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Application of the probability-based covering algorithm model in text classification 认领 引用
1
作者 ZHOU Ying 《Chinese Journal of Library and Information Science》 2009年第4期1-17,共17页
The probability-based covering algorithm(PBCA) is a new algorithm based on probability distribution. It decides, by voting, the class of the tested samples on the border of the coverage area, based on the probability ... The probability-based covering algorithm(PBCA) is a new algorithm based on probability distribution. It decides, by voting, the class of the tested samples on the border of the coverage area, based on the probability of training samples. When using the original covering algorithm(CA), many tested samples that are located on the border of the coverage cannot be classified by the spherical neighborhood gained. The network structure of PBCA is a mixed structure composed of both a feed-forward network and a feedback network. By using this method of adding some heterogeneous samples and enlarging the coverage radius,it is possible to decrease the number of rejected samples and improve the rate of recognition accuracy. Relevant computer experiments indicate that the algorithm improves the study precision and achieves reasonably good results in text classification. 展开更多
关键词 Probability-based covering algorithm Structural training algorithm Probability Text classification
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Hybrid genetic simulated annealing algorithm for agile Earth observation satellite scheduling considering cloud cover distribution 认领 引用
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作者 SUN Haiquan WANG Zhilong +1 位作者 HU Xiaoxuan XIA Wei 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第6期1595-1612,共18页
Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at... Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at any moment within the VTW.However,different observation times demonstrate different cloud cover distributions,which exhibit different effects on the AEOS observation.Previous studies ignored pitch angles,discretized VTWs,or fixed cloud cover for every VTW,which led to the loss of intermediate observation states,thus these studies are not suitable for AEOS scheduling considering cloud cover distribution.In this study,a relationship formula between the cloud cover and observation time is proposed to calculate the cloud cover for every observation time,and a relationship formula between the observation time and pitch angle is designed to calculate the pitch angle for every observation time in the VTW.A refined model including the pitch angle,roll angle,and cloud cover distribution is established,which can make the scheme closer to the actual application of AEOSs.A hybrid genetic simulated annealing(HGSA)algorithm for AEOS scheduling is proposed,which integrates the advantages of genetic and simulated annealing algorithms and can effectively avoid falling into a local optimal solution.The experiments are conducted to compare the proposed algorithm with the traditional algorithms,the results verify that the proposed model and algorithm are efficient and effective for AEOS scheduling considering cloud cover distribution. 展开更多
关键词 agile Earth observation satellite cloud cover distribution hybrid genetic simulated annealing algorithm
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Binary Fruit Fly Swarm Algorithms for the Set Covering Problem 认领 引用 被引量：2
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作者 Broderick Crawford Ricardo Soto +7 位作者 Hanns de la Fuente Mella Claudio Elortegui Wenceslao Palma Claudio Torres-Rojas Claudia Vasconcellos-Gaete Marcelo Becerra Javier Pena Sanjay Misra 《Computers, Materials & Continua》 SCIE EI 2022年第6期4295-4318,共24页
Currently,the industry is experiencing an exponential increase in dealing with binary-based combinatorial problems.In this sense,metaheuristics have been a common trend in the field in order to design approaches to so... Currently,the industry is experiencing an exponential increase in dealing with binary-based combinatorial problems.In this sense,metaheuristics have been a common trend in the field in order to design approaches to solve them successfully.Thus,a well-known strategy consists in the use of algorithms based on discrete swarms transformed to perform in binary environments.Following the No Free Lunch theorem,we are interested in testing the performance of the Fruit Fly Algorithm,this is a bio-inspired metaheuristic for deducing global optimization in continuous spaces,based on the foraging behavior of the fruit fly,which usually has much better sensory perception of smell and vision than any other species.On the other hand,the Set Coverage Problem is a well-known NP-hard problem with many practical applications,including production line balancing,utility installation,and crew scheduling in railroad and mass transit companies.In this paper,we propose different binarization methods for the Fruit Fly Algorithm,using Sshaped and V-shaped transfer functions and various discretization methods to make the algorithm work in a binary search space.We are motivated with this approach,because in this way we can deliver to future researchers interested in this area,a way to be able to work with continuous metaheuristics in binary domains.This new approach was tested on benchmark instances of the Set Coverage Problem and the computational results show that the proposed algorithm is robust enough to produce good results with low computational cost. 展开更多
