基于Mann-Kendall方法的闽江流域降水趋势分析

基于闽江流域1965年~2020年逐日降水资料,利用Mann-Kendall方法进行趋势分析。结果表明:①闽江流域1965年~2020年平均降水量约为1653 mm,有明显的时间规律和区域分布特点。汛期降水量占全年降水量的70%左右,降水在空间上呈现由上游至下游,从西北至东南减少的趋势;②闽江流域全年降水量呈上升趋势,但趋势不显著。汛期及非汛期期间内,多数站点的降水量呈现递增变化,少数站点表现为弱减少;③闽江流域汛期有雨日的日平均雨强有增加趋势,提高了洪水风险,增加了防洪难度。

伊犁河谷旅游气候变化特征分析——基于Mann-Kendall检验

旅游气候对旅游业发展的影响显著,分析旅游气候规律对于科学合理制定旅游业发展对策具有重要意义。基于Mann-Kendall检验伊犁河谷旅游气候变化规律,发现近59年来伊犁河谷年平均气温总趋势呈现波动升高态势,年降水量略呈波动增长趋势,年平均风速呈波动减小趋势,平均相对湿度变化幅度较小;气温、降水呈“V”型变化趋势;各县市年平均气温均表现为波动增长趋势,但其年平均气温差异较大,且风寒指数、着衣指数差异较大,对旅游具有一定区域性影响。

浅谈Mann-Kendall法分析蚌埠市降水量变化趋势

研究降水的趋势演变规律一直以来都是水文、气象领域的热点,其研究结果对于地区防洪减灾具有非常重要的意义,可以为降水和水资源长期预测提供依据,也为水资源合理开发与利用提供了参考。以安徽省蚌埠水文局辖区内23个水文基本雨量站1950—2022年各月、年降水量资料序列为基础,采用Mann-Kendall趋势分析法,分析了蚌埠市近73年春、夏、秋、冬四季及年降水量序列的趋势。分析结果为淮河流域蚌埠-洪泽湖区间降水预测及水资源合理调配等提供了最新的理论依据。

基于Mann-Kendall和Wavelet分析的唐山市近60年来降水量时空变化研究

降水量时空变化研究,对了解和预测气候变化趋势、合理规划水资源,以及应对极端天气事件具有重要意义。基于唐山市12个标准气象站点的1961-2020年观测资料,采用Mann-Kendall和Wavelet方法相结合的方式,对唐山市降水量时变性进行分析。结果表明,近60年来研究区降水量变化斜率为-1.59mm/a,经Mann-Kendall检测的趋势值Sen’slo值为-1.23mm/a;年际降水量于2014年发生突变,但并不显著;利用Wavelet分析发现,区域降水量存在1~8、7~10、14~16年的变化周期。

基于Mann-Kendall趋势检验的城市能源碳达峰评估方法

能源是城市碳排放的重要组成,评估城市能源碳达峰是践行国家“双碳”战略的必要手段.为此,针对城市能源的碳排放水平,提出了一种基于Mann-Kendall趋势检验的能源碳达峰评估方法.通过构建涵盖能源碳排放量、清洁能源发电量、交通电能替代量等要素的碳监测体系,结合历史数据计算城市的能源碳排放总量.鉴于能源碳排放具有季节性和随机性,采用Mann-Kendall趋势检验法,建立城市能源碳达峰判断模型,衡量不同时期区域碳排放水平.以上海某行政区为例,从年度、季度视角,判断该区域的能源碳达峰状态.计算结果表明,基于年度数据,该地区在2020年已实现能源碳达峰;基于季度数据,夏季与秋季已实现能源碳达峰,春季和冬季仍处于平台期.该方法可应用于评估城市级的碳达峰状态,为检验各省市的碳达峰进程提供参考.

