Article
Computer Science, Artificial Intelligence
Yongxuan Lai, Songyao He, Zhijie Lin, Fan Yang, Qifeng Zhou, Xiaofang Zhou
Summary: This article proposes a new framework that generates base partitions in an unsupervised manner and assigns different weights to each cluster of the base partitions. The weighted co-association matrix based consensus approach is then applied to achieve a final partition. Empirical results show that the new framework retains high accuracy, adaptability, and robustness.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2021)
Article
Computer Science, Information Systems
Ali Idrus, Nafan Tarihoran, Ucup Supriatna, Ahmad Tohir, Suwarni Suwarni, Robbi Rahim
Summary: The purpose of this research is to analyze the clustering results obtained through clustering method measures to determine the connections between existing clusters. Different measurement methods were used and the average DBI values were calculated using the Davies Bouldin Index. The measurement method with the best DBI value was identified through the analysis of the results.
TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Shuyin Xia, Daowan Peng, Deyu Meng, Changqing Zhang, Guoyin Wang, Elisabeth Giem, Wei Wei, Zizhong Chen
Summary: This paper presents a novel accelerated exact k-means algorithm called Ball k-means, which uses a ball to describe each cluster. The algorithm focuses on reducing the point-centroid distance computation by finding neighbor clusters for each cluster. It divides each cluster into stable and active areas, with the latter further divided into annular areas. The points in the stable area remain unchanged, while the points in each annular area are adjusted among a few neighbor clusters. The Ball k-means achieves higher performance and requires fewer distance calculations compared to other state-of-the-art accelerated exact bounded methods, making it a versatile replacement for the naive k-means algorithm.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Automation & Control Systems
Chang Fan, Zhao Zhang, Dinghua Zhang, Ming Luo
Summary: This paper proposes a novel evolutionary cluster analysis method to analyze the evolution of tool wear in nickel-based superalloy GH4169, and establishes a more accurate tool wear model.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Environmental Sciences
Marisela Uzcategui-Salazar, Javier Lillo
Summary: This research proposed a new methodology to eliminate subjectivity in evaluating the vulnerability to contamination of aquifers using K-means cluster analysis and PCA technique. The results showed that the joint application of PCA and K-means analysis improved the assessment of groundwater vulnerability in detrital aquifers compared to traditional methods.
ENVIRONMENTAL EARTH SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Xinwang Liu
Summary: The newly proposed localized simple multiple kernel k-means (SimpleMKKM) provides an elegant clustering framework that considers the potential variation among samples. However, it requires pre-specifying an extra hyperparameter, limiting its practical applications. To overcome this issue, a hyperparameter-free localized SimpleMKKM is proposed, which jointly learns the optimal coefficient of neighborhood mask matrices together with the clustering tasks. The obtained optimum is proved to be the global one, and comprehensive experimental studies verify its effectiveness.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Tianjiao Ni, Minghao Qiao, Zhili Chen, Shun Zhang, Hong Zhong
Summary: The paper introduces a novel differentially private k-means clustering algorithm, DP-KCCM, which improves the utility of clustering significantly by adding adaptive noise and merging clusters. The algorithm first generates initial centroids, adds adaptive noise, and further improves the utility by merging clusters.
Article
Automation & Control Systems
Sugiyarto Surono, Rizki Desia Arindra Putri
Summary: This study utilized a new method that combined Minkowski and Chebyshev distances, PCA for dimensional reduction, and FCM for clustering to minimize the objective function of FCM. The results showed that the combination of PCA and FCMMC algorithms achieved a cluster accuracy of 1.6468, with the smallest objective function value of 0.0373 obtained in the 15th iteration out of 100 maximum iterations.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Shishir Gaur, K. Srinivasa Raju, D. Nagesh Kumar, Mayank Bajpai
Summary: The study applied an Analytic Element Method (AEM) simulation model and a Non-dominated Sorting Genetic Algorithm (NSGA-II) optimization model to address groundwater planning issues in a part of the Dore river catchment in France, considering three objectives: maximizing discharge, minimizing pumping cost, and minimizing piping cost. A total of 2105 non-dominated groundwater planning strategies were generated and were classified into 20 clusters using K-Means cluster analysis and Davies-Bouldin index. Multicriterion Decision-Making (MCDM) techniques like VIKOR and TOPSIS were employed to rank these strategies, with a sensitivity analysis showing changes in ranking pattern for different values of a parameter v but the top-ranking strategy remaining unchanged as A5.
