Link stability - based optimal routing path for efficient data communication in MANET by Renisha Pulinchuvallil Salim, Rajesh Ramachandran

“…Subsequently, the Canberra-based K Means (C-K Means) algorithm is employed to identify Neighboring Nodes (NNs), which are pivotal for creating communication links within the network. …”
Get full text

Comprehensive analysis of total knee arthroplasty kinematics and functional recovery: Exploring full-body gait deviations in patients with knee osteoarthritis. by Xavier Gasparutto, Alice Bonnefoy-Mazure, Michael Attias, Katia Turcot, Stéphane Armand, Hermès H Miozzari

“…Patients were clustered by applying K-means algorithms on full-body kinematic features of gait before surgery. …”
Get full text

FUZZY GEOGRAPHICALLY WEIGHTED CLUSTERING WITH OPTIMIZATION ALGORITHMS FOR SOCIAL VULNERABILITY ANALYSIS IN JAVA ISLAND by Alwan Fadlurohman, Tiani Wahyu Utami, Setiawan Amrullah, Nila Ayu Nur Roosyidah, Oktaviana Rahma Dhani

“…FGWC is an extension of the Fuzzy C-Means algorithm, which involves geographical influences in calculating membership values. …”
Get full text

A Study on Spatial and Temporal Changes and Synergies/Trade-Offs of the Production-Living-Ecological Functions in Mountainous Areas Based on the Niche Width Model by Yaling Li, Ruoying Song, Ping Ren

“…Based on this, spatial clustering patterns were further analyzed using Maxwell’s triangle and K-means algorithms to delineate functional zones. Key findings include: (1) Production function (PF) and living function (LF) exhibit a “core-periphery” spatial pattern (high-value clusters in the south, low-value contiguous areas in the north), while ecological function (EF) displays a “high-low-high” ring-shaped pattern (high values in the northwest and southeast, declining in the central region due to development pressure); (2) synergy and trade-off relationships coexist in the study area. …”
Get full text

CPT-DF: Congestion Prediction on Toll-Gates Using Deep Learning and Fuzzy Evaluation for Freeway Network in China by Tongtong Shi, Ping Wang, Xudong Qi, Jiacheng Yang, Rui He, Jingwen Yang, Yu Han

“…The evaluation module is proposed based on these predicted results. Then, fuzzy C-means algorithm (FCM) is further modified by determining coupling weight for these two key indicators to detect congestion state. …”
Get full text

Use of X means and C4.5 algorithms on lateral cephalometric measurements to identify craniofacial patterns by Merve Gonca, Mehmet Birol Özel

“…Results A total of four clusters were obtained using the X-means algorithm. Decision trees were used to identify the most discriminative variables among clusters. …”
Get full text

CLUSTERING ANALYSIS FOR GROUPING SUB-DISTRICTS IN BOJONEGORO DISTRICT WITH THE K-MEANS METHOD WITH A VARIETY OF APPROACHES by Denny Nurdiansyah, Mochamad Nizar Palefi Ma'ady, Yuana Sukmawaty, Muchammad Chandra Cahyo Utomo, Tia Mutiani

“…In this case, data mining techniques can identify patterns and relationships in population data. The K-Means algorithm is a clustering technique that divides data into groups or clusters based on similar characteristics. …”
Get full text

ONLINE FUZZY CLUSTERING OF HIGH DIMENSION DATA STREAMS BASED ON NEURAL NETWORK ENSEMBLES by Yevgeniy Bodyanskiy, Iryna Perova, Polina Zhernova

“…The following results are obtained - the main idea of the proposed approach is based on a modification of the fuzzy C-means algorithm. To reduce the dimension of the input space, the modified Hebb-Sanger network is suggested to be used; this net is characterized by the increased speed and is built on the basis of the modified Oja neurons. …”
Get full text

Exploring Passengers’ Dependency Variety on Stations’ Functions in Urban Subway by Xia Zhao, Pengpeng Jiao, Yong Zhang, Chenjing Zhou

“…These features are clustered into 5 distinct levels via the k-means algorithm, before an inference of subway stations’ functions from 236,040 POI data sources via the LDA approach. …”
Get full text

Integrated Time Series Analysis, Clustering, and Forecasting for Energy Efficiency Optimization and Tariff Management by Anderson Jhones Passos Nascimento, Menaouar Berrehil El Kattel, Jose Antonio Fernandes de Macedo, Fernando Luiz Marcelo Antunes