关键词 Set covering problem fruit fly swarm algorithm metaheuristics binarization methods combinatorial optimization problem
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A Comparison among Different Machine Learning Algorithms in Land Cover Classification Based on the Google Earth Engine Platform: The Case Study of Hung Yen Province, Vietnam 认领 引用
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作者 Le Thi Lan Tran Quoc Vinh Phạm Quy Giang 《Journal of Environmental & Earth Sciences》 CAS 2025年第1期132-139,共8页
Based on the Google Earth Engine cloud computing data platform,this study employed three algorithms including Support Vector Machine,Random Forest,and Classification and Regression Tree to classify the current status ... Based on the Google Earth Engine cloud computing data platform,this study employed three algorithms including Support Vector Machine,Random Forest,and Classification and Regression Tree to classify the current status of land covers in Hung Yen province of Vietnam using Landsat 8 OLI satellite images,a free data source with reasonable spatial and temporal resolution.The results of the study show that all three algorithms presented good classification for five basic types of land cover including Rice land,Water bodies,Perennial vegetation,Annual vegetation,Built-up areas as their overall accuracy and Kappa coefficient were greater than 80%and 0.8,respectively.Among the three algorithms,SVM achieved the highest accuracy as its overall accuracy was 86%and the Kappa coefficient was 0.88.Land cover classification based on the SVM algorithm shows that Built-up areas cover the largest area with nearly 31,495 ha,accounting for more than 33.8%of the total natural area,followed by Rice land and Perennial vegetation which cover an area of over 30,767 ha(33%)and 15,637 ha(16.8%),respectively.Water bodies and Annual vegetation cover the smallest areas with 8,820(9.5%)ha and 6,302 ha(6.8%),respectively.The results of this study can be used for land use management and planning as well as other natural resource and environmental management purposes in the province. 展开更多
关键词 Google Earth Engine Land Cover Landsat Machine Learning Algorithm
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EXACT ALGORITHM FOR BIN COVERING 认领 引用
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作者 CHEN Feng YAO En-yu 《Journal of Zhejiang University Science》 2001年第3期2-7,共6页
This paper presents a new arc flow model for the one-dimensional bin covering problem and an algorithm to solve the problem exactly through a branch-and-bound procedure and the technique of column generation. The subp... This paper presents a new arc flow model for the one-dimensional bin covering problem and an algorithm to solve the problem exactly through a branch-and-bound procedure and the technique of column generation. The subproblems occuring in the procedure of branch-and-bound have the same structure and therefore can be solved by the same algorithm. In order to solve effectively the subproblems which are generally large scale, a column generation algorithm is employed. Many rules found in this paper can improve the performance of the methods. 展开更多
关键词 bin covering column generation branch-and-bound algorithm
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Parallel machine covering with limited number of preemptions 认领 引用 被引量：1
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作者 JIANG Yi-wei HU Jue-liang +1 位作者 WENG Ze-wei ZHU Yu-qing 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2014年第1期18-28,共11页
In this paper, we investigate the/-preemptive scheduling on parallel machines to maximize the minimum machine completion time, i.e., machine covering problem with limited number of preemptions. It is aimed to obtain t... In this paper, we investigate the/-preemptive scheduling on parallel machines to maximize the minimum machine completion time, i.e., machine covering problem with limited number of preemptions. It is aimed to obtain the worst case ratio of the objective value of the optimal schedule with unlimited preemptions and that of the schedule allowed to be preempted at most i times. For the m identical machines case, we show the worst case ratio is 2m-i-1/m and we present a polynomial time algorithm which can guarantee the ratio for any 0 〈 i 〈2 m - 1. For the /-preemptive scheduling on two uniform machines case, we only need to consider the cases of i = 0 and i = 1. For both cases, we present two linear time algorithms and obtain the worst case ratios with respect to s, i.e., the ratio of the speeds of two machines. 展开更多
关键词 90B35 90C27 68Q25 i-preemptive scheduling machine covering approximation algorithm worst case ratio
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Estimating wheat fractional vegetation cover using a density peak k-means algorithm based on hyperspectral image data 认领 引用 被引量：7
