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128 articles for “clustering algorithms”
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Radial Basis Function Neural Networks for Rainfall-Runoff Modeling
Abstract: Rainfall-runoff process is purely nonlinear and varies spatially as well as temporally. Any hydrological model requires many parameters which represent different components of the process. Availability of all the parameters is difficult for any catchment and probabilistic generation of such type of data is impossible. Under such circumstances, artificial neural networks (ANNs) have proven to be a better tool to model the rainfall-runoff process with minimum available data. The present …
Published in Journal of Water Resource Engineering and Management · Vol. 1, Issue 2, 2014 · pp. 11–18 Read article
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Relay Node Selection Based Reduced Energy Consumption in Heterogeneous Wireless Sensor Network
Abstract: Energy conserving optimization is of chief concern while scheming a wireless sensor network (WSN) as most of the sensor nodes are furnished with limited power supply. In this paper, we focus on minimizing energy consumption and maximizing network lifetime in three-tiered network architecture. For this obvious goal, clustering techniques are a boon with a hierarchical arrangement to boost the performance of the network as well as reduce the consumption of …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 3, Issue 2, 2016 · pp. 7–14 Read article
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A Latest Approach for Crime Rate Prediction and Analysis by Using the Clustering and Machine Learning Algorithm
Abstract: In our daily life, the collection and analysis of crime-related data is uncertain from a security perspective. Crime rate forecasting and analysis is a way of identifying and analyzing crime patterns in crime data contained in a crime database. Our system predicts what criminal activity occurs in everyday life in various parts of the world. Through the utilization of machine learning and data mining algorithms, it is possible to forecast …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 32–42 Read article
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A Clustering Based CPU Scheduling Algorithm for Real Time Systems
Abstract: CPU scheduling is a fundamental function of operating system. The performance and efficiency of multitasking operating systems mainly depend upon the uses of CPU scheduling algorithm. When an operating system wants to execute a process, it does not know the execution time it needs. After running, the exact execution time of that process would appear. Here we present a new scheduling approach using the Partitioning Around Medoid (PAM) clustering algorithm …
Published in Current Trends in Information Technology · Vol. 1, Issue 1, 2011 · pp. 1–7 Read article
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A Review on Heart Disease Monitoring System by Using Machine Learning
Abstract: Heart disease is one of the most popular diseases which can lead to reduce the lifespan of human beings now a day. Every year 17.5 million people are get dying due to heart disease. Researchers have been using various types of data mining techniques and machine learning algorithms to help in the diagnosis of heart disease and various other type of diseases. Health care Centre collects large amount of data. …
Published in Recent Trends in Programming languages · Vol. 7, Issue 1, 2020 · pp. 1–6 Read article
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Performance Analysis of Hierarchical and Non Hierarchical Clustering Techniques
Abstract: Clustering is a procedure to organizing the objects in to groups or clustered together, based on the principle of minimizing the intra-class similarity. The various clustering algorithms are analyzed and compare the performance of clustering algorithms on aspect for validity indices to build the model. The aim is to judge the efficiency of different clustering techniques on wine dataset and determine the optimum algorithm. The results show that complete linkage …
Published in Research & Reviews : Journal of Statistics · Vol. 9, Issue 2, 2020 · pp. 54–71 Read article
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Adaptive Huffman Algorithm for Data Compression Using Text Clustering and Multiple Character Modification
Abstract: Adaptive Huffman algorithm is a popular data compression technique that creates a variable-length binary code for each symbol in a message. However, the original algorithm may not be efficient in compressing text data, particularly when dealing with long sequences of repeated characters. In this study, we propose a novel approach to enhance the compression ratio of the Adaptive Huffman algorithm by utilizing text clustering and multiple character modification. The proposed …
Published in Recent Trends in Programming languages · Vol. 10, Issue 1, 2023 · pp. 30–40 Read article
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Customer Segmentation for Enhancing Customer Centric Business
Abstract: Customer segmentation is grouping customers based on similarities so companies can approach each group for marketing effectively and appropriately. Customer segmentation is important for enhancing customer centric business for gaining retention among customers by campaigning them using better marketing strategies, causing more institutional benefit. This paper segments customers by analyzing their characteristics based on both demographic and behavioral attributes using K-Means clustering algorithm and Self-Organizing Maps (SOM). K-Means is a …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 1, 2021 · pp. 17–31 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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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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Energy Efficient Data Aggregation of Heterogeneous Network using Metaheuristic Approach