基于Mann-Kendall法的祖厉河流域水沙特征及趋势分析

为了探究半干旱黄土区水沙特征及变化趋势,采用Mann-Kendall非参数检验法,对祖厉河流域2001—2016年的降水量、径流量与输沙量进行了分析研究。结果表明:研究期内年降水量呈不明显增加趋势,年变化幅度为1.83 mm/a,汛期降水量呈减少趋势,年变化幅度为-2.01 mm/a;年径流量与汛期径流量变化曲线基本一致,总体都呈显著波动下降趋势(P<0.05),径流量年变化幅度为-3.85×10^(6) m^(3)/a,汛期径流量年变化幅度为-2.729×10^(6) m^(3)/a,二者突变时间均在2013年左右,突变以后UF k值超过95%的信度线(α=0.05),呈现急剧减少趋势;输沙量和径流量呈现相似的显著减少趋势,年输沙量与汛期输沙量变化曲线基本一致,年输沙量和汛期输沙量年变化幅度均为-1.06×10^(6) t/a,二者突变开始时间均在2011—2012年之间,2014年以后UF k值超过95%的信度线(α=0.05),呈急剧减少趋势。

基于Sen+Mann-Kendall陕西省植被覆盖度时空变化规律研究

研究长时段、多尺度植被覆盖度时空格局变化及其影响因素对于监测陕西省环境变化,保障生态环境高质量发展具有重要意义。基于MOD17A3H数据、采用Sen趋势分析以及Mann-Kendall显著性检验,对陕西省2000—2019年植被覆盖度时空格局变化进行研究。结果表明:时间上,2010—2019年陕西省植被覆盖度呈波动增长趋势,植被生长环境不断改善;空间上,自北向南,植被覆盖度整体呈低-高-低-高分布,植被覆盖度年际变化趋势呈增-减-增-减分布,两者空间上具有一定互补性;Sen+Mann-Kendall方法对于异常值不敏感,对于数据分布无要求,可以广泛应用到植被覆盖度变化趋势分析中。

基于Mann-Kendall和小波功率谱的丹东市近35年降水量变化特征解析

为探究丹东市降水时空变化规律,以1986—2020年站点观测资料和降水栅格数据为基础,运用Mann-Kendall检验、Morlet分析和统计方法,研究了该地降水倾向趋势、变化周期及空间分布。结果显示,丹东近35年来平均降水量以3.79mm/a的速率增加,但趋势不显著。降水变化具有多个短震荡周期,主周期为6a,在2000年发生弱突变。受季风与地形影响,降水量呈现中高周低分布,空间差异为823~1098mm。文章揭示了近35年丹东降水量变化特征,可为区域水资源管理提供参考依据。

基于Mann-Kendall法的流域降雨与地下水位时空变化特征研究

降水量在空间和时间上的变化会影响水资源的可用性,导致农业、生态和基础设施受损。在区域和局部尺度上,降雨均有增加和减少的趋势。降雨强度增加可能导致山洪暴发,降水减少也会影响水的可用性和水质。如何预测降水量在时空中的变化趋势具有重要意义。采用Mann-Kendall方法对河北某区域降雨量变化趋势及特征进行分析,并分析观测井的降雨量与地下水水位之间的关系,研究成果可知:4个观测台站中,H台站接收的年降雨量最大,最大值达到了5 153 mm,而K-K台站最大降雨量仅次于H站台,为3 598 mm。地下水位变化与降雨变化趋势相同。可为相关工程提供参考。

基于Mann-Kendall法的西宁市降水量变化规律分析

利用青海省西宁市4个气象站60年的降水资料,采用Mann-Kendall检验方法分析了降水量的年际、年代际变化特征及趋势,研究了该地区多年降水量的时程变化规律并得出该地区降水相关特征量的变化特征。结果表明:西宁地区年降水量整体呈现上升趋势,降水量的季节性差异较大,汛期表现出较为明显的上升趋势;年降水日数也呈现上升趋势,但上升趋势不显著;西宁市降水量在2005年发生突变。分析结果可为西宁市未来降水资源合理利用、洪涝灾害防治等工作提供参考依据。

Underwater four-quadrant dual-beam circumferential scanning laser fuze using nonlinear adaptive backscatter filter based on pauseable SAF-LMS algorithm

