Search Results - (( java application classification algorithm ) OR ( using interactive pollination algorithm ))
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1
An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite
Published 2018“…Although useful, most of the aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. …”
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2
Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…Although useful, all aforementioned t-way strategies have assumed sequence-less interactions amongst input parameters. …”
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3
Hybrid flower pollination algorithm strategies for t-way test suite generation
Published 2018“…Consequently, many useful meta-heuristic algorithms have been developed on the basis of the implementation of t-way strategies (where t indicates the interaction strength). …”
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4
Test suite generation based on hybrid flower pollination algorithm and hill climbing
Published 2021“…In this research paper, we propose a new software t-way testing tool based on hybrid Flower Pollination Algorithm and Hill Climbing for generating test suite generation, called FPA-HC strategy can be used for generating smaller test suite size. …”
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5
Comparative Study of Adaptive Elitism and Mutation Operators in Flower Pollination Algorithm for Combinatorial Testing Problem
Published 2018“…Flower Pollination Algorithm (FPA) is one of the recent meta-heuristic algorithms for global optimization. …”
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Sequence and sequence-less T-way test suite generation strategy based on flower pollination algorithm
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Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…This system was mainly developing using java programming. Apache Tom cat was used as a server in order to run the application smoothly. …”
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8
Performance properties optimization of triaxial ceramic-palm oil fuel ash by employing Taguchi design and flower pollination algorithm
Published 2018“…Primarily, this research is about the optimization of triaxial ceramic employing the POFA process by the Taguchi design and Flower Pollination Algorithm (FPA). The recycled POFA was evaluated through the POFA layer formation method where selected POFA layers were employed as filler raw material. …”
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9
A Unified Strategy for Sequence and Sequence-less T-way Test Suite Generation
Published 2016“…Although useful, existing t-way strategies have assumed sequence-less interactions amongst input parameters. …”
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10
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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11
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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12
A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
Published 2012“…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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14
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The results reveal that the proposed hybrid algorithm is capable of achieving classification accuracy values of (95.82 % and 97.68 %), detection rates values of (95.8 % and 99.3 %) and false alarm rates values of (0.083 % and 0.045 %) on both KDD CUP 99 and NSL KDD. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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