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作者 LIU Da-zhong YANG Fei-fei LIU Sheng-ping 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2021年第11期2880-2891,共12页
Fractional vegetation cover(FVC)is an important parameter to measure crop growth.In studies of crop growth monitoring,it is very important to extract FVC quickly and accurately.As the most widely used FVC extraction m... Fractional vegetation cover(FVC)is an important parameter to measure crop growth.In studies of crop growth monitoring,it is very important to extract FVC quickly and accurately.As the most widely used FVC extraction method,the photographic method has the advantages of simple operation and high extraction accuracy.However,when soil moisture and acquisition times vary,the extraction results are less accurate.To accommodate various conditions of FVC extraction,this study proposes a new FVC extraction method that extracts FVC from a normalized difference vegetation index(NDVI)greyscale image of wheat by using a density peak k-means(DPK-means)algorithm.In this study,Yangfumai 4(YF4)planted in pots and Yangmai 16(Y16)planted in the field were used as the research materials.With a hyperspectral imaging camera mounted on a tripod,ground hyperspectral images of winter wheat under different soil conditions(dry and wet)were collected at 1 m above the potted wheat canopy.Unmanned aerial vehicle(UAV)hyperspectral images of winter wheat at various stages were collected at 50 m above the field wheat canopy by a UAV equipped with a hyperspectral camera.The pixel dichotomy method and DPK-means algorithm were used to classify vegetation pixels and non-vegetation pixels in NDVI greyscale images of wheat,and the extraction effects of the two methods were compared and analysed.The results showed that extraction by pixel dichotomy was influenced by the acquisition conditions and its error distribution was relatively scattered,while the extraction effect of the DPK-means algorithm was less affected by the acquisition conditions and its error distribution was concentrated.The absolute values of error were 0.042 and 0.044,the root mean square errors(RMSE)were 0.028 and 0.030,and the fitting accuracy R2 of the FVC was 0.87 and 0.93,under dry and wet soil conditions and under various time conditions,respectively.This study found that the DPK-means algorithm was capable of achieving more accurate results than the pixel dichotomy method in various soil and time conditions and was an accurate and robust method for FVC extraction. 展开更多
关键词 fractional vegetation cover k-means algorithm NDVI vegetation index wheat
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Metaheuristic post-optimization of the NIST repository of covering arrays 认领 引用
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作者 Jose Torres-Jimenez Arturo Rodriguez-Cristerna 《CAAI Transactions on Intelligence Technology》 EI 2017年第1期31-38,共8页
Construction of Covering Arrays （CA） with minimum possible number of rows is challenging. Often the available CA have redundant combinatorial interaction that could be removed to reduce the number of rows. This pape... Construction of Covering Arrays （CA） with minimum possible number of rows is challenging. Often the available CA have redundant combinatorial interaction that could be removed to reduce the number of rows. This paper addresses the problem of removing redundancy of CA using a metaheuristic post- optimization （MPO） approach. Our approach consists of three main components： a redundancy detector （RD）; a row reducer （RR）; and a missing-combinations reducer （MCR）. The MCR is a metaheuristic component implemented using a simulated annealing algorithm. MPO was instantiated with 21,964 CA taken from the National Institute of Standards and Technology （NIST） repository. It is a remarkable result that this instantiation of MPO has delivered 349 new upper bounds for these CA. 展开更多
关键词 Covering arrays NIST repository of covering arrays Metaheuristic post-processing algorithms
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New Hybrid Genetic Algorithm for Vertex Cover Problems 认领 引用
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作者 HuoHongwei XuJin 《Journal of Systems Engineering and Electronics》 EI 2003年第4期90-94,共5页
This paper presents a new hybrid genetic algorithm for the vertex cover problems in which scan-repair and local improvement techniques are used for local optimization. With the hybrid approach, genetic algorithms are ... This paper presents a new hybrid genetic algorithm for the vertex cover problems in which scan-repair and local improvement techniques are used for local optimization. With the hybrid approach, genetic algorithms are used to perform global exploration in a population, while neighborhood search methods are used to perform local exploitation around the chromosomes. The experimental results indicate that hybrid genetic algorithms can obtain solutions of excellent quality to the problem instances with different sizes. The pure genetic algorithms are outperformed by the neighborhood search heuristics procedures combined with genetic algorithms. 展开更多
关键词 vertex cover hybrid genetic algorithm scan-repair local improvement.
