,bilinear,sawtooth,and sinusoidal PRI modulation types with 91.43% accuracy and complete the pulse sequence search with 30% missing pulses and 50% spurious pulses under the small sample prerequisite.

Partial transmitting sequence method based on trellis factor search

To obtain good trade-offs between complexity and performance onpeak-to-average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM)using partial transmitting sequence (PTS) schemes, a trellis structure based PTS factor searchmethod is proposed. The trellis search is with a variant constraint length L_C, 1 ≤ L_C ≤ V-1,where V is the number of PTS subblocks. The method is to decide a PTS factor by searching all thepossible paths obtained by varying L_C consecutive factors. The trellis search can be viewed as ageneral PTS factor search model. If L_C = V-1, it is a full search, and if L_C = 1, it is aniterative search. Using different constraint lengths, trellis factor search PTS exhibits differentPAPR reduction performances. A larger L_C results in a better performance and L_C = V-1 results inthe optimum. However, a larger L_C requires more computation. This helps to choose a good trade-offbetween complexity and performance.

Towards a Comprehensive Search of Putative Chitinases Sequences in Environmental Metagenomic Databases

Chitinases catalyze the hydrolysis of chitin, a linear homopolymer of β-(1,4)-linked N-acetylglucosamine. The broad range of applications of chitinolytic enzymes makes their identification and study very promising. Metagenomic approaches offer access to functional genes in uncultured representatives of the microbiota and hold great potential in the discovery of novel enzymes, but tools to extensively explore these data are still scarce. In this study, we develop a chitinase mining pipeline to facilitate the comprehensive search of these enzymes in environmental metagenomic databases and also to explore phylogenetic relationships among the retrieved sequences. In order to perform the analyses, UniprotKB fungal and bacterial chitinases sequences belonging to the glycoside hydrolases (GH) family-18, 19 and 20 were used to generate 15 reference datasets, which were then used to generate high quality seed alignments with the MAFFT program. Profile Hidden Markov Models (pHMMs) were built from each seed alignment using the hmmbuild program of HMMER v3.0 package. The best-hit sequences returned by hmmsearch against two environmental metagenomic databases (Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis—CAMERA and Integrated Microbial Genomes—IMG/M) were retrieved and further analyzed. The NJ trees generated for each chitinase dataset showed some variability in the catalytic domain region of the metagenomic sequences and revealed common sequence patterns among all the trees. The scanning of the retrieved metagenomic sequences for chitinase conserved domains/signatures using both the InterPro and the RPS-BLAST tools confirmed the efficacy and sensitivity of our pHMM-based approach in detecting putative chitinases sequences. These analyses provide insight into the potential reservoir of novel molecules in metagenomic databases while supporting the chitinase mining pipeline developed in this work. By using our chitinase mining pipeline, a larger number of previously unannotated metagenomic chitinase sequences can be classified, enabling further studies on these enzymes.

Sequence Pair-Based Scatter Search Approach for Cell Formation and Layout Considering Unequal Machine Dimensions and Cell Input and Output Locations

In the purpose of dealing with the inconsistency of the machine dimensions in cell formation and layout problems,comprehensively taking into account such factors as alternative process routings, lot splitting, cell input and output( I / O)locations,an integrated cell formation and layout model considering unequal machine dimensions is established which aims at minimizing intra-cell material handling cost,inter-cell material handling cost and cell expansion cost. A sequence pair-based scatter search algorithm is proposed which simultaneously adopts the roulette wheel selection operator as a subsets combination method to improve the quality of new solutions and the dynamic reference sets updating method to accelerate the convergence rate. Through the comparison of the results achieved by the proposed algorithm, Lingo and simulated annealing under different problem scales,the correctness of the model and the effectiveness of the algorithm are verified.

