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136 articles for “cluster analysis”
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Research Survey of Data Mining with Processing in Different fields for Next Research Directions
Abstract: Data mining (DM) is a method used for mines the different category of related data in different research fields. This is a set of different techniques like classification, clustering, prediction, outlier analysis; decision making, regression etc used for gain the knowledge for intelligence computing. In this review, explain the different research papers, architecture with components of DM, processing of DM and applications of DM in various fields for next research …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 2, 2020 · pp. 5–9 Read article
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An Approach for Travel Pattern Analysis Using HDBSCAN and Apriori Algorithms
Abstract: Most mega-city regions around the world are suffering from an ongoing increase in the number of commuting trips. Understanding commuting patterns is crucial for both public and authority planners. The understanding of travel patterns helps passengers to know about the places and the time where they could get vacant transport and also helps authority planners in laying out a new transport service. The traditional way of understanding travel patterns includes …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 2, 2023 · pp. 1–9 Read article
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Geospatial Representation of Interdecadal Temperature Variations over Parts of Andhra Pradesh, India using Geographic Information Systems
Abstract: Climate change is one of the holistic phenomena experienced by human beings since recent decades. Keeping the view of several other hydrometerological factors, this paper emphasizes the application of geographic information systems to represent temperature variations observed over parts of Andhra Pradesh, India. Spatio-temporal representation of thermal variations was presented using cluster and outlier analysis over GIS platform. For this purpose hot spot analysis was conducted for 1951 to 1990. …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 4, Issue 2, 2014 · pp. 10–13 Read article
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Computational Analysis of Microarray Gene Expression Profiling in Leishmania donovani and Leishmania major
Abstract: Leishmaniasis is one of the most deadly diseases in which the human genes are affected and gets altered expression. The genes of Leishmania species which are responsible for causing leishmaniasis are not known yet. The objective behind this study is to know about the genes which are differentially expressed (DE) when macrophage of mice is infected with Leishmania donovani and Leishmania major. It also aims to know the similarities of …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 1, Issue 1, 2014 · pp. 1–14 Read article
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Identification of Thyroid Disease Severity using Fuzzy C-Means
Abstract: Clustering is a primary data description method in data mining which group’s most similar data. Data clustering is one of the important problems in the fields of data mining, bio-informatics and pattern recognition. Various algorithms are used to solve this problem. This paper presents the performance analysis of k-means clustering algorithm and compares it with fuzzy C- Means (FCM) algorithm on Thyroid disease data set. We also find the accuracy …
Published in Journal of Advanced Database Management & Systems · Vol. 1, Issue 1, 2014 · pp. 13–19 Read article
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Survey of Techniques for Clustering and Classification of ECG using WEKA
Abstract: ECG analysis can be done for automatic detection of abnormality in cardiac activity. This can be helpful in generating alert for saving a precious life. Various techniques have been proposed in literature for feature detection and classification such as; fuzzy logic methods, artificial neural networks (ANN), and support vector machines (SVM), wavelet transform, Hilbert transform, etc. Recently, numerous researches and techniques have been developed for analyzing the ECG signal on …
Published in Journal of Microcontroller Engineering and Applications · Vol. 3, Issue 2, 2016 · pp. 14–19 Read article
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A Qualitative Study on the Lived Experiences of Women with Polycystic Ovary Syndrome Attending Gynecology OPD, Bangalore
Abstract: Polycystic ovary syndrome (PCOS) is a prevalent hormonal disorder among women of reproductive age, affecting multiple aspects of their well-being, including physical, psychological, emotional, social, and spiritual dimensions. Despite its widespread occurrence, the lived experiences of women with PCOS remain inadequately understood. The present qualitative study aimed to explore and interpret these lived experiences to enhance professional awareness, improve understanding, and promote better support for affected women. A phenomenological research …
Published in International Journal of Midwifery Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 30–40 Read article
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Clustering Categorical Data Using Node Importance Method
Abstract: Normal 0 false false false EN-US X-NONE X-NONE Data clustering is an important technique in data analysis. It can be defined as a given set of data objects, the problem of clustering is to partition data objects into groups in such a way that objects in same group are similar and objects in different groups are dissimilar according to the predefined similarity measurement [Han Jiawei and Kamber Micheline. Data mining: …
Published in Current Trends in Information Technology · Vol. 1, Issue 2-3, 2011 Read article
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Fractional Riemannian Fuzzy C-Means with Time-Series Regularization for Economic Manifold Forecasting
Abstract: A fractional Riemannian fuzzy c-means framework is proposed for uncertain economic forecasting on non-Euclidean data domains. Observations are represented on a Riemannian manifold, cluster centres are intrinsic prototypes, and a latent fuzzy regime signal is regularised by both autoregressive and fractional-memory penalties. The resulting objective couples geometric clustering with time-series consistency, thereby discouraging partitions that are locally plausible but temporally incoherent. Closed-form membership updates, exponential-map centre updates, normal equations for …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 49–55 Read article
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Recent Advances in Polymer Analysis and Characterization Techniques for High-Performance Materials