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A Heuristic Approach to Fast NOVCA (Near Optimal Vertex Cover Algorithm) 认领 引用
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作者 Sanj aya Gajurel Roger Bielefeld 《Computer Technology and Application》 2014年第2期83-90,共8页
This paper describes an extremely fast polynomial time algorithm, the NOVCA （Near Optimal Vertex Cover Algorithm） that produces an optimal or near optimal vertex cover for any known undirected graph G （V, E）. NOVC... This paper describes an extremely fast polynomial time algorithm, the NOVCA （Near Optimal Vertex Cover Algorithm） that produces an optimal or near optimal vertex cover for any known undirected graph G （V, E）. NOVCA is based on the idea of（l） including the vertex having maximum degree in the vertex cover and （2） rendering the degree of a vertex to zero by including all its adjacent vertices. The three versions of algorithm, NOVCA-I, NOVCA-II, and NOVCA-random, have been developed. The results identifying bounds on the size of the minimum vertex cover as well as polynomial complexity of algorithm are given with experimental verification. Future research efforts will be directed at tuning the algorithm and providing proof for better approximation ratio with NOVCA compared to any available vertex cover algorithms. 展开更多
关键词 Vertex cover problem combinatorial problem NP-complete problem approximation algorithm optimization algorithms.
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基于GWO-VMD和改进XGBoost的水轮机顶盖振动故障识别 认领 引用 被引量：1
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作者 张彬桥 黄海洋 江雨 《大电机技术》 2026年第1期72-81,共10页
水轮机顶盖振动是影响水轮机运行稳定性和安全性的重要因素,深入分析其诱因并采取有效措施,有助于提高设备可靠性和运行效率。为了应对水轮机复杂振动信号在噪声干扰下难以提取故障特征的问题,本文提出了一种改进的变分模态分解(VMD)与... 水轮机顶盖振动是影响水轮机运行稳定性和安全性的重要因素,深入分析其诱因并采取有效措施,有助于提高设备可靠性和运行效率。为了应对水轮机复杂振动信号在噪声干扰下难以提取故障特征的问题,本文提出了一种改进的变分模态分解(VMD)与多尺度样本熵相结合的特征提取方法,并利用改进极端梯度提升(XGBoost)机器学习算法进行故障识别。首先,提出将皮尔逊相关系数作为VMD的适应度函数来进行自适应优化分解参数,并通过皮尔逊相关系数来筛选本征模态函数。然后,采用多尺度样本熵对筛选后的本征模函数(IMF)进行特征量化。最后,提出一种基于牛顿-拉夫逊优化算法(NRBO)优化XGBoost模型超参数,将提取到的故障特征数据集分为训练集和测试集输入优化后的XGBoost模型进行训练和故障识别。经实测振动数据集和对比实验验证,该方法能有效地提取振动故障信号,并有更高的故障识别准确率。 展开更多
关键词 水电机组 顶盖振动信号 变分模态分解 灰狼优化算法 多尺度样本熵 牛顿-拉夫逊优化算法 XGBoost
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基于启发式可变力度覆盖表的列车自动驾驶测试用例生成方法 认领 引用
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作者 张雁鹏 王贺贺 +2 位作者 王菲 曹宇翔 窦道飞 《铁道学报》 EI CAS CSCD 北大核心 2026年第8期83-94,共12页
