Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.

Some results of modeling D-D seismogenic pattern by the fracture model experiment of large-scale rock samples(I)

sing the natural limestone samples taken from the field with dimension of 500 mm×500 mm×1 000 mm, the D-D (dilatancy-diffusion) seismogeny pattern was modeled under the condition of water injection, which observes the time-space evolutionary features about the relative physics fields of the loaded samples from deformation, formation of microcracks to the occurrence of main rupture. The results of observed apparent resistivity show: ① The process of the deformation from microcrack to main rupture on the loaded rock sample could be characterized by the precursory spatial-temporal changes in the observation of apparent resistivity; ② The precursory temporal changes of observation in apparent resistivity could be divided into several stages, and its spatial distribution shows the difference in different parts of the rock sample; ③ Before the main rupture of the rock sample the obvious ″tendency anomaly′ and ′short-term anomaly″ were observed, and some of them could be likely considered as the ″impending earthquake ″anomaly precursor of apparent resistivity. The changes and distribution features of apparent resistivity show that they are intrinsically related to the dilatancy phenomenon of the loaded rock sample. Finally, this paper discusses the mechanism of resistivity change of loaded rock sample theoretically.

Low-Level Temperature Inversions and Their Effect on Aerosol Condensation Nuclei Concentrations under Different Large-Scale Synoptic Circulations

Knowledge of the statistical characteristics of inversions and their effects on aerosols under different large-scale synoptic circulations is important for studying and modeling the diffusion of pollutants in the boundary layer. Based on results gen- erated using the self-organizing map （SOM） weather classification method, this study compares the statistical characteristics of surface-based inversions （SBIs） and elevated inversions （EIs）, and quantitatively evaluates the effect of SBIs on aerosol condensation nuclei （CN） concentrations and the relationship between temperature gradients and aerosols for six prevailing synoptic patterns over the the Southern Great Plains （SGP） site during 2001-10. Large-scale synoptic patterns strongly influ- ence the statistical characteristics of inversions and the accumulation of aerosols in the low-level atmosphere. The activity, frequency, intensity, and vertical distribution of inversions are significantly different among these synoptic patterns. The verti- cal distribution of inversions varies diurnally and is significantly different among the different synoptic patterns. Anticyclonic patterns affect the accumulation of aerosols near the ground more strongly than cyclonic patterns. Mean aerosol CN con- centrations increase during SBIs compared to no inversion cases by 16.1%, 22.6%, 24.5%, 58.7%, 29.8% and 23.7% for the six synoptic patterns. This study confirms that there is a positive correlation between temperature gradients and aerosol CN concentrations near the ground at night under similar large-scale synoptic patterns. The relationship is different for different synoptic patterns and can be described by linear functions. These findings suggest that large-scale synoptic patterns change the static stability of the atmosphere and inversions in the lower atmosphere, thereby influencing the diffusion of aerosols near the ground.

Large-scale conditions of Tibet Plateau vortex departure

Based on the circumfluence situation of the out- and in-Tibet Plateau Vortex (TPV) from 1998–2004 and its weather-influencing system,multiple synthesized physical fields in the middle–upper troposphere of the out- and in-TPV are computationally analyzed by using re-analysis data from National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) of United States.Our research shows that the departure of TPV is caused by the mutual effects among the weather systems in Westerlies and in the subtropical area,within the middle and the upper troposphere.This paper describes the large-scale meteorological condition and the physics image of the departure of TPV,and the main differences among the large-scale conditions for all types of TPVs.This study could be used as the scientific basis for predicting the torrential rain and the floods caused by the TPV departure.

Evaluation of meteorological predictions by the WRF model at Barrow, Alaska and Summit, Greenland in the Arctic in April 2019

Accurate meteorological predictions in the Arctic are important in response to the rapid climate change and insufficient meteorological observations in the Arctic.In this study,we adopted a high-resolution Weather Research and Forecasting(WRF)model to simulate the meteorology at two Arctic stations(Barrow and Summit)in April 2019.Simulation results were also evaluated by using surface measurements and statistical parameters.In addition,weather charts during the studied time period were also used to assess the model performance.The results demonstrate that the WRF model is able to accurately capture the meteorological parameters for the two Arctic stations and the weather systems such as cyclones and anticyclones in the Arctic.Moreover,we found the model performance in predicting the surface pressure the best while the performance in predicting the wind the worst among these meteorological predictions.However,the wind predictions at these Arctic stations were found to be more accurate than those at urban stations in mid-latitude regions,due to the differences in land features and anthropogentic heat sources between these regions.In addition,a comparison of the simulation results showed that the prediction of meteorological conditions at Summit is superior to that at Barrow.Possible reasons for the deviations in temperature predictions between these two Arctic stations are uncertainties in the treatments of the sea ice and the cloud in the model.With respect to the wind,the deviations may source from the overestimation of the wind over the sea and at coastal stations.