Abstract: The development of wireless sensor network results in faster technological development and its fundamental problem of network life time in the given energy constraints leads to several research study and its optimization. Sensor networks revolutionize the paradigm of collecting and processing information from diverse environments. In this paper proposed the distributed clustering optimization to determine the better network performance using the meta-heuristic approach based on Improved Harmony Search Algorithm (IHSA) …
Published in Recent Trends in Sensor Research & Technology · Vol. 1, Issue 1, 2014 · pp. 8–15 Read article
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Comparative Analysis of Proposed FCM Clustering Integrated Enhanced Firefly-Optimized Algorithm (En-FAOFCM) for MR Image Segmentation and Performance Evaluation
Abstract: Image segmentation has a significant responsibility in diagnosis and treatment of diseases. To scan patients and determine the severity of certain injuries in hospitals, magnetic resonance imaging (MRI) method is normally used. This paper emphasizes on comparative study of segmentation techniques for segmenting MRI brain images. In this regard, to group the pixels of images in the intensity space, unsupervised clustering techniques are used. Here enhanced firefly algorithm is used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 1, 2016 · pp. 32–44 Read article
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Q-Metrics for Early Detection of Cervical Cancer
Abstract: The most prevalent form of cancer in women worldwide is uterine cervical cancer. Through screening programs aimed at detecting precancerous lesions most cases of cervical cancer can be prevented. In this article, Q-metrics has been proposed for carrying out automated image segmentation of uterine cervical cancer. The validation of detection of cervical lesions is an important issue in medical image processing because it has a specific impact on surgical planning. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 26–30 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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An Analysis into the Issues of Multi-Agent Data Mining
Abstract: Presently instructional establishments compile and store vast volumes of information like student enrollment and attending records, moreover as their examination results. Mining such knowledge yields stimulating info that serves its handlers well. Ascension in instructional knowledge points to the very fact that distilling huge amounts of information needs an additional subtle set of algorithms. This issue led to the emergence of the sphere of Educational Data Mining (EDM). Ancient data …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 3, 2018 · pp. 1–4 Read article
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Bandwidth Management in WSN Through Discrete Fourier Transform
Abstract: In wireless sensor network, bandwidth and energy is the major consideration. In WSN, there are various protocols and management techniques which are involved in the bandwidth utilization and minimization of energy used in the data communication. The most common problem in WSN is of traffic congestion which results in loss of packets hence wastage of bandwidth and energy used to transfer the data is also increased. The technique discussed in …
Published in Recent Trends in Sensor Research & Technology · Vol. 1, Issue 3, 2014 · pp. 17–24 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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COMPARISION OF DIFFERENT ROUTING PROTOCOLS IN WSN
Abstract: Wireless sensor network is designed on the basis of increase of their lifetime and conservation of the available energy in each sensor node. A number of routing algorithm is designed for WSN but clustering algorithm gains a lot of importance because the energy distribution throughout the network is equal. The comparison of different routing protocols performance is done i.e LEACH ,TEEN,SEP and EAMMH on the behalf of different factors and …
Published in Journal of Advances in Shell Programming · Vol. 5, Issue 1, 2018 · pp. 26–35 Read article
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Energy efficiency improvement in LEACH protocol for wireless sensor network
Abstract: The biggest reason for reduction of energy in the wireless sensor network is the communication. Nearly 70% of sensor node energy is used in the transmission of data. Efficient usage of energy in sensor node is a desirable method to improve the life time of WSN. In order to improve the lifetime of the network energy efficient routing protocols should be designed. In this paper I will discuss about(LEACH) which …
Published in Journal Of Network security · Vol. 8, Issue 2, 2020 · pp. 16–23 Read article
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CHROMAWEAR: An AI Assisted Personalized Fashion Design Recommender System for Diverse Skin Tones to Enhance Fashion Choices
Abstract: In the age of fashion, we receive the same question every day: What should I wear today to look nice? The fashion industry is always changing, welcoming inclusivity and diversity. Still, despite the advancements, there are difficulties meeting people's varied needs, especially with regard to skin tone. This research work presents a personalized fashion design recommender system with artificial intelligence support to improve the fashion choices of people with different …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 49–58 Read article