Search Results - (( variable implementation clustering algorithm ) OR ( java application tree algorithm ))
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A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
Published 2014“…Next, we also optimize the fuzzification variable, m in FCM algorithm in order to improve the clustering performance. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Mining Sequential Patterns using I-PrefixSpan
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Adaptive neuro-fuzzy model with fuzzy clustering for nonlinear prediction and control
Published 2014“…Nonlinear systems have more complex manner and profoundness than linear systems.Thus, their analyses are much more difficult.This paper presents the use of neuro-fuzzy networks as means of implementing algorithms suitable for nonlinear black-box prediction and control.In engineering applications, two attractive tools have emerged recently.These two attractive tools are: the artificial neural networks and the fuzzy logic system. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…The research implements stock prediction analysis as a case study for training the neural network by adopting MGWO algorithm. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction
Published 2023“…The existing research in traffic speed prediction used LSTM with single variable (traffic speed) and multi variables (traffic speed and vehicle headway). …”
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Classification and prediction analysis for weld bead surface quality using feature extraction and mahalanobis-taguchi system
Published 2025“…The results reveal that while the K-means clustering method outperforms the Variable Bin Width method across several performance metrics, including an accuracy of 86.36% and a high specificity of 94.5%, the method’s recall rate of 50.49% indicates room for improvement in identifying true positives. …”
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