IMPLEMENTATION OF FUZZY C-MEANS AND FUZZY POSSIBILISTIC C-MEANS ALGORITHMS ON POVERTY DATA IN INDONESIA by Dian Kurniasari, Virda Kurniawati, Aang Nuryaman, Mustofa Usman, Rizki Khoirun Nisa

“…The methodologies employed include the Fuzzy C-Means (FCM) and Fuzzy Probabilistic C-Means (FPCM) algorithms. …”
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Turbid of Water By Using Fuzzy C- Means and Hard K- Means by Rand Muhaned Fawzi, Iden Hassan Alkanani

Subjects: “…Clustering, Turbid water, Fuzzy C Means algorithm, Hard K Means algorithm.…”
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A Novel Linguistic Relational Fuzzy C-Means by Peerawich Phaknonkul, Sansanee Auephanwiriyakul, Nipon Theera-Umpon

Subjects: “…Relational fuzzy C-means…”
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Comparison of Clustering Algorithms: Fuzzy C-Means, K-Means, and DBSCAN for House Classification Based on Specifications and Price by Dhendy Mardiansyah Putra, Ferian Fauzi Abdulloh

“…This study aims to compare the performance of three clustering algorithms, namely Fuzzy C-Means, K-Means, and DBSCAN, in grouping houses based on their specifications and prices. …”
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WSN clustering routing algorithm based on PSO optimized fuzzy C-means by Aijing SUN, Shichang LI, Yicai ZHANG

“…Aimed at the problems of limited energy and unbalanced load in wireless sensor network, POFCA based on particle swarm optimization fuzzy C-means was proposed.POFCA was respectively optimized from the cluster stage and the data transmission stage.In the clustering stage, the particle swarm optimization fuzzy C-means was firstly used to overcome the sensitivity to the initial clustering center.And the cluster head was dynamically updated according to the remaining power and the relative distance of the nodes to balance the network load.Then in the data transfer phase, a path evaluation function was designed based on the distance factor, the energy factor and the nodal load.Besides, the cat swarm optimization was used to search the optimal routing path for the cluster head to balance the load of the cluster head without increasing the load of the relay node.The simulation result shows that compared with algorithms of LEACH and LEACH-improved, POFCA can effectively balance the network load, reduce the energy consumption of nodes and extend the lifetime of the entire network.…”
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APPLICATION OF K-MEANS AND FUZZY C-MEANS ALGORITHMS TO DETERMINE FLOOD VULNERABILITY CLUSTERS (CASE STUDY: KUTAI KARTANEGARA REGENCY) by Desi Nurjanah, Indira Anggriani, Primadina Hasanah

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Collocating Recommendation Method for E-Commerce Based on Fuzzy C-Means Clustering Algorithm by LiJia Wang, Yanyan Jiang

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Comparative Study of Earthquake Clustering in Indonesia Using K-Medoids, K-Means, DBSCAN, Fuzzy C-Means and K-AP Algorithms by Nurfidah Dwitiyanti, Siti Ayu Kumala, Shinta Dwi Handayani

“…This research evaluates the effectiveness of five clustering algorithms—K-Medoids, K-Means, DBSCAN, Fuzzy C-Means, and K-Affinity Propagation (K-AP)—for analyzing earthquake data from January 2017 to January 2023. …”
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The Comparison Combination of Naïve Bayes Classification Algorithm with Fuzzy C-Means and K-Means for Determining Beef Cattle Quality in Semarang Regency by Feroza Rosalina Devi, Endang Sugiharti, Riza Arifudin

“…In this research, used the combination of Naïve Bayes Classification and Fuzzy C-Means algorithm also Naïve Bayes Classification and K-Means. …”
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Identification of Anomaly Detection in Power System State Estimation Based on Fuzzy C-Means Algorithm by Di Leng, Ziliang Qiu

“…An anomaly detection identification method based on fuzzy C-means algorithm is proposed to cluster the measured data and identify the anomaly detection of power system. …”
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A Bridge Crack Segmentation Algorithm Based on Fuzzy C-Means Clustering and Feature Fusion by Yadong Yao, Yurui Zhang, Zai Liu, Heming Yuan

“…In response to the limitations of traditional image processing algorithms, such as high noise sensitivity and threshold dependency in bridge crack detection, and the extensive labeled data requirements of deep learning methods, this study proposes a novel crack segmentation algorithm based on fuzzy C-means (FCM) clustering and multi-feature fusion. …”
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3D WSN clustering routing algorithm based on IHBA optimized fuzzy C-means by Jing YANG, Biyang XU, Weizheng LI, Wei LI, Zhaoqiang ZHU, Tao QIN

Subjects: “…3D wireless sensor network;clustering routing;honey badger algorithm;fuzzy C-means;energy consumption balance…”
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Rolling Bearing with Isometric Feature Mapping and Fuzzy C means Fault Identification Method by WANG Ya-ping, LI Shi-song, GE Jiang-hua, XU Di, LI Yun-fei

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Enhancing Fuzzy C-Means Clustering with a Novel Standard Deviation Weighted Distance Measure by Ahmed Husham Mohammed, Marwan Abdul Hameed Ashour

“…The aim of this paper is to present a new approach to address the Fuzzy C Mean algorithm, which is considered one of the most important and famous algorithms that addressed the phenomenon of uncertainty in forming clusters according to the overlap ratios. …”
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Clustering and Detecting Network Intrusion Based on Fuzzy Algorithms by Manar Kashmola, Bayda Khaleel

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Using the Hopfield– Fuzzy C Means Algorithm for Clustering of People based on Food Insecurity and Obesity in the Northwest of Iran by Helda Tutunchi, Alireza Ostadrahimi, Soltanali Mahboob, Reza Mahdavi, SIROUS J Tabrizi

“…Finally, it tests the validity of the suggested model with comparing by other models (Hopfield–K-Means, K-Means, and fuzzy C Means). @JASEM Keywords: Learning, Clustering, Algorithm, Hopfield J. …”
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Fuzzy clustering method based on genetic algorithm in intrusion detection study by HUANG Min-ming LIN Bo-gang

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Optimasi Fuzzy C-Means dan K-Means Menggunakan Algoritma Genetika untuk Pengklasteran Dataset Diabetic Retinopathy by Muhammad Ezar Al Rivan, Steven Steven, William Tanzil

“…Based on the comparison of Genetic Algorithm  Fuzzy C-Means and Genetic Algorithm K-Means iterations, it can be concluded that Genetic Algorithm Fuzzy C-Means has a better number of iteration than Genetic Algorithm K-Means. …”
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An intelligent hybrid approach combining fuzzy C-means and the sperm whale algorithm for cyber attack detection in IoT networks by E. I. Elsedimy, Sara M. M. AboHashish

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Grading of Traffic Interruptions in Highways to Tibet Based on the Entropy Weight-TOPSIS Method and Fuzzy C-Means Clustering Algorithm by Jian Tian, Zhiqiang Li, Suyan Zhuang, Jianfeng Xi, Min Li

“…The work proposed a model that integrated the entropy weight-TOPSIS method with the fuzzy C-means clustering algorithm to discuss the causes and characteristics of traffic interruptions on the four main highways to Tibet. …”
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