The Influence of Large-Scale Phenomena on La Paz Bay Hydrographic Variability

We analyzed the hydrographic variability of La Paz Bay, the largest coastal water body in the Gulf of California, and its relationship with Pacific large-scale phenomena, including the El Ni?o-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Pacific-North America pattern (PNA), and North Pacific pattern (NP). We used several indices related to these phenomena and the hydrographic variability data of La Paz Bay, consisting of the annual sea surface temperature patterns from satellite imagery from 2000 to 2010 and the mixed layer depths measured with?in situ?data from 1994 to 2009. The results indicate the sea surface temperature fluctuated during the study period, with 2007 as the coldest year and 2009 as the warmest. Two periods were identified in the annual thermal cycle of the bay, one period of warmth from June to November, and one of cold from December to May. The sea surface temperature is primarily influenced by the ENSO. The mixed layer depth analysis showed its absence during August-September, while the deepest ones were in November-March. The unusual 100 m mixed layer depth noted during February 2002 and its absence in March 1996 and 2009 were related to uncommon atmospheric conditions in the annual patterns of the ENSO, PNA, and NP. The variability of the mixed layer depth is primarily related to the variability of the NP. We concluded that the hydrographic conditions of La Paz Bay are most influenced by the NP during the cold phase of its annual cycle, and by the ENSO during the warm phase.

Meteorological mechanism for a large-scale persistent severe ozone pollution event over eastern China in 2017

An intensive and persistent regional ozone pollution event occurred over eastern China from 25 June to 5 July 2017.73 out of 96 selected cities,most located in the Beijing-TianjinHebei and the surrounding area(BTHS),suffered severe ozone pollution.A north-south contrast ozone distribution,with higher ozone(199±33μg/m3)in the BTHS and lower ozone(118±25μg/m^3)in the Yangtze River Delta(YRD),was found to be dominated by the position of the West Pacific Subtropical High(WPSH)and mid-high latitude wave activities.In the BTHS,the positive anomalies of geopotential height at 500 hPa and temperature at the surface indicated favorable meteorological conditions for local ozone formation.Prevailing northwesterly winds in the mid-high troposphere and warm advection induced by weak southerly winds in the low troposphere resulted in low-moderate relative humidity(RH),less total cloud cover(TGC),strong solar radiation and high temperatures.Moreover,southerly winds prevailing over the BTHS aggravated the pollution due to regional transportation of O3 and its precursors.On one hand,the deep sinking motion and inversion layer suppressed the dispersion of pollutants.On the other hand,O3-rich air in the upper layer was maintained at night due to temperature inversion,which facilitated O3 vertical transport to the surface in the next-day morning due to elevated convection.Generally,temperature,UV radiation,and RH showed good correlations with O3 in the BTHS,with rates of 8.51(μg/m^3)/℃(within the temperature range of 20-38℃),59.54(μg/m^3)/(MJ/m^2)and-1.93(μg/m^3)/%,respectively.

Evolution Process of Urban Spatial Pattern in Hubei Province Based on DMSP/OLS Nighttime Light Data

This paper intends to investigate the urban spatial patterns of Hubei Province and its evolution from three different perspectives: urban nodes, urban connections and urban clusters. The research adopts nighttime light imagery of cities in Hubei Province, the viewpoint of ′point-axis-area′ in the ′point-axis system′ theory, and employs light index model, gravity model and social network analysis. The findings are as follows: 1) In terms of urban nodes, the urbanization process of Hubei has been carried out mainly on the basis of external expansion rather than internal increasing. The polarization trend of urban connection network is strengthening. 2) As for urban connections, the estimation of urban connections using light index model is capable of containing various actual flow, and the connections are getting increasingly closer. 3) In regard to urban groups, seven urban groups of varying sizes have formed. On that basis, three stable and relatively independent urban groups as the centers, namely Wuchang, Yichang and Xiangyang emerge as well. But the structures of ′Wuhan Metropolitan Area′, ′Yichang-Jingzhou-Jingmen City Group′ and ′Xiangyang-Shiyen-Suizhou City Group′, which are defined by local development strategy in Hubei Province, are different from the above three urban groups.