当采用组合测试方法对智能高速铁路列车自动驾驶(ATO)功能测试时,输入参数动态取值易导致重复或无效的测试用例生成,甚至引发组合爆炸。为了满足ATO功能测试的覆盖力度和效率要求,提出一种利用启发式可变力度覆盖表生成测试用例集的方... 当采用组合测试方法对智能高速铁路列车自动驾驶(ATO)功能测试时,输入参数动态取值易导致重复或无效的测试用例生成,甚至引发组合爆炸。为了满足ATO功能测试的覆盖力度和效率要求,提出一种利用启发式可变力度覆盖表生成测试用例集的方法。首先,分析ATO模式转换流程,提取相关设备的故障特征,构建测试参数表,作为输入参数;其次,根据功能测试参数覆盖需求,确定可变力度覆盖表的维度,得到小规模测试用例集;再次,利用遗传算法控制测试用例的进化和变异,扩充小规模测试用例集的垂直维度;同时,结合贪心策略生成测试用例局部最优解,扩充测试用例集的水平维度,最终生成满足覆盖需求的初始测试用例集;最后,依托京沈高速铁路仿真测试平台,验证所提方法的有效性。实验结果表明:所提方法相比固定力度覆盖表,在达到相同覆盖力度的前提下,生成的测试用例数量平均减少了31.91%;相比基于TS-C、IPOG-D、GA和WOA的测试用例生成算法,最小故障模式的检测率分别提升了5.06%、6.95%、28.18%和28.99%。所提方法具有较好的测试用例约简和故障检测能力,可为智能高速铁路ATO功能验证及安全性评估提供一定的参考。 展开更多
关键词 列车自动驾驶 组合测试 测试用例生成 覆盖表 遗传算法 贪心策略
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基于模糊最大覆盖模型的无人机应急配送中心选址研究 认领 引用
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作者 万莉莉 徐舒梦 +2 位作者 黄嘉慧 张庆阳 袁振宇 《交通运输系统工程与信息》 EI CSCD 北大核心 2026年第3期166-175,共10页
针对突发灾害救援中物资需求及无人机覆盖半径的不确定问题,本文提出一种基于模糊理论的无人机应急配送中心选址优化方法。基于地理数据,利用k-means算法识别需求点及候选设施位置。采用三角与梯形模糊数刻画参数不确定性,引入可信度约... 针对突发灾害救援中物资需求及无人机覆盖半径的不确定问题,本文提出一种基于模糊理论的无人机应急配送中心选址优化方法。基于地理数据,利用k-means算法识别需求点及候选设施位置。采用三角与梯形模糊数刻画参数不确定性,引入可信度约束,构建以覆盖需求量最大、总成本最小和空间公平性最优为目标的模糊最大覆盖选址模型(FMCLP)。设计嵌入模糊模拟的混合模拟退火算法,利用蒙特卡洛采样处理模糊参数,通过局部搜索与自适应冷却机制实现全局寻优。以南京市江宁区为例进行对比实验和灵敏度分析。结果表明:相较于经典确定性模型,该方案在同等设施规模下覆盖需求量提升82个单位,总成本降低6.14万元,最大未覆盖距离缩减7.63 km,且在设施失效时具有更优的鲁棒性;确定覆盖需求量、总成本与公平性的最优权重组合为(0.7,0.2,0.1),并识别出区域核心枢纽设施。研究结果验证了模型在复杂不确定环境下的适用性,可为城市无人机应急物流网络规划提供科学决策依据。 展开更多
关键词 航空运输 设施选址 模糊最大覆盖模型 无人机(UAV) 应急物流 模拟退火算法
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基于Landsat-8开封市主城区地表温度反演分析研究 认领 引用
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作者 王冬梅 《测绘与空间地理信息》 2026年第3期56-59,共4页
以2013年和2020年开封市主城区Landsat-8影像为数据源,基于QUEST算法进行遥感图像决策树分类得到土地覆盖分类图与对应植被覆盖度,计算得到地表比辐射率;结合过境时间接近的Terra/MODIS水汽产品MOD05-L2获取水汽含量计算大气透过率;根... 以2013年和2020年开封市主城区Landsat-8影像为数据源,基于QUEST算法进行遥感图像决策树分类得到土地覆盖分类图与对应植被覆盖度,计算得到地表比辐射率;结合过境时间接近的Terra/MODIS水汽产品MOD05-L2获取水汽含量计算大气透过率;根据研究区域的亮度温度、地表比辐射率和大气透过率,采用劈窗算法反演地表温度,进而分析城市热岛效应。结果表明:水体及植被覆盖区域地表温度较低,建筑地的地表温度相对较高。2020年相对于2013年城市热岛效应有效缓解,为研究区域政府减缓城市热岛效应提供参考数据。 展开更多
关键词 土地覆盖分类 劈窗算法 地表温度反演 热岛效应
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Innovative Deep Learning Models for Streamflow Forecasting in High Elevation Catchments 认领 引用
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作者 Rana Muhammad Adnan Ikram Jing-Cheng Han +4 位作者 Ahmed A.Ewees Mo Wang Ozgur Kisi Salim Heddam Mohammad Zounemat-Kermani 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第7期911-934,共24页
