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11 articles for “Fuzzy c-means”
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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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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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Fuzzy C-Means
Abstract: AbstractFuzzy c-means (FCM) incorporates spatial information into the membership function for clustering and uses it for obtaining the enhanced image. The main aim of the project is to develop a user friendly graphical user interface, manipulate and retrieve the data and run models for routing application in terrain trafficability. In the classification process, first clustering is done which involves grouping similar pixels (or forming clusters) in the test image based …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 3, 2015 · pp. 10–16 Read article
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Detection of Cancer using Machine Learning Algorithms
Abstract: Cancer is a group of diseases characterized by uncontrolled growth and spread of abnormal cells. There are over 100 types of cancer. And any part of the body can be affected. Cancer has become 2nd leading cause of death. Some hospitals offer cancer screening tests; the test results need to be evaluated by an oncologist. The cancer screening test are very expensive and not available in all of the hospital. …
Published in Trends in Machine design · Vol. 7, Issue 3, 2020 · pp. 9–16 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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Reduction of Harmonics for Isolated Diesel Generation System with DSTATCOM Using Fuzzy
Abstract: This paper presents the compensation of reactive power, harmonics, and unbalanced load current of diesel generator set for an isolated system by controlling voltage source convertor (VSC) which is working as distribution static synchronous compensator (DSTATCOM). Here least mean square based adaptive linear element (ADALINE) is use to extract balanced positive sequence real fundamental frequency component of the load current for converter and used to control DSTATCOM. For fast dynamic …
Published in Journal of Automobile Engineering and Applications · Vol. 2, Issue 3, 2015 · pp. 12–22 Read article
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Unveiling Patterns in Complexity: The Role of Simple Statistics and Fuzzy Mathematics in Data Analysis
Abstract: In this study, statistical methods must be integrated with fuzzy mathematics to solve complex data. Statistical methods offer clear, unbiased, and computationally feasible tools for analysing numerical data. whereas fuzzy mathematics excels in describing the vagueness and ambiguity of human feeling by way of linguistic variables, membership functions, and inference systems. Giving it an apparent advantage when modelling complex conditions. Hybrid frameworks offer fine-grained decision-making and resilient adaptability to real-world …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 1, 2025 · pp. 01–10 Read article
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Image Processing Techniques for Detecting and Classification of Leaf Diseases
Abstract: Plants are the way to make a living. From the factors of our daily life to breathing we are totally dependent on plants. Therefore, plant care must be proper. Plant diseases involve, of instance, algae, bacteria, and viruses. Several researchers have to classify plant diseases but it is time consuming to manually identify them. Image processing techniques are used to detect various diseases of the plant. There are several steps …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 2, 2021 · pp. 1–6 Read article
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Health Assessment of Oil Immersed Transformer Using Fuzzy Logic
Abstract: A transformer is an electrical device that transfers energy between two or more circuits through electromagnetic induction. Commonly, transformers are used to increase or decrease the voltages of alternating current in electric power applications. Mineral oil treats heart of the transformer, its functions are to insulate, suppress corona and arcing, and to serve as a coolant. The oil helps cool the transformer. Because it also provides part of the electrical …
Published in Trends in Electrical Engineering · Vol. 5, Issue 3, 2015 · pp. 6–16 Read article
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Short-Term Load Demand Forecasting using Chaos Theory and ANFIS
Abstract: In the electrical power sector, forecasting of load demand is an important process for effective planning of future expansion and periodical operations including unit commitments, fuel scheduling, short-term maintenance, security assessments, reducing spinning reserve, reliability analysis etc. Accurate load predictions are also necessary to utilize the electrical energy efficiently and to minimize the conflicts between the demand and supply of electricity. As electric load pattern of a region is very …
Published in Trends in Electrical Engineering · Vol. 6, Issue 2, 2016 · pp. 50–57 Read article