Search Results - (( java implementation during algorithm ) OR ( using samples learning algorithm ))
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We extracted 30 different features from network traffic. We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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Thesis -
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…In conclusion, diabetic ketoacidosis in unrestricted food intake conditions can be predicted using the proposed ANFIS and GA-ANFIS model. Future work should be focusing on data collection of the E-Nose sensors and the improvement of the learning algorithm robustness towards environmental noise during data acquisition, such as evaporation and contamination of odor samples.…”
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Pairwise testing tools based on hill climbing algorithm (PTCA)
Published 2014“…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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Undergraduates Project Papers -
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. Few by electronic components such as RFID, multiplexer, XBee, and servo motors have been used to realize the system. …”
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Alternate methods for anomaly detection in high-energy physics via semi-supervised learning
Published 2020“…In this paper, we introduce two new algorithms called EHRA and C-EHRA, which use machine learning regression and clustering to detect anomalies in samples. …”
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Evolutionary deep belief networks with bootstrap sampling for imbalanced class datasets
Published 2019“…However, when handling imbalanced class data, DBN encounters low performance as other machine learning algorithms. In this paper, the genetic algorithm (GA) and bootstrap sampling are incorporated into DBN to lessen the drawbacks occurs when imbalanced class datasets are used. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation
Published 2020“…To test the effectiveness of the proposed algorithm, the real and generated samples is added to training phase to build a prediction model using M5 Model Tree. …”
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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Academic Exercise -
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A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification
Published 2024“…CNN is a type of convolution neural network that has an unpredictable development and uses convolution calculations. It is one of the most well-known deep learning algorithms. …”
Conference Paper -
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Advanced flood prediction at forest with rainfall data using various machine learning algorithms
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Conference or Workshop Item -
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Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…The system is capable in operating an off-line programming method, starting from its programming sequences until robotic implementation of the program. During early stages, the research is emphasis more towards designing a robotic system using RoboLab software and C++ programming language. …”
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…Results show that the proposed algorithm required a learning dataset size as small as 5 samples and was resistant to learning labelling error up to 50%.…”
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Hybrid sampling and random forest machine learning approach for software detect prediction
Published 2019“…Cross validation is used to remove overriding problem. Scikit-learn library is used for machine learning algorithms. …”
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Conference or Workshop Item -
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Wavelet network based online sequential extreme learning machine for dynamic system modeling
Published 2013“…The main advantage of OSELM over conventional algorithms is the ability of updating network weights sequentially through data sample-by-sample in a single learning step. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. Six machine learning algorithms were applied and compared based on the classification evaluation methods. …”
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Final Year Project / Dissertation / Thesis -
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Impact learning: A learning method from feature's impact and competition
Published 2023“…A variety of well-known machine learning algorithms have been developed for use in the field of computer science to analyze data. …”
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