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A Fast Underwater Optical Image Segmentation Algorithm Based on a Histogram Weighted Fuzzy C-means Improved by PSO 被引量:4
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作者 王士龙 徐玉如 庞永杰 《Journal of Marine Science and Application》 2011年第1期70-75,共6页
The S/N of an underwater image is low and has a fuzzy edge.If using traditional methods to process it directly,the result is not satisfying.Though the traditional fuzzy C-means algorithm can sometimes divide the image... The S/N of an underwater image is low and has a fuzzy edge.If using traditional methods to process it directly,the result is not satisfying.Though the traditional fuzzy C-means algorithm can sometimes divide the image into object and background,its time-consuming computation is often an obstacle.The mission of the vision system of an autonomous underwater vehicle (AUV) is to rapidly and exactly deal with the information about the object in a complex environment for the AUV to use the obtained result to execute the next task.So,by using the statistical characteristics of the gray image histogram,a fast and effective fuzzy C-means underwater image segmentation algorithm was presented.With the weighted histogram modifying the fuzzy membership,the above algorithm can not only cut down on a large amount of data processing and storage during the computation process compared with the traditional algorithm,so as to speed up the efficiency of the segmentation,but also improve the quality of underwater image segmentation.Finally,particle swarm optimization (PSO) described by the sine function was introduced to the algorithm mentioned above.It made up for the shortcomings that the FCM algorithm can not get the global optimal solution.Thus,on the one hand,it considers the global impact and achieves the local optimal solution,and on the other hand,further greatly increases the computing speed.Experimental results indicate that the novel algorithm can reach a better segmentation quality and the processing time of each image is reduced.They enhance efficiency and satisfy the requirements of a highly effective,real-time AUV. 展开更多
关键词 underwater image image segmentation autonomous underwater vehicle (AUV) gray-scale histogram fuzzy c-means real-time effectiveness sine function particle swarm optimization (PSO)
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ALLIED FUZZY c-MEANS CLUSTERING MODEL 被引量:2
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作者 武小红 周建江 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2006年第3期208-213,共6页
A novel model of fuzzy clustering, i.e. an allied fuzzy c means (AFCM) model is proposed based on the combination of advantages of fuzzy c means (FCM) and possibilistic c means (PCM) clustering. PCM is sensitive... A novel model of fuzzy clustering, i.e. an allied fuzzy c means (AFCM) model is proposed based on the combination of advantages of fuzzy c means (FCM) and possibilistic c means (PCM) clustering. PCM is sensitive to initializations and often generates coincident clusters. AFCM overcomes this shortcoming and it is an ex tension of PCM. Membership and typicality values can be simultaneously produced in AFCM. Experimental re- suits show that noise data can be well processed, coincident clusters are avoided and clustering accuracy is better. 展开更多
关键词 fuzzy c-means clustering possibilistic c means clustering allied fuzzy c-means clustering
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Fuzzy C-Means算法中隶属度信息在特征空间的分布特性分析及改进方法 被引量:2
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作者 胡世英 周源华 《红外与毫米波学报》 SCIE EI CAS CSCD 北大核心 1999年第1期67-72,共6页
首先推导了FuzzyC-Means算法在特征空间的迭代公式,然后就其隶属度信息在特征空间的分布缺陷提出两种改进方法:一是通过引入选择注意性参数控制隶属度信息的分布;二是从条件概率出发构造类置信度取代原隶属度.实验表明... 首先推导了FuzzyC-Means算法在特征空间的迭代公式,然后就其隶属度信息在特征空间的分布缺陷提出两种改进方法:一是通过引入选择注意性参数控制隶属度信息的分布;二是从条件概率出发构造类置信度取代原隶属度.实验表明这两种方法均起到了较好的效果. 展开更多
关键词 fuzzy 隶属度 选择注意性参数 置信度 FCM算法
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一种新的基于Fuzzy c-means的高效自适应截集算法
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作者 高晶 常亮 吴铁峰 《现代电子技术》 2006年第14期100-101,104,共3页
提出了一种新的模糊聚类方法-自适应截集算法。该方法克服了聚类数目c要求预先确定、局部最优、分类不确定等弱点,对算法结构加以改进,增加聚类有效性问题的分析,在聚类过程中可动态调整聚类数目。针对时间消耗问题,利用模糊截集提高分... 提出了一种新的模糊聚类方法-自适应截集算法。该方法克服了聚类数目c要求预先确定、局部最优、分类不确定等弱点,对算法结构加以改进,增加聚类有效性问题的分析,在聚类过程中可动态调整聚类数目。针对时间消耗问题,利用模糊截集提高分类识别的速度。经实验表明,本算法可以提高聚类算法的可靠程度和分类识别的正确性。 展开更多
关键词 模糊聚类 聚类数 自适应截集算法 聚类分析
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Soil pore identification with the adaptive fuzzy C-means method based on computed tomography images 被引量:5
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作者 Yue Zhao Qiaoling Han +1 位作者 Yandong Zhao Jinhao Liu 《Journal of Forestry Research》 SCIE CAS CSCD 2019年第3期1043-1052,共10页
