Suchergebnisse - "Fuzzy C-means Algorithm"

Pythagorean fuzzy C‐means algorithm for image segmentation von Ma, Rong, Zeng, Wenyi, Song, Guangcheng, Yin, Qian, Xu, Zeshui

“… In recent decades, image segmentation has aroused great interest of many researchers, and has become an important part of machine learning, pattern …”
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A Unified Form of Fuzzy C-Means and K-Means algorithms and its Partitional Implementation von Borlea, Ioan-Daniel, Precup, Radu-Emil, Borlea, Alexandra-Bianca, Iercan, Daniel

“… This paper proposes as an element of novelty the Unified Form (UF) clustering algorithm, which treats Fuzzy C-Means (FCM) and K-Means (KM) algorithms as a …”
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Cloud Workload Forecasting via Latency‐Aware Time Series Clustering‐Based Scheduling Technique von Sridhar, P., Sathiya, R. R.

“… ABSTRACT Cloud computing is a fundamental paradigm for computing services based on the elasticity attribute, in which available resources are effectively …”
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A small-object segmentation algorithm for intercluster imbalance based on histogram- and stickiness-aware boosting von Chong, Qianpeng, Wen, Jiakun, Wan, Qianhui, Zeng, Wenyi, Yin, Qian, Cheng, Dong

“… Traditional fuzzy C-means (FCM) clustering and its variants, as important unsupervised image segmentation methods, have average performance, usually perform …”
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Intuitionistic Fuzzy C-Means Algorithm Based on Membership Information Transfer-Ring and Similarity Measurement von Chen, Haipeng, Xie, Zeyu, Huang, Yongping, Gai, Di

“… The fuzzy C-means clustering (FCM) algorithm is used widely in medical image segmentation and suitable for segmenting brain tumors. Therefore, an …”
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Robust unsupervised small area change detection from SAR imagery using deep learning von Zhang, Xinzheng, Su, Hang, Zhang, Ce, Gu, Xiaowei, Tan, Xiaoheng, Atkinson, Peter M.

“… [Display omitted] •A multiscale superpixel reconstruction method was developed to generate the Difference Image.•A two-stage center-constrained FCM algorithm …”
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A novel hybrid Extreme Learning Machine and Teaching–Learning-Based​ Optimization algorithm for skin cancer detection von Priyadharshini, N., N., Selvanathan, Hemalatha, B., Sureshkumar, C.

“… Skin cancers, such as melanoma, can be difficult to spot in their early stages because they often resemble benign moles. Early detection of melanoma is crucial …”
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Performance based analysis between k-Means and Fuzzy C-Means clustering algorithms for connection oriented telecommunication data von T., Velmurugan

“… •The partition based clustering algorithms k-Means and Fuzzy C-Means algorithms are taken for analysis via its computational time.•The distance between servers …”
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Intuitionistic fuzzy local information C-means algorithm for image segmentation von Cui, Hanshuai, Xie, Zheng, Zeng, Wenyi, Ma, Rong, Zhang, Yinghui, Yin, Qian, Xu, Zeshui

“… Image segmentation allows us to separate an image into distinct, non-overlapping parts by utilizing specific features such as hue, texture, and shape. The …”
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Interval possibilistic C-means algorithm and its application in image segmentation von Zeng, Wenyi, Liu, Yuqing, Cui, Hanshuai, Ma, Rong, Xu, Zeshui

“… Currently, image segmentation is widely used in face recognition, medical imaging, traffic control systems, and many other fields. The traditional …”
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Methods of Resource Scheduling Based on Optimized Fuzzy Clustering in Fog Computing von Li, Guangshun, Liu, Yuncui, Wu, Junhua, Lin, Dandan, Zhao, Shuaishuai

“… Cloud computing technology is widely used at present. However, cloud computing servers are far from terminal users, which may lead to high service request …”
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Coupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones von Liang, Xun, Liu, Xiaoping, Chen, Guangliang, Leng, Jiye, Wen, Youyue, Chen, Guangzhao

“… Modeling urban growth in Economic development zones (EDZs) can help planners determine appropriate land policies for these regions. However, sometimes EDZs are …”
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An application of sine cosine algorithm-based fuzzy possibilistic c-ordered means algorithm to cluster analysis von Kuo, R. J., Lin, Jun-Yu, Nguyen, Thi Phuong Quyen

“… Due to advances in information technology, data collection is becoming much easier. Clustering is an important technique for exploring data structures used in …”
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Consensus reaching process using personalized modification rules in large-scale group decision-making von Guo, Lun, Zhan, Jianming, Kou, Gang

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Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks von Zahedi, Zeynab Molay, Akbari, Reza, Shokouhifar, Mohammad, Safaei, Farshad, Jalali, Ali

“… •A fuzzy-based protocol is presented for clustered wireless sensor networks.•The main objective is to form balanced clusters over the network.•A hybrid swarm …”
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A hierarchical prediction model for lane-changes based on combination of fuzzy C-means and adaptive neural network von Tang, Jinjun, Yu, Shaowei, Liu, Fang, Chen, Xinqiang, Huang, Helai

“… •A hierarchical prediction model is proposed to predict steering angles.•The model combines fuzzy c-means and adaptive neural network.•A clustering learning …”
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Fuzzy c-means clustering algorithm for directional data (FCM4DD) von Kesemen, Orhan, Tezel, Özge, Özkul, Eda

“… •A new approximation for clustering of directional data is proposed.•The proposed method is simple, fast and stable when compared to other methods.•The …”
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Rapid identification and efficient resolution of rock mass structural planes using the OPFF algorithm: applications in slope stability analysis von Guan, Shenggong, Yuan, Mingsong, Wu, Faquan, Nan, Hu, Zheng, Hongchao

“… •A novel OPFF algorithm is proposed, integrating Octree, PCA, Firefly, and FCM for structural plane identification.•The method achieves high accuracy (<5% …”
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基于改进PSO-PFCM聚类算法的电力大数据异常检测方法 von 李清

“… 针对传统电力大数据异常检测方法检测精度低、复杂度高等问题,提出了一种将可能性模糊C均值算法和改进的粒子群优化算法相结合的电力大数据异常检测方法.使用改进的粒子群优 …”
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Data-driven prediction method for characteristics of voltage sag based on fuzzy time series von Wang, Ying, Yang, Min-hui, Zhang, Hua-ying, Wu, Xian, Hu, Wen-xi

“… •The prediction method for voltage sag events is guided by the classical fuzzy time-series prediction method.•This paper proposes a data preprocess method to …”
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