Two-phase optimized machine learning and deep learning models play a key role in enhancing the prediction accuracy of nonlinear time series modeling.This study assesses the performance of a novel two-phase optimized L... Two-phase optimized machine learning and deep learning models play a key role in enhancing the prediction accuracy of nonlinear time series modeling.This study assesses the performance of a novel two-phase optimized Long Short-Term Memory(LSTM)model with integration of Aquila Optimizer(AO)and Wild Horse Optimizer(WHO)in predicting monthly streamflow in a snow-fed catchment.The two-phase optimized LSTM-WHOAO model is compared with single-phase optimized models such as LSTM-GA(Genetic Algorithm),LSTM-GWO(Grey Wolf Optimizer),LSTM-WOA(Whale Optimization Algorithm),LSTM-AO,and LSTM-WHO.The outcomes acquired from the deep learning models were compared using four statistical measures:root-mean-square-error(RMSE),mean absolute error(MAE),Nash-Sutcliffe efficiency(NSE),and coefficient of determination(R²).The LSTM-WHOAO model exhibited the best performance during training,with a mean RMSE of 51.930 and an R² of 0.851.The LSTM-WHO model also demonstrated robust performance,achieving an average RMSE of 53.900 and an R² value of 0.840.Other models,such as LSTM-AO and LSTM-WOA,showed average RMSE of 57.135 and 58.978,respectively,indicating improved performance over the single LSTM model.For the testing stage,the LSTM-WHOAO model remained more effective than other models,with an average RMSE of 70.413 and an R²of 0.755.For peak streamflow events,the LSTM-WHOAO model had the lowest absolute error(201.4%),significantly reducing prediction error compared to other models such as LSTM-GA(333.9%)and LSTM(347.1%).For peak streamflow events,the LSTM-WHOAO model had the lowest absolute error(201.4%),significantly reducing the prediction error compared to other models such as LSTM-GA(333.9%)and LSTM(347.1%).Models that incorporated snow-covered area(SCA)data,such as LSTM-WHOAO and LSTM-WHO,showed lower RMSE and higher R²values,underscoring the importance of considering snow cover dynamics in streamflow forecasting.The LSTM-WHOAO model proved to be the most successful,showing superior results in both the training and testing stages,as well as in peak streamflow predictions.By addressing the unique challenges of snow-fed catchments,this research offers valuable insights,especially into the application of advanced ML techniques in hydrology. 展开更多
关键词 Streamflow prediction long short-term memory genetic algorithm grey wolf optimizer whale optimization algorithm aquila optimizer wild horse optimizer algorithm snow covered area
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集合覆盖问题:算法与应用 认领 引用
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作者 锁小娜 王晓峰 +2 位作者 颜冬 胡思敏 宋家欢 《计算机工程与应用》 EI CSCD 北大核心 2026年第8期1-20,共20页
