Search Results - (( developing agent evolutionary algorithm ) OR ( java application tree algorithm ))
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Software testing optimization for large systems using agent-based and NSGA-II algorithms
Published 2023“…The proposed work is innovative because it applies an evolutionary multi-agent system (EMAS) and NSGA-II from various traditional evolutionary methods. …”
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Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List
Published 2023“…This paper presents an approach to solve the unit commitment problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority List optimisation technique (MAEP-PL). …”
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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman
Published 2013“…This research presents an approach to solve the UC problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority Listing optimisation technique (MAEP-PL). …”
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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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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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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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