北洛河流域气象干旱百年演化特征研究

[目的]揭示黄土高原典型区域百年尺度干旱演化特征,与地貌类型耦合阐明气象干旱的时空变化规律,进而为北洛河流域综合治理提供科技支撑。[方法]基于1915—2020年北洛河流域1 km分辨率的平均气温及降水数据,计算了年际标准化降水蒸散指数(SPEI),并结合Theil-Sen Median趋势分析、Mann-Kendall检验、小波分析、反距离权重插值(IDW)等方法,分析了流域内100余年不同地貌类型区的气象干旱时空演变特征。[结果](1)北洛河流域降水量及平均气温的空间分布差异较大,总体呈现东南向西北递减的特点;降水量多呈条带状分布,平均气温沿河道自上而下梯度增加,上游区(丘陵沟壑区)降水量相对较少,下游区(阶地平原区)平均气温相对偏高;(2) 1915—2020年北洛河流域SPEI-12震荡明显,干旱事件交替出现且弱减,下降速率为-0.04/10 a, 1942年,1990年和2010年为旱势转折年,并以1990年最为明显;周期变化大致可从1960年分为两个时期,之前以10 a, 17 a为主,其后为3 a, 7 a, 30 a左右,10 a和30 a周期在不同时期干旱变化中起主导作用;(3) SPEI-12的不显著下降趋势具有全域性且由东北向西南有增大趋势,表明北洛河流域总体呈弱旱化发展;(4)不同年代干旱事件发生频率差异较大,1990s重旱和特旱发生频率最高;2000s不同类型干旱事件发生的总频率最大,其中上游区(丘陵沟壑区)和下游区(阶地平原区)可达70%,而中游区(土石山林区和高原沟壑区)约为60%;(5)不同类型干旱空间分布存在异质性,轻旱发生频率有自南向北逐渐降低的趋势,中旱发生频率与之相反。总体来看,北洛河流域上游区(丘陵沟壑区)易发生中旱,下游区(阶地平原区)更易发生轻旱,重旱高发区在流域内零散分布,特旱的发生概率仅为1.69%~2.10%。[结论]全球变暖引发的旱化趋势在黄土高原地区的影响客观存在,北洛河流域不同地貌类型区气象干旱发生的高频类型略有差别,未来应提升中下游地区的抗旱减灾能力。

Identifying spatiotemporal traffic patterns in large-scale urban road networks using a modified nonnegative matrix factorization algorithm

The identification and analysis of spatiotemporal traffic patterns in road networks constitute a crucial process for sophisticated traffic management and control.Traditional methods based on mathematical equations and statistical models can hardly be applicable to large-scale urban road networks,where traffic states exhibit high degrees of dynamics and complexity.Recently,advances in data collection and processing have provided new opportunities to effectively understand spatiotemporal traffic patterns in large-scale road networks using data-driven methods.However,limited efforts have been exerted to explore the essential structure of the networks when conducting a spatiotemporal analysis of traffic characteristics.To this end,this study proposes a modified nonnegative matrix factorization algorithm that processes high-dimensional traffic data and provides an improved representation of the global traffic state.After matrix factorization,cluster analysis is conducted based on the obtained low-dimensional representative matrices,which contain different traffic patterns and serve as the basis for exploring the temporal dynamics and spatial structure of network congestion.The applicability and effectiveness of the proposed approach are examined in a road network of Beijing,China.Results show that the methods exhibit considerable potential for identifying and interpreting the spatiotemporal traffic patterns over the entire network and provide a systematic and efficient approach for analyzing the network-level traffic state.

环境和气象因素对柑橘黄龙病重要传播媒介——柑橘木虱发生规律的影响

研究了柑橘木虱(Diaphorina citri)对环境和气象因素的敏感性,以及其与柑橘黄龙病(Huanglongbing,HLB)传播的关系。总结了柑橘木虱(Diaphorina citri)的基本情况,并探究了环境因素(如海拔、纬度、土壤、田间管理、寄主和生物因素)和气象因素(如温度、湿度、降雨、光照和气压)对其发生规律的影响。这些信息有助于预测柑橘木虱的发生情况和制定有效的防治策略,从而减少柑橘黄龙病的传播风险。

Pattern control for large-scale spacecraft swarms in elliptic orbits via density fields