集合覆盖问题作为组合优化领域的核心基础问题,因其NP-hard复杂性,广泛应用于无线网络基站部署、物流配送路径规划等工程领域,具有重要的实际应用价值。近年来,针对其求解的算法研究不断推进,主要包括启发式算法、群智能优化算法、进化... 集合覆盖问题作为组合优化领域的核心基础问题,因其NP-hard复杂性,广泛应用于无线网络基站部署、物流配送路径规划等工程领域,具有重要的实际应用价值。近年来,针对其求解的算法研究不断推进,主要包括启发式算法、群智能优化算法、进化算法、机器学习以及基于实际应用的算法等。系统地梳理集合覆盖问题的研究现状与算法发展脉络,从算法设计原理、结构适应性、性能对比等方面展开综述。总结各类算法的优势与局限,归纳适用场景与发展趋势,并展望集合覆盖问题在大规模数据集下的研究方向,旨在为相关研究提供理论支持与方法指导。 展开更多
关键词 集合覆盖问题(SCP) 群智能优化算法 进化算法 启发式算法 机器学习
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Assessing impact of climate change on forest cover type shifts in Western Himalayan Eco-region 认领 引用 被引量：1
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作者 P.K.Joshi Asha Rawat +1 位作者 Sheena Narula Vinay Sinha 《Journal of Forestry Research》 CAS CSCD 2012年第1期75-80,共6页
Climate is a critical factor affecting forest ecosystems and their capacity to produce goods and services. Effects of climate change on forests depend on ecosystem-specific factors including dimensions of climate （te... Climate is a critical factor affecting forest ecosystems and their capacity to produce goods and services. Effects of climate change on forests depend on ecosystem-specific factors including dimensions of climate （temperature, precipitation, drought, wind etc.）. Available infor- mation is not sufficient to support a quantitative assessment of the eco- logical, social and economic consequences. The present study assessed shifts in forest cover types of Western Himalayan Eco-region （700-4 500 m）. 100 randomly selected samples （75 for training and 25 for testing the model）, genetic algorithm of rule set parameters and climatic envelopes were used to assess the distribution of five prominent forest cover types （Temperate evergreen, Tropical semi-evergreen, Temperate conifer, Sub- tropical conifer, and Tropical moist deciduous forests）. Modelling was conducted for four different scenarios, current scenario, changed precipi- tation （8% increase）, changed temperature （1.07℃ increase）, and both changed temperature and precipitation. On increasing precipitation a downward shift in the temperate evergreen and tropical semi-evergreen was observed, while sub-tropical conifer and tropical moist-deciduous forests showed a slight upward shift and temperate conifer showed ＇no shift. On increasing temperatm＇e, an upward shift in all forest types was observed except sub-tropical conifer forests without significant changes. When both temperature and precipitation were changed, the actual dis- tribution was maintained and slight upward shift was observed in all the forest types except sub-tropical conifer. It is important to understand the likely impacts of the projected climate change on the forest ecosystems, so that better management and conservation strategies can be adopted for the biodiversity and forest dependent community. Knowledge of impact mechanisms also enables identification and mitigation of some of the conditions that increase vulnerability to climate change in the forest sector. 展开更多