Abstract: Polymers play a vital role in various fields, from biomedical engineering to energy storage. Developing high-performance polymers requires a deep understanding of their structure, properties, and behavior. This review paper delves into recent advancements in polymer analysis and characterization techniques. This paper is a comprehensive bibliometric analysis which investigates the research landscape of geopolymer concrete incorporating construction and demolition waste (CDW) by analyzing 389 publications from the Web of Science …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 76–93 Read article
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Language Independent Emotion Quantification using Non-linear Modelling of Speech
Abstract: Abstract: At present, emotion extraction from speech is a very important issue due to its diverse applications. Hence, it becomes absolutely necessary to obtain models that take into consideration the speaking styles of a person, vocal tract information, timbral qualities and other congenital information regarding his voice. Our speech production system is a nonlinear system like most other real-world systems. Hence, the need arises for modeling our speech information using …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 3, 2019 · pp. 24–30 Read article
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Study on High Rise (G+32) Cluster Shaped Building Under Earthquake with the help of IS 1893, UBC-97 and ASCE 7-10 codal provisions
Abstract: Modern high-rises, in low seismicity areas, are designed to withstand lateral loads.While high rise buildings would suffer structural damage, the shaking produced by the earthquake is a long period of slow shaking.The stability and stiffness of any structure is the major issue of concern in any high-rise buildings.This research is related to comparison of high rise G+32 cluster shape building under Seismic area with the help of different country codes …
Published in Recent Trends in Civil Engineering & Technology · Vol. 10, Issue 3, 2020 · pp. 24–33 Read article
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Multivariate Analysis of The Determinants of Undernutrition in Under-Five Children In Zimbabwe
Abstract: Background: Undernutrition is one of the leading causes of infant mortality in developing countries including Zimbabwe. The main objective for the study was to model the relationship between undernutrition and individual, household and community level determinants. Material and methods: Secondary data analysis of the 2019 Multiple Indicator Cluster Survey (MICS) was performed using the merged children and household datasets. A total of 6223 children’s data was used for the study. …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 9, Issue 3, 2022 · pp. 9–19 Read article
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A Comparative Analysis of Different Routing Protocols in WSN
Abstract: Wireless sensor network (WSN) consists of small sized sensor nodes that collects the data and sends to base terminal. The important issue in the field of WSN is the power supply by the batteries and routing protocol planning and engineering. The basic aim of these protocols is to reduce the energy consumption. In the present paper different routing protocols like Geographic and Energy Aware Routing (GEAR), Hybrid Energy Efficient Distributed …
Published in Recent Trends in Parallel Computing · Vol. 5, Issue 2, 2018 · pp. 7–12 Read article
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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Relationship Between Conceptual Load and Output in Children with Learning Disability
Abstract: Discourse analysis is a term given to a cluster of approaches intended in measuring the output with reference to the output measured on verbal, written or sign language. The output can be measured in terms of C units, T units etc. The output derived would be directly related to the conceptual output. The conceptual unit also reflects the relationship shared by the conceptual load and verbal output. Discourse analysis is …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 8, Issue 1, 2018 · pp. 1–5 Read article
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A PCA Based K-Means Clustering Algorithm for Wireless Sensor Nodes
Abstract: This paper presents a novel and improved approach for K-Means Clustering of wireless sensor networks, by using Principal Component Analysis for data reduction on the raw data. A wireless sensor network consisting of 100 nodes is classified into three different clusters using PCA based K-Means Algorithm. Davies-Bouldin Index is used as a parameter to check the effectiveness of the clustering algorithm. Experimental results demonstrate that the PCA based K-Means Algorithm …
Published in Journal of Web Engineering & Technology · Vol. 2, Issue 2, 2015 · pp. 6–10 Read article
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A Novel Clustering Techniques Evaluation using Monte Carlo Simulation
Abstract: In Machine Learning clustering is one the most significant method. Today, we have data in rich from many sources but in order to get meaningful information from it is very boring task. Machine learning clustering algorithms to create cluster to decode the meaningful information from the data, this analysis approach has gained much popularity in recent years. This paper explores evaluation performance of frequently used existing clustering techniques such as …
Published in Research & Reviews : Journal of Statistics · Vol. 10, Issue 3, 2021 · pp. 1–23 Read article
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Compact Method for Analyzing Big Data
Abstract: Big Data Analysis (BDA) method is proposed in this paper. A compact method (K-Means Cluster, Generalised K-Means Cluster, C-Means, Fuzzy Means, Fuzzy Numbers, Fuzzy Set, Fuzzy Logic, Neural Network, Genetic Algorithm) based big data analysis is presented in this paper. There are four models are presented as, probabilistic model, possibility model, fuzzy model and variance model. A compact algorithm is illustrated also in this paper.Keywords: Big Data, K-Means Cluster, Generalised …
Published in Journal of Advanced Database Management & Systems · Vol. 7, Issue 2, 2020 · pp. 5–14 Read article
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Big Data Management: Theory & Practice
Abstract: In this paper, Big Data Management is studied. There is finite number of information in Big Data and correspondingly its method of analysis exists. Big Data Analysis (BDA) method is proposed in this paper. A compact method (K-Means Cluster, Generalised K-Means Cluster, C-Means, Fuzzy Means, Fuzzy Numbers, Fuzzy Set, Fuzzy Logic, Neural Network, Genetic Algorithm) based big data analysis is presented in this paper. There are four models are presented …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 7, Issue 2, 2020 · pp. 13–22 Read article