Space swarms,enabled by the miniaturization of spacecraft,have the potential capability to lower costs,increase efficiencies,and broaden the horizons of space missions.The formation control problem of large-scale spacecraft swarms flying around an elliptic orbit is considered.The objective is to drive the entire formation to produce a specified spatial pattern.The relative motion between agents becomes complicated as the number of agents increases.Hence,a density-based method is adopted,which concerns the density evolution of the entire swarm instead of the trajectories of individuals.The density-based method manipulates the density evolution with Partial Differential Equations(PDEs).This density-based control in this work has two aspects,global pattern control of the whole swarm and local collision-avoidance between nearby agents.The global behavior of the swarm is driven via designing velocity fields.For each spacecraft,the Q-guidance steering law is adopted to track the desired velocity with accelerations in a distributed manner.However,the final stable velocity field is required to be zero in the classical density-based approach,which appears as an obstacle from the viewpoint of astrodynamics since the periodic relative motion is always time-varying.To solve this issue,a novel transformation is constructed based on the periodic solutions of Tschauner-Hempel(TH)equations.The relative motion in Cartesian coordinates is then transformed into a new coordinate system,which permits zero-velocity in a stable configuration.The local behavior of the swarm,such as achieving collision avoidance,is achieved via a carefully-designed local density estimation algorithm.Numerical simulations are provided to demonstrate the performance of this approach.

Exploratory space data analysis of spatial patterns of large-scale retail commercial facilities:The case of Gulou District,Nanjing,China

This study uses methods,such as a nearest proximity index,nuclear density,spatial interpolation,buffering zone,and overlay analysis,based on an exploratory spatial data analysis tool.It focuses on a large commercial facility in which a mathematical analysis is conducted on its spatial patterns.In the study,45 large-scale retail commercial facilities(LSRCFs)in the Gulou District,Nanjing,China,were chosen,and the spatial concentration,density,and structure of the LSRCFs in this area were analyzed.Three additional factors,namely,population,transportation,and consumption,were examined to determine their impact on the spatial patterns of the LSRCFs.Finally,this study recommends a spatial layout for the future of the Gulou District according to the analysis results.

Non-orthogonal pilot pattern for sparse channel estimation in large-scale MIMO-OFDM system

From the perspective of compressed sensing（CS） theory, the channel estimation problem in large-scale multiple input multiple output（MIMO）-orthogonal frequency division multiplexing（OFDM） system is investigated. According to the theory, the smaller mutual coherence the reconstruction matrix has, the higher success probability the estimation can obtain. Aiming to design a pilot that can make the system reconstruction matrix having the smallest mutual coherence, this paper proposes a low complexity joint algorithm and obtains a kind of non-orthogonal pilot pattern. Simulation results show that compared with the conventional orthogonal pilot pattern, applying the proposed pattern in the CS channel estimation can obtain the better normalized mean square error performance. Moreover, the bit error rate performance of the large-scale MIMO-OFDM system is also improved.

基于气象再分析数据的泸州市降水演变规律研究

本文根据气象再分析中国逐日降水数据集,整合计算得到四川省泸州市1961—2022年的逐日降水序列,借助Mann-Kendall检验、Sen′s斜率估计法、创新性趋势分析法、滑动T检验和Morlet小波分析等方法对泸州市降水年际变化规律和年内分配规律进行了分析。分析结果表明:泸州市年降水量序列在2011年发生了跳跃变异。变异后年尺度上的极端降水天数和极端降水量虽呈现显著的下降趋势,但整体上平均态明显高于2011年之前;年降水天数序列则无明显增减趋势。1961—2022年的泸州市年降水量序列具有越来越明显的周期性。泸州市降水季节差异较大,降水年内分配特征变化总体上为无趋势或不显著的下降趋势。降水集中度(PCD)的不显著下降趋势集中于低值区和高值区;降水不均匀系数(Cv)、完全调节系数(Cr)在低、中、高值区的增减趋势较为一致,不显著的下降趋势主要位于中低值区。

潮州市城区PM_(2.5)-O_(3)复合污染特征及其发生的天气型分析

利用广东省潮州市区2014—2020年空气质量逐小时浓度数据,分析了PM_(2.5)、O_(3)浓度及复合污染的年、月、日变化特征,利用再分析资料对天气形势进行分型,结合相应时段潮州国家气象观测站资料,分析PM_(2.5)-O_(3)与天气型及气象因子的关系。结果表明:2014—2020年潮州市区年平均ρ(PM_(2.5))、ρ(O_(3)-8h)及复合污染出现日数均呈波动下降趋势,月平均ρ(PM_(2.5))最高出现在3月,月平均ρ(O_(3)-8h)最高出现在10月,两种污染物最低均出现在6月。复合污染出现较多的是10月—次年4月。PM_(2.5)、O_(3)污染具有一定相互作用,当其中一种污染物日均浓度较高时另一种污染物的浓度相应较高,同时污染物浓度的日较差也会相应增大;污染物峰谷值出现时间表现为空气污染较严重时,O_(3)峰值出现时间在15时,PM_(2.5)峰值出现在19—20时。造成潮州复合污染的天气型主要为变性高压脊(DR)、反气旋(AC)、副高+变性高压脊(SD)、均压场(UP)天气型,主要出现在秋、冬、春季,少数出现在初夏。4种天气型出现的季节不同,但总体来说晴朗干燥是出现复合污染的主要气象因素。