The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant dual-beam circumferential scanning laser fuze to distinguish various interference signals and provide more real-time data for the backscatter filtering algorithm.This enhances the algorithm loading capability of the fuze.In order to address the problem of insufficient filtering capacity in existing linear backscatter filtering algorithms,we develop a nonlinear backscattering adaptive filter based on the spline adaptive filter least mean square(SAF-LMS)algorithm.We also designed an algorithm pause module to retain the original trend of the target echo peak,improving the time discrimination accuracy and anti-interference capability of the fuze.Finally,experiments are conducted with varying signal-to-noise ratios of the original underwater target echo signals.The experimental results show that the average signal-to-noise ratio before and after filtering can be improved by more than31 d B,with an increase of up to 76%in extreme detection distance.

Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor networks.This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies.The proposed algorithms lack algorithm-specific parameters and metaphorical connotations.The proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned solutions.The proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing protocol.We compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)algorithms.The efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base station.The experimental results were compared with those obtained using the Jaya optimization algorithm.The proposed algorithms exhibited the best performance.The proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base station.

Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

Product quality prediction based on RBF optimized by firefly algorithm

With the development of information technology,a large number of product quality data in the entire manufacturing process is accumulated,but it is not explored and used effectively.The traditional product quality prediction models have many disadvantages,such as high complexity and low accuracy.To overcome the above problems,we propose an optimized data equalization method to pre-process dataset and design a simple but effective product quality prediction model:radial basis function model optimized by the firefly algorithm with Levy flight mechanism(RBFFALM).First,the new data equalization method is introduced to pre-process the dataset,which reduces the dimension of the data,removes redundant features,and improves the data distribution.Then the RBFFALFM is used to predict product quality.Comprehensive expe riments conducted on real-world product quality datasets validate that the new model RBFFALFM combining with the new data pre-processing method outperforms other previous me thods on predicting product quality.

Path Planning for AUVs Based on Improved APF-AC Algorithm

With the increase in ocean exploration activities and underwater development,the autonomous underwater vehicle(AUV)has been widely used as a type of underwater automation equipment in the detection of underwater environments.However,nowadays AUVs generally have drawbacks such as weak endurance,low intelligence,and poor detection ability.The research and implementation of path-planning methods are the premise of AUVs to achieve actual tasks.To improve the underwater operation ability of the AUV,this paper studies the typical problems of path-planning for the ant colony algorithm and the artificial potential field algorithm.In response to the limitations of a single algorithm,an optimization scheme is proposed to improve the artificial potential field ant colony(APF-AC)algorithm.Compared with traditional ant colony and comparative algorithms,the APF-AC reduced the path length by 1.57%and 0.63%(in the simple environment),8.92%and 3.46%(in the complex environment).The iteration time has been reduced by approximately 28.48%and 18.05%(in the simple environment),18.53%and 9.24%(in the complex environment).Finally,the improved APF-AC algorithm has been validated on the AUV platform,and the experiment is consistent with the simulation.Improved APF-AC algorithm can effectively reduce the underwater operation time and overall power consumption of the AUV,and shows a higher safety.

Investigation into Recent Temperature and Rainfall Trends in Mali Using Mann-Kendall Trend Test: Case Study of Bamako

Rainfall and temperature variability analysis is important for researchers and policy formulators in making critical decisions on water availability and use in communities. The Western Sahel, which comprises Mali is considered as one of the vulnerable regions to climate change, and also encountered the challenges of climatic shocks such as flood and drought. This research therefore sought to investigate climate change effects on hydrological events and trends in Sahelian rainfall intensity using Bamako (Mali) as a case study from 1991 to 2020, as limited data availability did not allow an extended period of study. Monthly observed data provided by MALI-METEO was used to validate daily rainfalls data from African Rainfall Climatology Version 2 (ARC2) satellite-based rainfall product on monthly basis. The validated model performance used Nash-Sutcliffe Efficiency (NSE) and Percent Bias (PBAIS) and gave results of 0.904 and 1.0506 respectively. Trends in annual maximum temperatures and rainfalls were analyzed using Mann-Kendall trend test. The result indicated that the trend in annual maximum rainfalls was decreasing, while annual total rainfall was increasing but not significant at 5% significance level. The rate of increase in annual total rainfalls was 0.475 mm/year according to the observed annual rainfall series and decreased to 0.68 mm/year in annual maximum. The analysis further found that annual maximum temperatures were increasing at the rate of 0.03°C/year at 5% significance level. To provide more accurate climate predictions, it is recommended that further studies on rainfall and temperature with data sets spanning 60 - 90 years be carried out.

