Search Results - (( java implementation tree algorithm ) OR ( knowledge operation clustering algorithm ))

Adaptive firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim

“…As search engine operates on Internet content that is constantly being updated, there is a need for a clustering algorithm that offers automatic grouping of items without prior knowledge on the collection. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…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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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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Determining number of clusters using firefly algorithm with cluster merging for text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…Such a scenario requires a dynamic text clustering method that operates without initial knowledge on a data collection.In this paper, a dynamic text clustering that utilizes Firefly algorithm is introduced.The proposed, aFAmerge, clustering algorithm automatically groups text documents into the appropriate number of clusters based on the behavior of firefly and cluster merging process. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

“…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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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Regionalization by fuzzy expert system based approach optimized by genetic algorithm. by Chavoshi, Sattar, Sulaiman, Wan Nor Azmin, Saghafian, Bahram, Sulaiman, Md. Nasir, Abd Manaf, Latifah

“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning by Noor, Ubair, Hassan, Raini, Dwi Handayani, Dini Oktarina

“…The implemented algorithm to perform such operation was far more efficient, faster and accurate as compared to conventional methods. …”
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Chaotic mutation immune evolutionary programming for photovoltaic planning in power system / Sharifah Azma Syed Mustaffa by Syed Mustaffa, Sharifah Azma

“…The knowledge contributions from this study would be beneficial to power system operators and planners for future offline development and expansion of their system…”
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Fruity vegetable recognition system using Color Histogram and BRISK features extraction / Siti Hajar Mohd Nasri by Mohd Nasri, Siti Hajar

“…In process to extract the two main features, K-means clustering algorithm is used as background subtraction method with combination of Canny’s Edge Detection and Mathematical Morphology Operation for shape extraction. …”
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Using ideal time horizon for energy cost determination by Hasan, Raed Abdulkareem, Abdulwahid, Hadeel W., Abdalzahra, Arwa Sahib

“…The activities implemented by this policy are (a) to relocate the VM from an encumbered server, a server that operates in an undesirably high regime with applications forecasted to rise their burdens to compute in the subsequent reallocation cycles; (b) to conduct VM migration from servers that operate within the undesirable regime to shift the server to a SLEEP mode; (c) putting an idle server to SLEEP mode and rebooting the servers from the SLEEP mode at high cluster loads. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

“…Such approach is highly dependable on the clustering algorithm parameterization, and is not capable to deal with the normal system’s specification changes. …”
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A framework for automatic modelling of survival using fuzzy inference. by Hamdan, Hazlina, Garibaldi, Jonathan M.

“…In this framework, alternative methods of partitioning the input space can be selected to define the membership functions, for example by using expert knowledge, equalizer partitioning, fuzzy c-means clustering, or the combination of these techniques. …”
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