JOURNAL OF HYDROINFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Merhad Ay, Lale Ozbakir, Sinem Kulluk, Burak Guelmez, Gueney Oztuerk, Sertay Ozer
Summary: Clustering is a data mining method that divides large-sized data into subgroups based on similarities. The FC-Kmeans algorithm, proposed in this paper, allows clustering by fixing some cluster centers while considering real conditions. Experimental results show that although the FC-Kmeans algorithm has more limitations, it performs similarly to the K-means algorithm in terms of performance indicators.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Civil
Majid Vali, Mohammad Zare, Saman Razavi
Summary: This study introduces a novel 'local surrogate modelling' framework guided by automatic clustering for solving computationally intensive groundwater remediation optimization problems. Results show that the proposed automatic clustering-based local surrogate modeling is effective and reliable while reducing at least 60 percent of the computational burden.
JOURNAL OF HYDROLOGY
(2021)
Article
Construction & Building Technology
Qian Huang, Shengyang Chen, Ya Li
Summary: Automatic selection of analysis windows is crucial in conducting accurate HVSR investigations in urban areas. A procedure utilizing K-means cluster analysis is proposed to achieve this goal. Through comparing K-means and hierarchical clustering methods, the characteristics of spectral ratio curves generated by anthropogenic sources (EHVSR) and site information (SHVSR) were examined. An automatic procedure for selecting SHVSR curves using K-means was presented and applied to 24 sites, where the results showed close proximity between SHVSR curve and site transfer function.
CASE STUDIES IN CONSTRUCTION MATERIALS
(2023)
Article
Computer Science, Information Systems
Yudhistira Arie Wijaya, Dedy Achmad Kurniady, Eddy Setyanto, Wahdan Sanur Tarihoran, Dadan Rusmana, Robbi Rahim
Summary: The research aims to optimize clustering results using DBI. The data used includes the number of villages with school facilities and the level of education obtained from the government website. Through the use of k-means, it was found that over 90% of villages still have school facilities, especially at the high school and vocational high school levels.
TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Chonghui Guo, Mucan Liu, Menglin Lu
Summary: This research proposes a Dynamic Ensemble Learning Algorithm based on K-means sampling and distance-based dynamic ensemble to overcome the limitations of traditional scoring systems and classical ensemble models in ICU mortality prediction. Experimental results demonstrate the outstanding performance of the proposed algorithm in most mortality prediction tasks.
APPLIED SOFT COMPUTING
(2021)
Article
Geosciences, Multidisciplinary
Anja Katzenberger, Anders Levermann, Jacob Schewe, Julia Pongratz
Summary: Excessive rainfall during the summer monsoon seasons in the Indian subcontinent has caused widespread floods and landslides. The latest climate models indicate that these intense rainfall seasons will become more frequent in the future, with efforts to mitigate climate change having a significant impact. Moreover, the number of heavy rainfall days and the shift towards moderate or heavy rainfall is projected to increase.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Computer Science, Artificial Intelligence
Sravana Kumar Bali, Suryakalavathi Munagala, Venkata Nagesh Kumar Gundavarapu
NEURAL COMPUTING & APPLICATIONS
(2019)
Article
Computer Science, Hardware & Architecture
K. V. R. Swathi, G. V. Nagesh Kumar
COMPUTERS & ELECTRICAL ENGINEERING
(2019)
Article
Energy & Fuels
M. Rambabu, G. V. Nagesh Kumar, S. Sivanagaraju
Article
Engineering, Electrical & Electronic
Janaki Pakalapati, Karthick Nagaraj, Gundavarapu Venkata Nagesh Kumar
JOURNAL OF ELECTROMAGNETIC WAVES AND APPLICATIONS
(2020)
Article
Engineering, Electrical & Electronic
P. Janaki, N. Karthick, G. V. Nagesh Kumar
Summary: In the operation of three-phase gas-insulated busducts (GIB), the establishment of supporting insulators is crucial for reducing electric field stress. Insulator failures in GIB can result in uneven electric field distribution and significant economic loss.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Polamraju V. S. Sobhan, Janaki Pakalapati, Venkata Nagesh Kumar Gundavarapu, Deepak Chowdary Duvvada, Sravana Kumar Bali
Summary: This paper discusses the design of a Functionally Graded Material (FGM) spacer for a three-phase Gas Insulated Busduct (GIB) to minimize electric field stress by increasing the number of gradings and inserting metal inserts (MI) at the end of the enclosure. By doping different permittivity values, functionally graded materials are spatially distributed with multiple filler materials to achieve uniform stress on the electric field. Simulation results show that the stress is minimized and an enhanced uniform field allocation along the surface is obtained with the use of MI.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2021)
Article
Energy & Fuels
Muppidi Rambabu, Gundavarapu VenkataNagesh Kumar, Bathina Venkateswara Rao, Bali Sravan Kumar
Summary: An improved optimization strategy based on Elephant Herd Optimization method is proposed to minimize the objective function related to uncertain optimum power flow (OPF) considering cost analysis. The method has been applied to IEEE 57 bus system to evaluate emissions, generation cost, losses, and voltage deviation, showing efficiency compared to standard methods.
ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
(2021)
Article
Engineering, Electrical & Electronic
Uma Maheswari Ramisetty, Sumanth Kumar Chennupati, Venkata Nagesh Kumar Gundavarapu
Summary: The design and optimization of training sequences is crucial for enhancing the capacity and performance of multi user-multi-input and multi-output (MU-MIMO) systems. By reducing the sensing matrix through training sequence design and sparse channel estimation, the system's capacity and efficiency can be improved.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2021)
Article
Engineering, Multidisciplinary
Akanksha Mishra, Nagesh Kumar Gundavarapu Venkata, Sravana Kumar Bali, Venkateswara Rao Bathina, Uma Maheswari Ramisetty, Srikanth Gollapudi, Hady Habib Fayek, Eugen Rusu
Summary: This paper proposes an effective method for the placement of solar power units and Interline Power Flow Controllers (IPFC) to improve the reliability of power systems. The Firefly algorithm is used to optimize the placement, and the impact of the configuration on power systems is analyzed using Indian and IEEE bus systems.
Article
Automation & Control Systems
Pulivarthi Nageswara Rao, Ramesh Devarapalli, Fausto Pedro Garcia Marquez, G. V. Nagesh Kumar, Behnam Mohammadi-Ivatloo
Summary: The Bearingless Switched Reluctance Motor (BSRM) is a new technology motor that overcomes maintenance issues and lubrication requirements, improving output power and speed. However, torque ripple due to non-linearity and pole structures can cause vibrations and affect rotor safety. A sensorless control method is proposed to minimize torque ripple and achieve smooth operation without mechanical sensors, leading to a more efficient and robust system.
ARCHIVES OF CONTROL SCIENCES
(2021)
Article
Materials Science, Multidisciplinary
Janaki Pakalapati, Karthick Nagaraj, Venkata Nagesh Kumar Gundavarapu
Summary: This paper presents the design of a post type spacer with functionally graded material for a three phase gas insulated busduct (GIB), aiming to minimize electric field stress by inserting metal inserts. Simulation results demonstrate that inserting metal inserts can reduce the impact of particles of different sizes.
TRANSACTIONS ON ELECTRICAL AND ELECTRONIC MATERIALS
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Janaki Pakalapati, N. Karthick, G. V. Nagesh Kumar, Prasantha R. Mudimela
PROCEEDINGS OF 2020 6TH IEEE INTERNATIONAL WOMEN IN ENGINEERING (WIE) CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (WIECON-ECE 2020)
(2020)
Article
Engineering, Electrical & Electronic
Janaki Pakalapati, Venkata N. Kumar Gundavarapu, Deepak Chowdary Duvvada, Sravana Kumar Bali
INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS
(2020)
Article
Engineering, Multidisciplinary
Akanksha Mishra, G. V. Nagesh Kumar, Sravana Kumar Bali
WORLD JOURNAL OF ENGINEERING
(2020)
Article
Engineering, Multidisciplinary
Jagadeesh Adari, Venkata Siva Krishna Rao Gadi, Venkata Nagesh Kumar Gundavarapu
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
(2018)