A Review of Image Steganography Based on Multiple Hashing Algorithm

Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a significant problem.The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest.Therefore,several approaches,including steganography,have been developed by researchers over time to enable safe data transit.In this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,etc.We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)approach.In this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this strategy.Before encoding the data and embedding it into a carry image,this review verifies that it has been encrypted.Usually,embedded text in photos conveys crucial signals about the content.This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport.If the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.

Algorithm Selection Method Based on Coupling Strength for Partitioned Analysis of Structure-Piezoelectric-Circuit Coupling

In this study, we propose an algorithm selection method based on coupling strength for the partitioned analysis ofstructure-piezoelectric-circuit coupling, which includes two types of coupling or inverse and direct piezoelectriccoupling and direct piezoelectric and circuit coupling. In the proposed method, implicit and explicit formulationsare used for strong and weak coupling, respectively. Three feasible partitioned algorithms are generated, namely(1) a strongly coupled algorithm that uses a fully implicit formulation for both types of coupling, (2) a weaklycoupled algorithm that uses a fully explicit formulation for both types of coupling, and (3) a partially stronglycoupled and partially weakly coupled algorithm that uses an implicit formulation and an explicit formulation forthe two types of coupling, respectively.Numerical examples using a piezoelectric energy harvester,which is a typicalstructure-piezoelectric-circuit coupling problem, demonstrate that the proposed method selects the most costeffectivealgorithm.

Hybrid Optimization Algorithm for Handwritten Document Enhancement

The Gannet Optimization Algorithm (GOA) and the Whale Optimization Algorithm (WOA) demonstrate strong performance;however, there remains room for improvement in convergence and practical applications. This study introduces a hybrid optimization algorithm, named the adaptive inertia weight whale optimization algorithm and gannet optimization algorithm (AIWGOA), which addresses challenges in enhancing handwritten documents. The hybrid strategy integrates the strengths of both algorithms, significantly enhancing their capabilities, whereas the adaptive parameter strategy mitigates the need for manual parameter setting. By amalgamating the hybrid strategy and parameter-adaptive approach, the Gannet Optimization Algorithm was refined to yield the AIWGOA. Through a performance analysis of the CEC2013 benchmark, the AIWGOA demonstrates notable advantages across various metrics. Subsequently, an evaluation index was employed to assess the enhanced handwritten documents and images, affirming the superior practical application of the AIWGOA compared with other algorithms.

Representation of an Integer by a Quadratic Form through the Cornacchia Algorithm

Cornachia’s algorithm can be adapted to the case of the equation x2+dy2=nand even to the case of ax2+bxy+cy2=n. For the sake of completeness, we have given modalities without proofs (the proof in the case of the equation x2+y2=n). Starting from a quadratic form with two variables f(x,y)=ax2+bxy+cy2and n an integer. We have shown that a primitive positive solution (u,v)of the equation f(x,y)=nis admissible if it is obtained in the following way: we take α modulo n such that f(α,1)≡0modn, u is the first of the remainders of Euclid’s algorithm associated with n and α that is less than 4cn/| D |) (possibly α itself) and the equation f(x,y)=n. has an integer solution u in y. At the end of our work, it also appears that the Cornacchia algorithm is good for the form n=ax2+bxy+cy2if all the primitive positive integer solutions of the equation f(x,y)=nare admissible, i.e. computable by the algorithmic process.