The complex geometry and topology of soil is widely recognised as the key driver in many ecological processes. X-ray computed tomography (CT) provides insight into the internal structure of soil pores automatically an... The complex geometry and topology of soil is widely recognised as the key driver in many ecological processes. X-ray computed tomography (CT) provides insight into the internal structure of soil pores automatically and accurately. Until recently, there have not been methods to identify soil pore structures. This has restricted the development of soil science, particularly regarding pore geometry and spatial distribution. Through the adoption of the fuzzy clustering theory and the establishment of pore identification rules, a novel pore identification method is described to extract pore structures from CT soil images. The robustness of the adaptive fuzzy C-means method (AFCM), the adaptive threshold method, and Image-Pro Plus tools were compared on soil specimens under different conditions, such as frozen, saturated, and dry situations. The results demonstrate that the AFCM method is suitable for identifying pore clusters, especially tiny pores, under various soil conditions. The method would provide an optional technique for the study of soil micromorphology. 展开更多
关键词 CT soil IMAGES fuzzy c-means fuzzy clustering theory PORE IDENTIFICATION rule
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基于优化模糊C-means算法的不平衡大数据分类研究
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作者 卓柳俊 曾心怡 《信息技术》 2024年第10期14-21,29,共9页
针对不平衡大数据的分类问题,提出一种优化模糊C-means算法的不平衡大数据分类算法。先计算C-means模糊交叉算子,定义优化函数,并求解大数据不平衡增益。利用Spark分类平台,确定大数据样本压缩模糊近邻值的取值范围,再通过放大近邻值的... 针对不平衡大数据的分类问题,提出一种优化模糊C-means算法的不平衡大数据分类算法。先计算C-means模糊交叉算子,定义优化函数,并求解大数据不平衡增益。利用Spark分类平台,确定大数据样本压缩模糊近邻值的取值范围,再通过放大近邻值的处理方式,定义不平衡阈向量,从而完善整个分类流程,完成基于优化模糊C-means算法的不平衡大数据分类方法的设计。实验结果表明,上述分类方法的应用,可将正例信息、负例信息的取样长度区间完全分离开来,能有效解决因不平衡大数据分类不精准造成的信息样本混淆的问题,符合实际应用需求。 展开更多
关键词 优化模糊c-means算法 不平衡大数据 交叉算子 卡方检验 压缩模糊近邻值
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NEW SHADOWED C-MEANS CLUSTERING WITH FEATURE WEIGHTS 被引量:2
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作者 王丽娜 王建东 姜坚 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2012年第3期273-283,共11页
Partition-based clustering with weighted feature is developed in the framework of shadowed sets. The objects in the core and boundary regions, generated by shadowed sets-based clustering, have different impact on the ... Partition-based clustering with weighted feature is developed in the framework of shadowed sets. The objects in the core and boundary regions, generated by shadowed sets-based clustering, have different impact on the prototype of each cluster. By integrating feature weights, a formula for weight calculation is introduced to the clustering algorithm. The selection of weight exponent is crucial for good result and the weights are updated iteratively with each partition of clusters. The convergence of the weighted algorithms is given, and the feasible cluster validity indices of data mining application are utilized. Experimental results on both synthetic and real-life numerical data with different feature weights demonstrate that the weighted algorithm is better than the other unweighted algorithms. 展开更多
关键词 fuzzy c-means shadowed sets shadowed c-means feature weights cluster validity index
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ADAPTIVE GENETIC ALGORITHM BASED ON SIX FUZZY LOGIC CONTROLLERS 被引量:3
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作者 朱力立 张焕春 经亚枝 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2003年第2期230-235,共6页
The performance of genetic algorithm(GA) is determined by the capability of search and optimization for satisfactory solutions. The new adaptive genetic algorithm(AGA) is built for inducing suitable search and optimiz... The performance of genetic algorithm(GA) is determined by the capability of search and optimization for satisfactory solutions. The new adaptive genetic algorithm(AGA) is built for inducing suitable search and optimization relationship. The use of six fuzzy logic controllers(6FLCs) is proposed for dynamic control genetic operating parameters of a symbolic-coded GA. This paper uses AGA based on 6FLCs to deal with the travelling salesman problem (TSP). Experimental results show that AGA based on 6FLCs is more efficient than a standard GA in solving combinatorial optimization problems similar to TSP. 展开更多
关键词 adaptive genetic algorithm fuzzy controller dynamic parameters control TSP
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Multisensor Fuzzy Stochastic Fusion Based on Genetic Algorithms 被引量:3
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作者 胡昌振 谭惠民 《Journal of Beijing Institute of Technology》 EI CAS 2000年第1期49-54,共6页