关键词 Climate change forest cover types shift western Himalaya genetic algorithm
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基于弧段风险量化的铁路救援列车布局优化及混合算法改进研究 认领 引用
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作者 韩佳英 刘敬辉 +4 位作者 李秋芬 刘鑫贵 张俊伟 张济洲 张雨晨 《中国铁道科学》 EI CAS CSCD 北大核心 2026年第2期221-231,共11页
为优化我国铁路救援列车布局以提高铁路应急救援效能,在弧段风险量化的基础上,对遗传-模拟退火混合算法进行改进。首先,构建多维度路网风险量化评价指标体系,运用熵权-TOPSIS法对路网各弧段进行风险量化评价,并结合覆盖理论,构建以路网... 为优化我国铁路救援列车布局以提高铁路应急救援效能,在弧段风险量化的基础上,对遗传-模拟退火混合算法进行改进。首先,构建多维度路网风险量化评价指标体系,运用熵权-TOPSIS法对路网各弧段进行风险量化评价,并结合覆盖理论,构建以路网救援覆盖率、救援时间满意度和救援列车布局成本为目标的铁路救援列车最优布局模型;其次,设计多阶段自适应模拟退火遗传算法(MP-ASAGA)对模型进行求解,将求解过程分为重点搜索全局最优解的探索阶段和重点加速收敛的开发阶段,在各阶段采取不同进化策略提升算法的求解性能;最后,以我国某铁路局的实际路网数据为案例进行计算验证。结果表明:与案例中路局的原布局方案相比,运用所提方法求解得到的铁路救援列车最优布局方案的路网救援覆盖率提升8.99%,救援时间满意度提升11.62%。该方法可为铁路救援列车的布局优化及救援效能提升提供相应的理论支持。 展开更多
关键词 铁路救援列车 熵权-TOPSIS法 覆盖理论 最大覆盖选址问题 启发式算法
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基于多波束的冷泉区海底覆盖类型分类研究 认领 引用
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作者 王利利 张建兴 +2 位作者 崔晓东 栾振东 阳凡林 《海洋测绘》 CSCD 北大核心 2026年第2期39-42,共4页
针对传统支持向量机在参数选择方面易受人工经验影响陷入局部最优,难以适应冷泉区复杂环境下的分类需求问题,以中国台湾西南海域福尔摩沙海脊冷泉区为例,构建多维特征体系,通过粒子群优化算法对支持向量机的惩罚因子与核函数参数进行全... 针对传统支持向量机在参数选择方面易受人工经验影响陷入局部最优,难以适应冷泉区复杂环境下的分类需求问题,以中国台湾西南海域福尔摩沙海脊冷泉区为例,构建多维特征体系,通过粒子群优化算法对支持向量机的惩罚因子与核函数参数进行全局自适应寻优,实现冷泉区海底覆盖类型的精确分类。结果表明,该模型的总体分类精度达87.22%,Kappa系数为0.825 1,优于传统分类方法。研究提出的融合多源特征的模型能够提升冷泉区海底覆盖类型的识别精度,为冷泉区海底覆盖类型识别及生态地质过程研究提供技术参考。 展开更多
关键词 海底覆盖类型 多波束测深 海底冷泉 支持向量机 粒子群优化算法
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基于GEE平台的北海市土地覆被信息提取与长时序变化分析 认领 引用
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作者 陶衡 李金萍 +1 位作者 邹冲今 盘燕林 《河南科学》 CAS 2026年第4期751-758,共8页
为揭示典型滨海中小城市土地利用/覆被格局的长期演变特征及阶段性变化规律,支撑国土空间精细化管控决策,本文以北海市为研究对象,依托Google Earth Engine(GEE)平台,基于2000—2023年Landsat长时间序列遥感影像,采用随机森林方法开展... 为揭示典型滨海中小城市土地利用/覆被格局的长期演变特征及阶段性变化规律,支撑国土空间精细化管控决策,本文以北海市为研究对象,依托Google Earth Engine(GEE)平台,基于2000—2023年Landsat长时间序列遥感影像,采用随机森林方法开展土地利用/覆被分类,并结合土地利用转移矩阵分析其时空演变特征。研究表明:(1)各期土地覆被分类结果整体精度较高且稳定,总体分类精度(OA)均高于0.88,Kappa系数介于0.87~0.90之间。(2)研究期内北海市建设用地由中心城区和交通廊道向沿海地带及城市外围拓展,空间形态由单中心向多极化演变,耕地减少及部分生态用地在城镇扩张区受到挤压。(3)2000—2023年间,建设用地、林地面积分别增加73.75、396.77 km2,耕地减少458.99 km2。2000—2010年以生态结构调整为主,2010—2020年城镇扩张显著加速,2020—2023年土地利用转移强度明显减弱,建设用地由外延扩张向存量优化转型,土地利用格局趋于稳定与集约化发展。GEE平台结合机器学习方法在滨海城市长时序土地利用变化监测中具有较高适用性,可为土地资源管理与国土空间规划提供可靠技术支撑。 展开更多
关键词 土地覆被信息 长时序变化 GEE 随机森林算法 众数滤波算法 北海市
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