Dynamicity of Land Use/Land Cover(LULC):An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation(DMC)in India

The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city and fostering the growth of physical infrastructure.Using multi-temporal satellite images,the dynamics of Land Use/Land Cover(LULC)changes,the impact of urban growth on LULC changes,and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India.The study used different case studies to highlight the study area’s heterogeneity,as the phenomenon of change is not consistent.Landsat TM and OLI-TIRS satellite images in 1991,2001,2011,and 2021 were used to analyse the changes in LULC types.We used the relative deviation(RD),annual change intensity(ACI),uniform intensity(UI)to show the dynamicity of LULC types(agriculture land;built-up land;fallow land;vegetated land;mining area;and water bodies)during 1991-2021.This study also applied the Decision-Making Trial and Evaluation Laboratory(DEMATEL)to measure environmental sensitivity zones and find out the causes of LULC changes.According to LULC statistics,agriculture land,built-up land,and mining area increased by 51.7,95.46,and 24.79 km^(2),respectively,from 1991 to 2021.The results also suggested that built-up land and mining area had the greatest land surface temperature(LST),whereas water bodies and vegetated land showed the lowest LST.Moreover,this study looked at the relationships among LST,spectral indices(Normalized Differenced Built-up Index(NDBI),Normalized Difference Vegetation Index(NDVI),and Normalized Difference Water Index(NDWI)),and environmental sensitivity.The results showed that all of the spectral indices have the strongest association with LST,indicating that built-up land had a far stronger influence on the LST.The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km^(2)/a,respectively,during 1991-2021.In summary,this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land,thus making effective peri-urban planning decisions.

Necessary and Sufficient Conditions for Feasible Neighbourhood Solutions in the Local Search of the Job-Shop Scheduling Problem

The meta-heuristic algorithm with local search is an excellent choice for the job-shop scheduling problem(JSP).However,due to the unique nature of the JSP,local search may generate infeasible neighbourhood solutions.In the existing literature,although some domain knowledge of the JSP can be used to avoid infeasible solutions,the constraint conditions in this domain knowledge are sufficient but not necessary.It may lose many feasible solutions and make the local search inadequate.By analysing the causes of infeasible neighbourhood solutions,this paper further explores the domain knowledge contained in the JSP and proposes the sufficient and necessary constraint conditions to find all feasible neighbourhood solutions,allowing the local search to be carried out thoroughly.With the proposed conditions,a new neighbourhood structure is designed in this paper.Then,a fast calculation method for all feasible neighbourhood solutions is provided,significantly reducing the calculation time compared with ordinary methods.A set of standard benchmark instances is used to evaluate the performance of the proposed neighbourhood structure and calculation method.The experimental results show that the calculation method is effective,and the new neighbourhood structure has more reliability and superiority than the other famous and influential neighbourhood structures,where 90%of the results are the best compared with three other well-known neighbourhood structures.Finally,the result from a tabu search algorithm with the new neighbourhood structure is compared with the current best results,demonstrating the superiority of the proposed neighbourhood structure.

非冷链商品配送路径优化研究--以京东配送为例

如何有效降低商品配送成本是物流企业的关注重点,学界已就带时间窗的商品配送路径优化算法展开了相关研究,但相关算法还存在着过早陷入局部最优或无法收敛的问题。由此提出一种改进的变邻域遗传搜索算法(VNS-GA),以非冷链商品配送为研究对象,构造起求解物流配送车辆路径规划的数学模型。首先,以配送成本和缺货惩罚成本的最小化作为实现目标,构建了包括车辆使用成本、配送运输成本和时间窗口惩罚成本的配送路径优化模型;其次,运用变邻域遗传优化算法来实现多目标物流配送路径的优化;最后,以京东某北京配送中心的物流配送为例,运用MATLAB软件对VNS-GA算法模型的科学性及有效性进行仿真验证。经实证,VNS-GA算法与传统算法相比具有更好的全局和局部搜索能力。研究期望为配送车辆调度与配送路径规划提供更优的路径选择模型,从而降低物流配送成本和减少便利店因缺货造成的损失。

针对境内居留群体及其聚居区引入服务型爱国社团的思考及建议——以澳门街坊总会广东办事处服务点为例

伴随着改革开放力度的加大,我国入境居留且拥有境外身份的社会群体日益增大,其居留期内的社会服务需求凸显。针对居留群体引入并设立服务型爱国社团,有助于维护国家的安全稳定与繁荣发展,有助于提高居留群体的生活质量,有助于促进境内外交流与粤港澳融合发展,但同时也面临管理、资源不足等问题。澳门街坊总会在内地设立广东办事处及中山、横琴等服务点,以社会效益最大化为目标,建构社会服务机制,以需求为导向提供社会服务。引入境外爱国服务型社团,应依法筛选友好型、信誉良好、能提供优质服务的爱国社团,加强服务管理,促进其规范运作,发挥应有作用。