Cuckoo search algorithm-based optimal deployment method of heterogeneous multistatic radar for barrier coverage

This paper proposes an optimal deployment method of heterogeneous multistatic radars to construct arc barrier coverage with location restrictions.This method analyzes and proves the properties of different deployment patterns in the optimal deployment sequence.Based on these properties and considering location restrictions,it introduces an optimization model of arc barrier coverage and aims to minimize the total deployment cost of heterogeneous multistatic radars.To overcome the non-convexity of the model and the non-analytical nature of the objective function,an algorithm combining integer line programming and the cuckoo search algorithm(CSA)is proposed.The proposed algorithm can determine the number of receivers and transmitters in each optimal deployment squence to minimize the total placement cost.Simulations are conducted in different conditions to verify the effectiveness of the proposed method.

A hybrid algorithm based on tabu search and large neighbourhood search for car sequencing problem

The car sequencing problem(CSP)concerns a production sequence of different types of cars in the mixed-model assembly line.A hybrid algorithm is proposed to find an assembly sequence of CSP with minimum violations.Firstly,the hybrid algorithm is based on the tabu search and large neighborhood search(TLNS),servicing as the framework.Moreover,two components are incorporated into the hybrid algorithm.One is the parallel constructive heuristic(PCH)that is used to construct a set of initial solutions and find some high quality solutions,and the other is the small neighborhood search(SNS)which is designed to improve the new constructed solutions.The computational results show that the proposed hybrid algorithm(PCH+TLNS+SNS)obtains100best known values out of109public instances,among these89instances get their best known values with100%success rate.By comparing with the well-known related algorithms,computational results demonstrate the effectiveness,efficiency and robustness of the proposed algorithm.

MARS and RNAcmap3:The Master Database of All Possible RNA Sequences Integrated with RNAcmap for RNA Homology Search

sequences found in the huge,integrated database of protein sequences(Big Fantastic Database).In contrast,the existing nucleotide databases were not consolidated to facilitate wider and deeper homology search.Here,we built a comprehensive database by incorporating the non-coding RNA(ncRNA)sequences from RNAcentral,the transcriptome assembly and metagenome assembly from metagenomics RAST(MG-RAST),the genomic sequences from Genome Warehouse(GWH),and the genomic sequences from MGnify,in addition to the nucleotide(nt)database and its subsets in National Center of Biotechnology Information(NCBI).The resulting Master database of All possible RNA sequences(MARS)is 20-fold larger than NCBI’s nt database or 60-fold larger than RNAcentral.The new dataset along with a new split-search strategy allows a substantial improvement in homology search over existing state-of-the-art techniques.It also yields more accurate and more sensitive multiple sequence alignments(MSAs)than manually curated MSAs from Rfam for the majority of structured RNAs mapped to Rfam.The results indicate that MARS coupled with the fully automatic homology search tool RNAcmap will be useful for improved structural and functional inference of ncRNAs and RNA language models based on MSAs.MARS is accessible at https://ngdc.cncb.ac.cn/omix/release/OMIX003037,and RNAcmap3 is accessible at http://zhouyq-lab.szbl.ac.cn/download/.

生物序列搜索算法hmmsearch的加速技术

在FPGA平台实现细粒度并行的hmmsearch加速技术。采用数据预取、滑动窗口和数据传递等策略实现子处理单元的数据重用。在计算矩阵块内部实现流水线计算。加速器性能为3.59 GCUPS,与CPU相比,可获得接近235倍的加速效果。与目前FPGA上同性质最快的加速器相比,单PE可获得34%的性能提升。

基于LightGBM-VIF-MIC-SFS的风电机组故障诊断输入特征选择方法

针对风电机组数据采集与监视控制(SCADA)系统数据维数较高、特征冗余、特征相关性高导致风电机组的故障诊断过程存在误差大、分类正确率低的问题,提出一种基于LightGBM-VIF-MIC-SFS的三段式特征选择方法。首先,根据LightGBM实现对所有特征的重要性计算,确定初步特征空间;其次,根据方差膨胀因子(VIF)和最大信息系数(MIC)构建相关性判别阵,据此评估一次筛选中重要性相近的特征,舍弃相似性高的输入特征;最后,使用序列前向搜索法对特征进行第3次处理,逐个输入前2次特征选择获得的特征,保留能提升系统性能的特征,从而实现最终特征的选取。在完成了模型的建立后,使用风电场真实SCADA系统数据进行性能评估,将所提方法与2种对比算法在6个数据集上进行对比,结果显示所提出的LightGBM-VIF-MIC-SFS相较2种对比特征选择算法有显著优势。对所提方法内部的3个模块进行了消融实验,有效验证了所提特征选取方法内部各个模块的有效性以及基于所提方法得到的最优特征空间的合理性及准确性。