To establish a parallel fusion approach of processing high dimensional information, the model and criterion of multisensor fuzzy stochastic data fusion were presented. In order to design genetic algorithm fusion, the ... To establish a parallel fusion approach of processing high dimensional information, the model and criterion of multisensor fuzzy stochastic data fusion were presented. In order to design genetic algorithm fusion, the fusion parameter coding, initial population and fitness function establishing, and fuzzy logic controller designing for genetic operations and probability choosing were completed. The discussion on the highly dimensional fusion was given. For a moving target with the division of 1 64 (velocity) and 1 75 (acceleration), the precision of fusion is 0 94 and 0 98 respectively. The fusion approach can improve the reliability and decision precision effectively. 展开更多
关键词 MULTISENSOR data fusion fuzzy random genetic algorithm
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基于改进的模糊C-Means航迹聚类方法研究 被引量:19
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作者 王超 王明明 王飞 《中国民航大学学报》 CAS 2013年第3期14-18,共5页
为指导飞行程序的改善和发现管制员的指挥模式,在分析历史飞行航迹特征基础上,应用最小描绘长度(MDL)原理对航迹特征点进行划分,运用融合了遗传算法和模拟退火算法的改进的模糊C-Means算法对特征点进行聚类,通过最长公共子序列(LCS)算... 为指导飞行程序的改善和发现管制员的指挥模式,在分析历史飞行航迹特征基础上,应用最小描绘长度(MDL)原理对航迹特征点进行划分,运用融合了遗传算法和模拟退火算法的改进的模糊C-Means算法对特征点进行聚类,通过最长公共子序列(LCS)算法得到航迹相似性矩阵,利用矩阵得到航迹簇,最后形成中心航迹,算例仿真验证了新算法的有效性。 展开更多
关键词 航迹聚类 遗传模拟退火算法 模糊C—Means 最长公共子序列
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A fast and effective fuzzy clustering algorithm for color image segmentation 被引量:4
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作者 王改华 李德华 《Journal of Beijing Institute of Technology》 EI CAS 2012年第4期518-525,共8页
A fast and effective fuzzy clustering algorithm is proposed. The algorithm splits an image into n × n blocks, and uses block variance to judge whether the block region is homogeneous. Mean and center pixel of eac... A fast and effective fuzzy clustering algorithm is proposed. The algorithm splits an image into n × n blocks, and uses block variance to judge whether the block region is homogeneous. Mean and center pixel of each homogeneous block are extracted for feature. Each inhomogeneous block is split into separate pixels and the mean of neighboring pixels within a window around each pixel and pixel value are extracted for feature. Then cluster of homogeneous blocks and cluster of separate pixels from inhomogeneous blocks are carried out respectively according to different membership functions. In fuzzy clustering stage, the center pixel and center number of the initial clustering are calculated based on histogram by using mean feature. Then different membership functions according to comparative result of block variance are computed. Finally, modified fuzzy c-means with spatial information to complete image segmentation axe used. Experimental results show that the proposed method can achieve better segmental results and has shorter executive time than many well-known methods. 展开更多
关键词 CLUSTER image segmentation fuzzy c-means HISTOGRAM
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A Fuzzy Decision Based WSN Localization Algorithm for Wise Healthcare 被引量:1
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作者 Jiangyu Yan Ran Qiao +2 位作者 Liangrui Tang Chenxi Zheng Bing Fan 《China Communications》 SCIE CSCD 2019年第4期208-218,共11页
Wise healthcare is a typical application of wireless sensor network(WSN), which uses sensors to monitor the physiological state of nursing targets and locate their position in case of an emergency situation. The locat... Wise healthcare is a typical application of wireless sensor network(WSN), which uses sensors to monitor the physiological state of nursing targets and locate their position in case of an emergency situation. The location of targets need to be determined and reported to the control center,and this leads to the localization problem. While localization in healthcare field demands high accuracy and regional adaptability, the information processing mechanism of human thinking has been introduced,which includes knowledge accumulation, knowledge fusion and knowledge expansion. Furthermore, a fuzzy decision based localization approach is proposed. Received signal strength(RSS) at references points are obtained and processed as position relationship indicators, using fuzzy set theory in the knowledge accumulation stage; after that, optimize degree of membership corresponding to each anchor nodes in different environments during knowledge fusion; the matching degree of reference points is further calculated and sorted in decision-making, and the coordinates of several points with the highest matching degree are utilized to estimate the location of unknown nodes while knowledge expansion. Simulation results show that the proposed algorithm get better accuracy performance compared to several traditional algorithms under different typical occasions. 展开更多
关键词 WSN localization WISE healthcare fuzzy DECISION algorithm reference POINTS MATCHING DEGREE
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Research on the fully fuzzy time-cost trade-off based on genetic algorithms 被引量:1
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作者 JIN Chao-guang JI Zhuo-shang +2 位作者 LIN Yan ZHAO Yuan-min HUANG Zhen-dong 《Journal of Marine Science and Application》 2005年第3期18-23,共6页