基于近邻元分析的风电机组状态监测特征选择方法

针对现有特征选择方法难以从大量的SCADA参量中挑选出重要变量的问题,基于近邻元分析算法提出一种专门适用于风电机组状态监测的特征变量选择方法。所提方法根据每个待选变量对回归精度的贡献率为各变量赋予相应的重要度权值,从而挑选出最重要的特征变量。通过分析SCADA数据中冗余变量的特点,针对性地提出了基于相关系数矩阵的去除冗余方法。采用Pearson相关系数、互信息和随机森林三种方法作为对比,以门控循环神经网络作为模型预测齿轮箱油池温度,用预测精度指标和残差控制图对各特征选择方法的选择结果进行评价和对比,结果表明所提方法的特征选择结果更加直观、冗余变量更少、预测精度更高。

伊宁市历史文化街区句法分析——以六星街为例

文化历史街区是城市文化遗产真实性和完整性的代表之一,蕴藏城市独有历史文化内涵。文章以伊宁市历史文化街区—六星街为研究对象,对街区分层级构建评价模型并进行空间句法分析,结合实地考察对评价模型进行验证。结果表明:句法能为六星街历史文化街区研究提供量化分析和参数表达,整合度和选择度的高值主要在工人街、赛依拉木街和黎光街三条主街道,支巷空间不易感知到街区整体空间;可理解度在主街与支巷的节点处呈现高值;庭院全局空间具有较强的开放性,可达性和可穿越性均较高且东西厢房具有一定私密性。文章揭示六星街历史文化街区空间形态特征及成因,并对街区在街区层、巷道层和庭院层存在的问题提出建议,为今后街区保护和更新提供理论参考。

基于邻居采样和图注意力机制的产业链风险评估模型

风险评估是提高产业链韧性的重要途径,也是降低产业链不稳定性的有效手段。然而,现有风险评估的研究基于供应链结构,忽略了其他因素,无法准确地刻画产业链上下游各节点的关联关系,导致评估效果存在偏差。针对上述问题,考虑到产业链内部各节点相互关联、风险状况多样、存在风险传递的特性,提出了基于邻居采样和图注意力机制的产业链风险评估模型GANS。首先,构建了产业链的异质图,利用“产品-公司”“产品-产品”刻画了产业链节点之间的关联关系,并从产业链中提取财务数据等作为节点的数据特征;其次,提出了基于元路径和公司投融资关联规则的公司关系图生成模块,实现对产业链中公司节点关系的高效转化和结构特征的高效学习;接着,针对生成的多种公司关系图,设计了结合邻居采样和图注意力机制的产业链风险评估模块,对节点邻域特征进行随机采样和聚合,同时结合注意力机制对基于多种公司图的节点特征进行自适应聚合,并通过分类器实现节点级风险评估;最后,依据节点风险等级与节点的结构特征对产业链进行风险评估。实验表明,在真实产业链数据集上,GANS在准确性、F1分数等方面均优于现有的模型,证明了GANS实现产业链风险评估的准确性和有效性。

老旧小区改造项目优先级评价研究

为解决城镇老旧小区改造因资金短缺和改造效率低下等原因导致的改造工作停滞等问题,从多要素、多群体、多目标角度入手,基于组合赋权和TOPSIS法对老旧小区改造项目择优选择。从项目实施条件、实施风险、产生影响和项目协同性4个维度建立改造项目优先级评价指标体系;建立基于TOPSIS法的改造项目优先级评价模型,选取北京市某区10个改造项目进行实证研究;为实现资源高效配置,提出建立老旧小区改造项目储备库制度、鼓励多元主体参与、推进连片改造等优化建议。

基于动态扩展邻域蚁群算法的移动机器人路径规划

针对蚁群算法易陷入局部最优、路径转折点多、收敛速度慢的问题,提出一种基于动态扩展邻域蚁群算法(Dynamic extended neighbourhoods ant colony optimization,DENACO)。在蚂蚁搜索方式上采用动态扩展邻域方法,并定义新的信息素计算方式和增量规则,在取得更优收敛路径长度的同时,减少路径转折点数量及路径节点数量;引入自适应调整因子改进启发函数,提高算法的全局搜索能力,并设定迭代阈值,提升算法的收敛速度;提出一种路径节点双优化策略,对规划好的路径进一步优化,提高路径综合质量。不同复杂度及不同规模栅格地图中的仿真实验表明,DENACO算法所规划的路径更优,路径转折点数量减少,收敛速度加快,路径节点数量明显减少,表明算法具有更高的可行性和适用性。