改进布谷鸟算法在装配序列规划中的应用研究

针对装配序列规划问题,建立考虑装配序列的几何可行性、稳定性、聚合性、重定向性的装配关系模型以及基于适应度函数的装配序列优化数学模型。提出一种改进布谷鸟算法对装配序列规划问题进行求解,采用随机键和最小位置规则的方法设计基于零件编号、装配方向、装配工具的3层编码方案;设计基于最小装配成本的初始化策略与随机初始化策略相结合的混合种群初始化策略,提高种群质量;改进种群进化和搜索方式,将种群分为3个子群,并分别采用自适应步长飞行、标准步长飞行和交叉、变异的方式进行种群更新,提高算法的收敛速度和求解精度。最后通过实例应用及与其他算法的比较,验证了所提出的改进布谷鸟算法在求解装配序列规划问题上的有效性和优越性。

一种针对驻留转换雷达的信号分选算法

复杂电磁环境下驻留转换雷达的信号分选是制约电子侦察技术发展的瓶颈,由于其复杂多变的成形规律,信号子周期难以被检测;脉冲重复周期调制类型不明,脉冲序列无法成功提取;提取的多个子周期脉冲序列无法合并为一部雷达信号,造成虚警。针对以上问题,提出一种针对驻留转换雷达的信号分选算法,利用双门限提高子周期检测概率,通过霍夫变换结合迭代自组织聚类判断信号是否属于驻留转换雷达,改进搜索算法以提取脉冲序列,依据排列熵指标将多脉冲序列合并为一部驻留转换雷达信号。仿真实验结果表明,所提算法在25%脉冲丢失率的复杂电磁环境下,可以将三部驻留转换雷达信号成功分选。

基于深度蒙特卡洛树搜索的拱坝仓面排序研究

合理的仓面排序方案对于加快工程进度和优化资源配置有着重要影响。然而,现有仓面排序方法将这一序贯决策问题简化,多数采用多属性决策方法,存在仅对大坝实时施工状态进行分析以及未考虑未来仓面浇筑方案对当前排序策略影响的问题;部分采用多目标优化方法进行仓面排序多目标优化问题分析,但主要是采用静态权重,存在忽略了仓面排序策略随环境动态变化的不足。针对以上问题,本文提出基于深度蒙特卡洛树搜索的拱坝仓面排序方法。首先,分析仓面排序问题的约束条件和目标函数,建立仓面排序强化学习模型;其次,针对仓面排序强化学习模型具有复杂且庞大的离散状态空间,为提高搜索效率,提出融合深度学习的蒙特卡洛树搜索方法,分别利用深度神经网络进行先验动作概率分布预测和策略函数评估;最后,以乌东德拱坝工程为例进行研究,结果表明本文方法可以有效地分析拱坝仓面排序问题,且相比于粒子群方法、证据理论方法,本文方法分析的施工工期可分别提前6天、14天,平均机械利用率分别提高1.19%、1.35%。本研究为拱坝仓面排序分析与优化提供了新思路。

Cell search scheme for long-term evolution of TD-SCDMA system

Cell search is an important aspect for 3G long-term evolution （LTE）. This article deals with cell search in the time-division-synchronou code-division multiple access （TD-SCDMA） LTE system. On the basis of the synchronization channel （SCH） and cell specific reference symbols （CSRSs）, the proposed cell search procedure includes five stages： frame detection and coarse timing, coarse carrier frequency offset （CFO） estimation, fine timing, fine CFO estimation, and cell identification. The key features of the proposed method are as follows： first, the neighboring three cells＇ CSRSs are frequency division multiplexed （FD） to mitigate inter-cell interference. Second, the frequency domain differential cross-correlation, computed from CSRSs are maximally ratio combined for cell identification. Finally, the large set Kasami sequences are quadrature phase shift key （QPSK） modulated to be cell specific sequences （CSSs）, to support a large number of target cells. Simulations show that the FD method is better than the code division multiplexed （CD） method.