It is very difficult to estimate exact values of time and cost of an activity in project scheduling process because many uncertain factors, such as weather, productivity level, human factors etc. , dynamically affect ... It is very difficult to estimate exact values of time and cost of an activity in project scheduling process because many uncertain factors, such as weather, productivity level, human factors etc. , dynamically affect them during project implementation process. A GAs-based fully fuzzy optimal time-cost trade-off model is presented based on fuzzy sets and genetic algorithms (GAs). In tihs model all parameters and variables are characteristics by fuzzy numbers. And then GAs is adopted to search for the optimal solution to this model. The method solves the time-cost trade-off problems under an uncertain environment and is proved practicable through a giving example in ship building scheduling. 展开更多
关键词 fuzzy sets ranking fuzzy number genetic algorithms time-cost trade-off
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A New Fuzzy Adaptive Genetic Algorithm 被引量:6
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作者 房磊 张焕春 经亚枝 《Journal of Electronic Science and Technology of China》 2005年第1期57-59,71,共4页
Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while kee... Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained. 展开更多
关键词 adaptive genetic algorithm fuzzy logic controller dynamic parameters control population sizes
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Using genetic algorithm based fuzzy adaptive resonance theory for clustering analysis 被引量:3
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作者 LIU Bo WANG Yong WANG Hong-jian 《哈尔滨工程大学学报》 EI CAS CSCD 北大核心 2006年第B07期547-551,共5页
关键词 聚类分析 遗传算法 模糊自适应谐振理论 人工神经网络
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Image Retrieval Approach Based on Intuitive Fuzzy Set Combined with Genetic Algorithm
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作者 王潇茵 徐卫华 胡昌振 《Journal of Beijing Institute of Technology》 EI CAS 2009年第1期60-64,共5页
Aiming at shortcomings of traditional image retrieval systems, a new image retrieval approach based on color features of image combining intuitive fuzzy theory with genetic algorithm is proposed. Each image is segment... Aiming at shortcomings of traditional image retrieval systems, a new image retrieval approach based on color features of image combining intuitive fuzzy theory with genetic algorithm is proposed. Each image is segmented into a constant number of sub-images in vertical direction. Color features are extracted from every sub-image to get chromosome coding. It is considered that fuzzy membership and intuitive fuzzy hesitancy degree of every pixel's color in image are associated to all the color histogram bins. Certain feature, fuzzy feature and intuitive fuzzy feature of colors in an image, are used together to describe the content of image. Efficient combinations of sub-image are selected according to operation of selecting, crossing and variation. Retrieval results are obtained from image matching based on these color feature combinations of sub-images. Tests show that this approach can improve the accuracy of image retrieval in the case of not decreasing the speed of image retrieval. Its mean precision is above 80 %. 展开更多
关键词 intuitive fuzzy genetic algorithm color histogram image retrieval
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Mercer Kernel Based Fuzzy Clustering Self-Adaptive Algorithm
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作者 李侃 刘玉树 《Journal of Beijing Institute of Technology》 EI CAS 2004年第4期351-354,共4页
A novel mercer kernel based fuzzy clustering self-adaptive algorithm is presented. The mercer kernel method is introduced to the fuzzy c-means clustering. It may map implicitly the input data into the high-dimensional... A novel mercer kernel based fuzzy clustering self-adaptive algorithm is presented. The mercer kernel method is introduced to the fuzzy c-means clustering. It may map implicitly the input data into the high-dimensional feature space through the nonlinear transformation. Among other fuzzy c-means and its variants, the number of clusters is first determined. A self-adaptive algorithm is proposed. The number of clusters, which is not given in advance, can be gotten automatically by a validity measure function. Finally, experiments are given to show better performance with the method of kernel based fuzzy c-means self-adaptive algorithm. 展开更多
关键词 fuzzy c-means mercer kernel feature space validity measure function
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Applying Neural Network withGenetic Algorithm and FuzzySelection Models to Select Equipmentsfor Fully-Mechanized Coal Mining
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作者 王新宇 吴瑞明 冯春花 《Journal of China University of Mining and Technology》 2004年第2期147-151,共5页
