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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…A case study taken from database, provided by Le2i Universite de Bourgoune is used to evaluate the performance of the Bat Algorithm. …”
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A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem
Published 2022“…This paper studies the correlation of different parameters selection in Bat Algorithm in solving the camera auto-calibration problem. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
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A Comparative Study of the Application of Swarm Intelligence in Kruppa-Based Camera Auto-Calibration
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Conference or Workshop Item -
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Auto-encoder variants for solving handwritten digits classification problem
Published 2020“…Auto-encoders (AEs) have been proposed for solving many problems in the domain of machine learning and deep learning since the last few decades. …”
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Comparisons of automated machine learning (AutoML) in predicting whistleblowing of academic dishonesty with demographic and theory of planned behavior
Published 2023“…The findings of this study will be a great interest of many research scholars to conduct a more in-depth analysis on AutoML for many domains mainly in education and academic misconduct fields. â�¢ AutoML is the first of its kind to be empirically compared between TPOT and AutoModel in an application to predict academic dishonesty whistleblowing. â�¢ Besides accuracy performances of the AutoML, the proportion of the variance of each attribute from demographic and Theory of Planned Behavior (TPB) is also presented in the prediction models of academic dishonesty whistleblowing. â�¢ AutoML is a convenient and reproducible rapid modeling method of machine learning to be used in many kinds of prediction problem. …”
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Auto-formation group chat for fitness application with rule-based / Amar Aslam Ramli
Published 2018“…Moreover, the algorithm used for rule-based expert system is forward chaining method. …”
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Student Project -
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A Mobile Application For Stock Price Prediction
Published 2021“…A mobile application for stock price prediction using time series algorithms is developed to tackle the problem mentioned. …”
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Final Year Project / Dissertation / Thesis -
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Implementation of (AES) Advanced Encryption Standard algorithm in communication application
Published 2014“…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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Undergraduates Project Papers -
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems
Published 2020“…Therefore, in this research, a new model namely Encoder Simplified GRU (ES-GRU) is proposed to reduce dimension of data using an Auto-Encoder (AE). Accordingly, the reset gate is replaced with an update gate in order to reduce the redundancy and complexity in the standard GRU. …”
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Thesis -
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Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution
Published 2014“…The current approach in the literature has been largely based on trial and error, while most of the reported optimization approaches have limited the domain of the problem to a single objective problem. This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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