基于时序序列分解和IBAS LSTM的滑坡数据预测模型

针对传统静态机器学习模型在周期项位移预测中的缺陷和动态神经网络超参数人工选择困难的问题,在时序序列分解的基础上,提出一种新的滑坡预测耦合模型。首先,用最大相关最小冗余算法对周期项位移筛选合适的环境特征,作为长短期记忆人工神经网络的输入。然后,在天牛须搜索算法搜索过程中引入反馈机制,以避免原算法中出现远离最优解的问题;在算法迭代过程中将固定的递减因子改为动态递减因子,以提升前期全局和后期局部的寻优能力;利用改进的天牛须搜索算法对长短期记忆人工神经网络超参数进行寻优,以获得最佳的网络参数组合。最后,重构趋势项和周期项预测结果,得到最终预测位移。以发耳滑坡为例进行分析,结果表明:相较于其他方法,所提模型在平均绝对误差、均方根误差以及拟合度等方面更具优势。

多车场带时间窗车辆路径问题的改良自适应大邻域搜索算法

针对多车场带时间窗车辆路径问题(MDVRPTW),提出一种改良自适应大邻域搜索算法(IALNS)。首先,在构造初始解阶段改进一种路径分割算法;其次,在优化阶段利用设计的移除和修复启发式算子相互竞争择优选取算子,为各算子引入评分机制,采用轮盘赌方式选取启发式算子;同时,将迭代周期分段,动态调整各周期内的算子权重信息,有效避免算法陷入局部最优;最后,采取模拟退火机制作为解的接受准则。在Cordeau规范算例上进行实验,确定IALNS的相关参数,将所提算法求解结果与该领域其他代表性研究成果对比。实验结果表明,所提算法与变邻域搜索(VNS)算法的求解误差不超过0.8%,在某些算例上甚至更优;与多相位改进的蛙跳算法相比,算法的平均耗时减少12.8%,所提算法在绝大多数算例上运行时间更短。因此,验证了所提算法是求解MDVRPTW的有效算法。

改进爬行动物搜索算法的线阵波束形成研究

针对最小方差无畸变响应方法在已知先验信息的情况下抗干扰性能较差的问题,提出了基于改进爬行动物搜索的波束形成方向图控制算法。该算法通过设置合适的适应度函数,迭代寻找最优权值,并利用其实现对方向图的控制。首先采用Sobol序列对种群初始化方法进行改进,获得更均匀的种群初始分布;其次,改进进化因子提高该算法的收敛速度;最后,为了增强抗干扰性能,对适应度函数进行改进,使方向图旁瓣更低。仿真实验表明,相较于传统算法,该算法可以获得更深的零陷并将其准确的对准干扰来向,同时降低峰值旁瓣电平,提高了对干扰的抑制能力,使得元启发式算法在波束形成领域更具应用价值。

PCSS-SC下基于并行导频序列的一种主动式RAKE接收技术

为解决并行组合扩频散射传输系统信道中存在的严重多径衰落效应,提出一种基于并行导频序列的主动式RAKE接收技术。该技术利用扩频序列PN的自相关特性,添加额外并行扩频序列作为收发已知的导频信号,设计适用在并行组合扩频散射通信的系统模型,并提出该模型下的多径搜索和时延估计方法,利用散射信道相干时间减少导频序列占比。通过仿真对比分析,在SNR=-8 dB时,信号识别概率能达到90%以上,低信噪比范围内,相比无抗多径技术可以提升60%左右的正确识别概率;区分充分多径和不充分多径进行系统误码率性能仿真分析,在SNR>-2 dB的区间内,相比无抗多径技术误码率大小均降低了三个数量级以上。结果说明文中技术能有效地对抗系统存在的多径衰落,保持较好的工作性能,保证数据稳定传输。