According to the typical engineering samples, a neural net work model with genetic algorithm to optimize weight values is put forward to forecast the productivities and efficiencies of mining faces. By this model we c... According to the typical engineering samples, a neural net work model with genetic algorithm to optimize weight values is put forward to forecast the productivities and efficiencies of mining faces. By this model we can obtain the possible achievements of available equipment combinations under certain geological situations of fully-mechanized coal mining faces. Then theory of fuzzy selection is applied to evaluate the performance of each equipment combination. By detailed empirical analysis, this model integrates the functions of forecasting mining faces' achievements and selecting optimal equipment combination and is helpful to the decision of equipment combination for fully-mechanized coal mining. 展开更多
关键词 GENETIC algorithm artificial neural network fuzzy SELECTION SELECTION of equipment combination
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Design of fuzzy adaptive washout algorithm based on the novel tilt coordinate
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作者 WANG Hui ZHU Dao-yang CHENG Yuan-jie 《Journal of Chongqing University》 CAS 2018年第1期27-38,共12页
Motion simulator usually appears the phenomenon of false cues and the workspace is limited in the process of washout. The proposed washout algorithm combines fuzzy logic control with the vestibular system to design th... Motion simulator usually appears the phenomenon of false cues and the workspace is limited in the process of washout. The proposed washout algorithm combines fuzzy logic control with the vestibular system to design the tilt coordination fuzzy adaptive filter, in order to minimize the vestibular sensory error below the human perception threshold. Owing to tilt coordination angular velocity limiter, the loss of low-pass acceleration must be compensated by the acceleration transform model. The translational channel decreases the possibility of the workspace beyond limitation and expands the scope of motion platform simulating input acceleration by using third-order filter. The simulation results show that the proposed algorithm can effectively overcome the phase retardation of classical washout algorithm, and then prevent the produce of false cues, decrease the displacement of motion platform simultaneously; in addition, white Gaussian noise simulates large variations in acceleration. The proposed washout algorithm can have maximal extreme value of acceleration and accurate simulating performance in general. It also proves that the proposed washout algorithm has a strong adaptability and reliability, which can effectively improve the dynamic fidelity for motion simulator. 展开更多
关键词 classical washout algorithm fuzzy control false cues tilt coordinate washout filter vestibular system
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Integrated classification method of tight sandstone reservoir based on principal component analysise simulated annealing genetic algorithmefuzzy cluster means
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作者 Bo-Han Wu Ran-Hong Xie +3 位作者 Li-Zhi Xiao Jiang-Feng Guo Guo-Wen Jin Jian-Wei Fu 《Petroleum Science》 SCIE EI CSCD 2023年第5期2747-2758,共12页
In this research,an integrated classification method based on principal component analysis-simulated annealing genetic algorithm-fuzzy cluster means(PCA-SAGA-FCM)was proposed for the unsupervised classification of tig... In this research,an integrated classification method based on principal component analysis-simulated annealing genetic algorithm-fuzzy cluster means(PCA-SAGA-FCM)was proposed for the unsupervised classification of tight sandstone reservoirs which lack the prior information and core experiments.A variety of evaluation parameters were selected,including lithology characteristic parameters,poro-permeability quality characteristic parameters,engineering quality characteristic parameters,and pore structure characteristic parameters.The PCA was used to reduce the dimension of the evaluation pa-rameters,and the low-dimensional data was used as input.The unsupervised reservoir classification of tight sandstone reservoir was carried out by the SAGA-FCM,the characteristics of reservoir at different categories were analyzed and compared with the lithological profiles.The analysis results of numerical simulation and actual logging data show that:1)compared with FCM algorithm,SAGA-FCM has stronger stability and higher accuracy;2)the proposed method can cluster the reservoir flexibly and effectively according to the degree of membership;3)the results of reservoir integrated classification match well with the lithologic profle,which demonstrates the reliability of the classification method. 展开更多
关键词 Tight sandstone Integrated reservoir classification Principal component analysis Simulated annealing genetic algorithm fuzzy cluster means
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