“…The K-Means and Mini-Batch K-Means algorithms were used to segment consumer units based on contracted demand and average monthly consumption. …”
Get full text

Segmentation of Anterior and Posterior Chambers on UBM Images by Fuzzy Clustering by Yaru Yao, Xin Wang, Xinying You, Xueyan Liu

“…The UBM images are manually segmented using ImageJ software as the gold standard, while automatic segmentation employs six distinct methods: Otsu threshold, K-means, fuzzy C-means, robust self-sparse fuzzy clustering algorithm, spatial intuitionistic fuzzy C-means algorithm, and fast robust fuzzy C-means (FRFCM) algorithm. …”
Get full text

Clusters of patients with non-ST-segment elevation acute coronary syndrome depending on the laboratory data by D. N. Nedbaeva, V. S. Mikhaleva, E. A. Zolotova, O. V. Sirotkina, G. A. Kukharchik

“…As a statistical method, we performed сluster analysis by K-means algorithm.Results. We registered 18 adverse outcomes (myocardial infarction, unstable angina) during 6-month follow-up. …”
Get full text

Examining the interconnections among income, food prices, food insecurity, and health expenditure: a multicausality approach by Ahmet Murat Günal, Sevde Cantürk, Salim Yılmaz, Canser Boz, Derya Karabay

“…The augmented Dickey–Fuller test assessed stationarity, and optimal lag lengths were selected using the Akaike information criterion. We used the K-means algorithm for income group classification and the Wald test for comparing findings across groups, based on data from 99 countries. …”
Get full text

Enhancing DBSCAN Accuracy and Computational Efficiency Using Closest Access Point Pre-Clustering for Fingerprint-Based Localization by Abdulmalik Shehu Yaro, Filip Maly, Pavel Prazak

“…Furthermore, the CAP-DBSCAN algorithm demonstrates superior computational efficiency as a result of the CAP algorithm generating well-structured pre-clusters better than those generated by the k-means++ algorithm. This significantly reduces the computational burden of the cluster refinement process. …”
Get full text

Phenotyping of masked hypertension based on the clustering of 24-hour blood pressure monitoring data by B. I. Geltser, K. I. Shakhgeldyan, V. N. Kotelnikov, O. O. Vetrova, V. V. Orlova-Ilyinskaya, R. S. Karpov

“…The clustering of ABPM data was carried out using the Kohonen self-organizing neural networks and K-means algorithm. Data processing was performed in the R programming language using the RStudio environment.Results. …”
Get full text

Penerapan Metode K-Means Berbasis Jarak untuk Deteksi Kendaraan Bergerak by Yuslena Sari, Andreyan Rizky Baskara, Puguh Budi Prakoso

“…In this paper, the K-Means algorithm applies Euclidean distance, Manhattan distance, Canberra distance, Chebyshev distance and Braycurtis distance. …”
Get full text

Optimizing the Migratory Environment of Wildebeests in the Maasai Mara Reserve with a New Ecological Corridor and Customized Buffer Zone Model by Xinrui Fan, Kuok Ho Daniel Tang, Shoushuo Liu, Yang Liu, Charles Ken Smith

“…We then used a K-means algorithm (R² = 0.926) to fit coordinates representing the changes in the location of the wildebeests to enable a quantitative representation of their migration routes. …”
Get full text

Sex differences in alcohol use patterns and related harms: A mixed-methods, cross-sectional study of men and women in northern Tanzania. by Madeline McNee, Niveditha Badrinarayanan, Eleanor Strand, Thiago Augusto Hernandes Rocha, Timothy Antipas Peter, Yvonne Sawe, Anna Tupetz, Diego Galdino França, Judith Boshe, Joao Ricardo Nickenig Vissoci, Monica H Swahn, Blandina Mmbaga, Catherine Staton

“…Differences in scores by sex were assessed using unpaired t-tests. K-means algorithms were run independently in both samples. …”
Get full text

Habitat Analysis in Tumor Imaging: Advancing Precision Medicine Through Radiomic Subregion Segmentation by Wu LX, Ding N, Ji YD, Zhang YC, Li MJ, Shen JC, Hu HT, Jin L, Yin SN

“…By analyzing many literatures, the commonly used K-means algorithm and other algorithms such as hierarchical clustering and consensus clustering are summarized. …”
Get full text

Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

“…Furthermore, we compare the action selection between our Bayesian approach and non-Bayesian action clustering using K-Means algorithms, where our analysis highlights coherent clustering which indicates structure exploration, while non-Bayesian approach shows premature convergence to suboptimal policies.…”
Get full text