基于改进蜜蜂觅食算法的多阈值图像分割

为解决传统多阈值图像分割方法搜索最优阈值效率低的问题,利用蜜蜂觅食算法中蜂群对蜜源的智能搜索机制,提高多阈值图像分割的最优阈值搜索效率。针对蜜蜂觅食算法邻域收缩过快易陷入局部最优问题,引入自适应邻域收缩策略,根据搜索陷入停滞的状态,自适应调整邻域收缩率,在保证算法搜索效率的同时,进一步提高算法寻优精度。仿真实验结果证明该方法提升了蜜蜂觅食算法的优化性能和算法鲁棒性,基于最大类间方差的图像多阈值分割实验验证了该方法的有效性。

考虑等待成本的卡车与多无人机联合配送农村物流路径优化

车辆和无人机联合配送模式是降低末端配送成本、提高效率的全新尝试。本文考虑卡车和无人机相互等待成本,以最小总成本为目标建立了单卡车和多无人机联合配送路径优化模型。设计了自适应大邻域搜索算法,采用三种破坏算子和修复算子,对破坏、修复后的临时解使用模拟退火接受准则。对包含10-100个节点的呈均匀分布和簇状分布的2类算例进行求解,与CPLEX求解结果对比表明提出的算法具有较快的速度、较好的精度和稳定性;分析卡车携带不同数量无人机的联合配送方案,结果显示,相较于纯卡车配送,携带1-4台无人机的联合配送可降低农村物流配送总成本17.88%~28.94%;对无人机续航里程的敏感性分析,表明随无人机续航里程的增加配送成本呈先快速降低后缓慢降低或趋于稳定。

基于新邻里视角的食物共享平台社交服务系统设计研究

在城市化迅速推进的背景下,传统的邻里社交逐渐式微,导致现代社区居民凝聚力和归属感下降。为了应对这一现象,文章基于新邻里视角设计了食物共享平台社交服务系统的设计,以食物作为关键研究因素,探索其在改善社区现状方面的影响。通过系统研究和实践,设计了一套可行的社交服务系统,旨在促进社区内部的互动与合作。同时,强调了服务系统在加强社区凝聚力、推动社区共生方面的作用,并为未来社区发展提供了新的思路。

Disparities in tree mortality among plant functional types(PFTs)in a temperate forest:Insights into size-dependent and PFT-specific patterns

Tree mortality significantly influences forest structure and function,yet our understanding of its dynamic patterns among a range of tree sizes and among different plant functional types(PFTs)remains incomplete.This study analysed size-dependent tree mortality in a temperate forest,encompassing 46 tree species and 32,565 individuals across different PFTs(i.e.,evergreen conifer vs.deciduous broadleaf species,shade-tolerant vs.shade-intolerant species).By employing all-subset regression procedures and logistic generalized linear mixed-effects models,we identified distinct mortality patterns influenced by biotic and abiotic factors.Our results showed a stable mortality patte rn in eve rgreen conifer species,contrasted by a declining pattern in deciduous broadleaf and shadetolerant,as well as shade-intolerant species,across size classes.The contribution to tree mortality of evergreen conifer species shifted from abiotic to biotic factors with increasing size,while the mortality of deciduous broadleaf species was mainly influenced by biotic factors,such as initial diameter at breast height(DBH)and conspecific negative density.For shade-tolerant species,the mortality of small individuals was mainly determined by initial DBH and conspecific negative density dependence,whereas the mortality of large individuals was subjected to the combined effect of biotic(competition from neighbours)and abiotic factors(i.e.,convexity and pH).As for shade-intolerant species,competition from neighbours was found to be the main driver of tree mortality throughout their growth stages.Thus,these insights enhance our understanding of forest dynamics by revealing the size-dependent and PFT-specific tree mortality patterns,which may inform strategies for maintaining forest diversity and resilience in temperate forest ecosystems.

基于遗传-变邻域搜索算法的堆垛机作业调度优化

基于缩短自动化立体仓库中堆垛机完成货物出入任务时间的目的,建立了堆垛机作业调度的作业时间模型,通过修补机制、校正机制和遗传-变邻域搜索算法的优化方法,使得在优化的过程中,确保出入库任务序列的长度相等,并能够复用同一批作业任务中因出库作业产生的空货位。12组作业任务的仿真实验结果表明,相较于变邻域搜索算法,遗传-变邻域搜索算法的收敛速度更快,其中3组作业任务解的质量更高,总耗时和相对耗时的优化率分别为11.57%~21.56%和35.85%~68.89%,且复用空货位可以缩短堆垛机的作业时间。

Competitive effect, but not competitive response, varies along a climatic gradient depending on tree species identity

