Search Results - (( program solution clustering algorithm ) OR ( java applications tree algorithm ))
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Efficient genetic partitioning-around-medoid algorithm for clustering
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An integrated model of automated elementary programming feedback using assisted and recommendation approach
Published 2017“…Meanwhile, similar difficulty groups of the computer programs were generated using a K-Means clustering algorithm that was enhanced with ranking consideration. …”
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Enhancement of Ant System Algorithm for Course Timetabling Problem
Published 2009“…For this kind of problem, researchers believe that it will be better to find an approximate solution that can be delivered by a stochastic algorithm than waiting for an exact solution from the deterministic 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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Linear programming approach for scheduling sports league problems in Malaysia
Published 2017“…In order to solve the formulated LP model, we proposed several solution methods such as simplex and genetics algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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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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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata
Published 2018“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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A Framework for Green Energy Resources Identification and Integration Supported by Real-Time Monitoring, Control, and Automation Applications
Published 2025“…To address these challenges, a novel Geographical Information System-based fuzzy Technique for Order Preference by Similarity to Ideal Solution coupled with filtration algorithms was proposed. …”
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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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Conference or Workshop Item -
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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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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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Bottleneck-based heuristic for permutation flowshop scheduling
Published 2017“…There are four potential dominant machines (M1, M2, M3, M4) clustered as bottleneck machines. A total 1000 set random processing time for each job sizes was tested using Excel simple programming with built in Visual Basic for Application (VBA). …”
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4E analysis of a two-stage refrigeration system through surrogate models based on response surface methods and hybrid grey wolf optimizer
Published 2023“…Finally, the K-means clustering technique is applied for Pareto characterization. …”
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