A Hybrid Modified Sine Cosine Algorithm Using Inverse Filtering and Clipping Methods for Low Autocorrelation Binary Sequences

The essential purpose of radar is to detect a target of interest and provide information concerning the target’s location,motion,size,and other parameters.The knowledge about the pulse trains’properties shows that a class of signals is mainly well suited to digital processing of increasing practical importance.A low autocorrelation binary sequence(LABS)is a complex combinatorial problem.The main problems of LABS are low Merit Factor(MF)and shorter length sequences.Besides,the maximum possible MF equals 12.3248 as infinity length is unable to be achieved.Therefore,this study implemented two techniques to propose a new metaheuristic algorithm based on Hybrid Modified Sine Cosine Algorithm with Cuckoo Search Algorithm(HMSCACSA)using Inverse Filtering(IF)and clipping method to achieve better results.The proposed algorithms,LABS-IF and HMSCACSA-IF,achieved better results with two large MFs equal to 12.12 and 12.6678 for lengths 231 and 237,respectively,where the optimal solutions belong to the skew-symmetric sequences.The MF outperformed up to 24.335%and 2.708%against the state-of-the-art LABS heuristic algorithm,xLastovka,and Golay,respectively.These results indicated that the proposed algorithm’s simulation had quality solutions in terms of fast convergence curve with better optimal means,and standard deviation.

基于城市公园绿地公平性提升的非正式绿地更新时序——以徐州市鼓楼区为例

在全球气候变化等诸多挑战下,实现城市绿地的均衡配置是增加城市韧性、保证居民健康幸福的重要途径,而高密度城区绿地的均衡发展存在极大空间限制,基于此,提出将非正式绿地(IGS)作为提升城市绿地公平性的重要潜在空间,以不同方式将IGS纳入现有公园绿地系统,以缓解绿地资源不公平的问题。以徐州市老工业区鼓楼区为例,基于高斯两步移动搜索法、基尼系数方法,量化鼓楼区公园绿地公平性现状水平,进而建立一种以促进绿地公平性为目标的IGS更新时序评估方法。研究结果表明:(1)徐州市鼓楼区公园绿地处于严重不公平状态,公园绿地现状基尼系数高达0.79。(2)78.46%(51块)的IGS对于提升鼓楼区公园绿地公平性具有不同程度的潜力,但“非常高”和“高”潜力值IGS占比仅为1.54%和4.62%,提升潜力有限。(3)鼓楼区公园绿地布局优化方案中拟新增综合公园选址10处、社区公园选址8处、游园选址3处。研究结果可为高密度城市建成区的绿地更新规划提供精细化参考,也可作为棕地、闲置地功能更新决策的重要依据。

基于改良和声搜索的电力系统动态经济调度

针对电力系统动态经济调度(Dynamic economic dispatch,DED)问题提出了一种改良和声搜索算法(Reformed harmony search,RHS)求解。RHS在原始和声搜索算法的基础上进行了四方面改进:第一,以100%概率执行和声记忆步骤,排除了随机化步骤。第二,使用基于混沌序列的随机数对基音调整率进行扰动,使其在整个迭代过程中始终处于动态变化的状态。第三,根据当前和声记忆库获得每个变量的动态上下限,以此确定基音调整步长。第四,引入了一种全局搜索步骤,该步骤根据全局最优和声向量对当前和声向量进行更新。上述四个步骤有利于提高RHS算法的收敛性、种群多样性以及对问题的自适应性。实验表明,RHS在求解三种DED问题时能获得比其他两种算法更低的发电成本,因此,它具有更好的优化性能,是求解DED问题的一种有效方法。