Search Results - (( developing pervasive learning algorithm ) OR ( java application force algorithm ))
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak
Published 2021“…A classifier model is developed using Naive Bayes characteristics. A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Dynamic force-directed graph with weighted nodes for scholar network visualization
Published 2022“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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LINGUISTIC FUZZY MODELING IN LASER MACHINING QUALITY EVALUATION
Published 2007“…The aim of this scientific research is to design knowledge based linguistic rules, algorithm, architecture & learning ability and further develop fuzzy model for laser machining kerf edge quality prediction. …”
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Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider
Published 2011“…The studies show beyond technical algorithms, physical aspects plays a big rule in client server model. …”
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Fuzzy expert system modeling of laser processing
Published 2009“…The objective of the paper is: to design knowledge based rules, algorithm, architecture & learning ability to develop fuzzy surface roughness predictive model for laser machining; to develop fuzzy predictive model using design parameters which were critically analyzed; to make a comparative study of the observed and modelled surface roughness output of 5mm Mn-Mo pressure vessel plate. …”
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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…Missing data is a pervasive challenge in diverse datasets accross various domains. …”
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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…Missing data is a pervasive challenge in diverse datasets, often resulting from human error, system faults, and respondent non-response. …”
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