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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions
Published 2022“…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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SUDOKU HELPER
Published 2015“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…These kind of activities highly sparsely distributed in the input space which is problematic to be distinguish using traditional classifier model. …”
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Energy efficient cluster head distribution in wireless sensor networks
Published 2013“…PSO is lightweight heuristic optimization algorithm with each CH will move towards the best solutions by individual interaction with one another while learning from their own experience. …”
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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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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…The results indicated that the hydropower generated by the proposed algorithm could produce an evenly distributed high amount of energy increases the reliability of the reservoir system. …”
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Predictive Framework for Imbalance Dataset
Published 2012“…Experimental results suggested that the class probability distribution function of a prediction model has to be closer to a training dataset; less skewed environment enable learning schemes to discover better function F in a bigger Fall space within a higher dimensional feature space, data sampling and partition size is appear to proportionally improve the precision and recall if class distribution ratios are balanced. …”
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Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting
Published 2024“…Deep learning excels at managing spatial and temporal time series with variable patterns for streamflow forecasting, but traditional machine learning algorithms may struggle with complicated data, including non-linear and multidimensional complexity. …”
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Prediction of rice biomass using machine learning algorithms
Published 2022“…Unmanned aerial vehicles (UAVs) may address these issues. Machine learning algorithms (MLs) can predict rice biomass from UAV-based vegetation indices (VIs). …”
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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An approach to improve detecting and removing cross- site scripting vulnerabilities in web applications
Published 2015“…This research work was limited to Java based web applications. In future research, the method can be extended to include other programming languages as well as other similar web application security vulnerabilities.…”
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Human activity recognition via accelerometer and gyro sensors
Published 2023“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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Final Year Project / Dissertation / Thesis -
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Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS
Published 2019“…This is based on highresolution Light Detection and Ranging (LiDAR) techniques both airborne and terrestrial (ALS and TLS). Different machine learning algorithms (Artificial Neural Network [ANN], K Nearest Neighbor [KNN] and Support Vector Machine [SVM]) were tested individually and with various ensemble models (bagging, voting, and boosting) to detect the probability of the landslide and rockfall occurrences. …”
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