Background: Understanding the role of species identity in interactions among individuals is crucial for assessing the productivity and stability of mixed forests over time. However, there is limited knowledge concerning the variation in competitive effect and response of different species along climatic gradients. In this study, we investigated the importance of climate, tree size, and competition on the growth of three tree species: spruce(Picea abies), fir(Abies alba), and beech(Fagus sylvatica), and examined their competitive response and effect along a climatic gradient.Methods: We selected 39 plots distributed across the European mountains with records of the position and growth of 5,759 individuals. For each target species, models relating tree growth to tree size, climate and competition were proposed. Competition was modelled using a neighbourhood competition index that considered the effects of inter-and intraspecific competition on target trees. Competitive responses and effects were related to climate.Likelihood methods and information theory were used to select the best model.Results: Our findings revealed that competition had a greater impact on target species growth than tree size or climate. Climate did influence the competitive effects of neighbouring species, but it did not affect the target species? response to competition. The strength of competitive effects varied along the gradient, contingent on the identity of the interacting species. When the target species exhibited an intermediate competitive effect relative to neighbouring species, both higher inter-than intraspecific competitive effects and competition reduction occurred along the gradient. Notably, species competitive effects were most pronounced when the target species' growth was at its peak and weakest when growing conditions were far from their maximum.Conclusions: Climate modulates the effects of competition from neighbouring trees on the target tree and not the susceptibility of the target tree to competition. The modelling approach should be useful in future research to expand our knowledge of how competition modulates forest communities across environmental gradients.

Neighbourhood Unions and Vertex pancyclicity *

Let G be a 2 connected simple graph of order n ( n ≥5) and minimum degree δ . In this paper, we show that if for any two nonadjacent vertices u , v of G there holds | N(u)∪N(v)|≥n-δ , then G is {3,4} - vertex pancyclic unless G≌K n2,n2 .

基于多元主体需求的老旧生活性街区改造规划路径——以沈阳市大东区万寿小区为例

城镇老旧小区改造是城市更新的重要着力点,改造过程中出现的多方主体利益和需求关系,是打造共建共治共享社会的关键因素。阐析了多主体的利益诉求与博弈焦点,并构建了基于多元主体需求的改造路径。以沈阳市大东区万寿小区为例,对居民主体、政府主体、管理主体需求进行了调查分析,并结合改造路径的区域评估、整体统筹、策划方案和长效管理四步骤,提出了老旧生活性街区改造规划措施,以期为老旧小区提升改造提供新思路和参考。

基于改进领结模型的老旧小区改造项目风险管理探究

我国城市建设正在从“增量扩张”向“存量更新”转型,其中老旧小区改造已成为“十四五”规划中有关城市更新中的一项重要惠民举措,但老旧小区改造过程中存在诸多风险,一定程度上阻碍了城市更新的进程,故有必要系统地展开老旧小区改造项目风险识别、评价及管理相关研究。本文提出一种老旧小区改造风险管理方案,首先通过文献梳理及专家咨询较全面地归纳出当前老旧小区改造中潜在的风险因素;然后,构建老旧小区改造风险识别管理方法,即在老旧小区改造项目风险识别的基础上,采用Borda序值法对项目中风险因素的重要程度进行定量化排序,运用改进领结模型对涵盖重要风险因素的施工场景展开研究,分析施工过程中可能发生的事故,并设置预防和缓解屏障以降低事故发生概率和减轻后果影响。最后,以S市某老旧小区改造实际项目风险评价管理为研究案例,测试了本文构建的老旧小区改造风险识别与管理方法的有效性、可行性。

绿色建材在老旧小区住宅建筑改造中的应用

城市化进程的加速和老旧小区住宅建筑的增加,提升此类建筑的可持续性成为城市更新的迫切需求。研究从绿色建材的定义和特点出发,分析老旧小区住宅建筑改造的需求和挑战,研究不同类型绿色建材的特性及可持续性评估。得出绿色建材在老旧小区建筑改造中具有广泛的应用前景,是可持续发展的营造方式。研究旨在为城市改造和建筑领域的决策者、研究者提供有关绿色建材的实用指南,以推动城市可持续发展的目标。

有取货点选择的电动车集送货团队定向问题研究

随着国家越来越重视绿色物流,电动车在物流配送中的应用日益广泛,同时在实际配送过程中存在同一个配送需求有多个取货点可供选择以及由于配送资源有限不足以满足所有配送需求的情况。针对此类问题,本文研究了有取货点选择的电动车集送货团队定向问题,首次建立了针对该问题的混合整数规划模型。在该模型中各配送需求的取货点为决策变量,在不超过规定车辆数量和时间资源限制下以最大化总收益为目标。结合模拟退火算法的思想设计改进的自适应大邻域搜索算法对该问题进行求解,在该算法中首次设计贪婪随机修复算子和最小支撑树破坏算子,并结合文献中已有的算子以提高算法性能。通过不同规模算例实验证明了所提出模型和算法的有效性,进一步对比分析了有取货点选择对总收益的影响,实验结果显示在有取货点选择的情况下,三种大规模算例的总收益均有了显著的提高,最后说明了所提出新算子的有效性。