基于OBE的气象类创新创业课程教学模式研究

气象类创新创业课程教学常常以通识课方式开设,致使气象人才难以获得针对性和个性化指导。OBE理念,在学习结果导向、以学生为中心、真实情境学习、技能提升指引和评价形式多样方面具有显著优势,从解决课程教学设计固化、教师互动能力缺乏和学生需求多样等问题入手,构建了气象类创新创业课程教学模式。研究表明,在数字技术环境下,基于OBE理念的课程混合式教学模式包括设计学习产出、实现学习目标和评价学习效果三个阶段,其中设计学习产出重在目标设定,实现学习目标重在教师与学生互动,评价学习效果重在过程性与结果性考核结合。这丰富了已有创新创业课程教学模式,探索了气象类人才培养模式,为气象类专业人才提高创新创业成功率提供参考。

南京城区美国白蛾发生规律探析

2019—2023年对美国白蛾在南京市主城4区(鼓楼区、建邺区、秦淮区、玄武区)的发生规律进行了调查和分析,根据这5 a内美国白蛾成虫种群动态变化,幼虫危害情况及每年越冬蛹基数的调查,总结得出南京市主城区美国白蛾生活史。根据气象因子的数据汇总,并选取几种气象因子与每代成虫发生量进行相关性分析得出:与越冬代成虫羽化量最显著相关的气象因子为旬平均相对湿度,相关性R^(2)=0.9125;与第1代成虫羽化量最显著相关的气象因子为旬平均相对湿度,相关性R^(2)=0.6124;与第2代成虫羽化量最显著相关的气象因子为旬总降雨量,R^(2)=0.9998。利用回归法建立了南京市主城区美国白蛾发生期预测模型,以期为长江中下游其他城市地区预测美国白蛾发生趋势和开展防治工作提供一定参考。

广西南丹县2001-2020年森林火灾的时空特征及其与地形和气象因子的相关性

为深入了解森林火灾发生的时空分布格局及影响因素,优化防火和灭火资源的合理配置,采用时间序列法对广西南丹县2001-2020年森林火灾的变化特征进行分析,比较不同森林类型的受损特征与火因构成,并分析森林火灾与地形和气象因子之间的相关性。结果表明:(1)南丹县较大森林火灾发生在2001-2008年,而一般森林火灾发生在2009-2020年。全县80%的森林火灾发生在每年的1-4月,且主要集中于县域范围从西北到东南的中间地带,为交通路网密集或人口聚集区。(2)对于不同森林类型,灌木林和荒山更易发生森林火灾,而马尾松林、杉木林和桉树林虽然发生火灾次数较少,但受损面积远高于灌木林和荒山。人为因素如生产性用火和非生产性用火是导致森林火灾的主要原因。(3)森林火灾受到地形特征以及海拔因素的综合影响,即使在火灾频率较低的地方,火灾发生后如未能得到有效控制,其扩散蔓延的范围也较大。(4)虽然南丹县森林火灾次数和火场面积与主要气象指标的相关性较弱,但因子分析结果表明,各年份起主导作用的气象因子不同是森林火灾产生年际差异的主要原因。因此,未来南丹县应当依据当地森林火灾时空特征和准确掌握气候变化,加大林火监测和管理力度以预防森林火灾的发生,并制定科学的林火管理和扑救策略以更好地应对森林火灾。

Preliminary studies on the large-scale geomorphic patterns of the complex longitudinal sand ridge zone in the Taklimakan Desert

Through analysis of satellite images from Google Earth, this article expounds the characteristics of large-scale geomorphic patterns of the complex longitudinal sand ridge zone in the Taklimakan Desert, and reduces the large-scale geomorphic patterns to six types: parallel pattern, "日"character-shaped and "乡" character-shaped pattern, comb-shaped pattern, fork-shaped pattern, toe-shaped pattern and miscellaneous pattern. And according to the large-scale geomorphic pattern type (or composition of pattern types) as well as some other factors, the article divides the complex longitudinal sand ridge zone into 55 subzones. Lastly, aiming at the genetic problems of the large-scale geomorphic patterns, the article suggests three connective types of the sand ridges in the complex longitudinal sand ridge zone, i.e., connecting or intersecting after natural elongation, connecting in a narrow place and connecting with the aid of intermediary.