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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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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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Final Year Project -
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Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement
Published 2016“…Meanwhile, the Crisp-I current controller is developed to perform the integral control action, in which a controllable integral gain value is introduced.Third, a HFP+CI self-charging dc-link voltage control algorithm is constructed, using the self-charging control strategy together with a combination of Fuzzy-P and Crisp-I voltage controllers. …”
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A novel deadlock detection algorithm for neighbour replication on grid environment
Published 2012“…The NRGDD simulation model has been developed to test the algorithm on NRG. Two experiments have been conducted to test the correctness of NRGDD algorithm. …”
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Adaptive artificial neural network for power system security assessment and control action
Published 2012“…This is particularly important for giving a possible control action to mitigate an insecure situation during disturbance using AANN. …”
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Simulation of an adaptive artificial neural network for power system security enhancement including control action
Published 2015“…This paper presents a new method for enhancing power system security, including a remedial action, using an artificial neural network (ANN) technique. …”
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Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi
Published 2020“…In order to predict the attackers of online shaming, Ant Colony Optimization Algorithm will be used and it will be compared with J48 algorithm. …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…To show the methods applicability, this paper uses the proposed algorithm in three sustainable and resilient case studies. …”
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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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Adaptive hybrid fuzzy-proportional plus crisp-integral current control algorithm for shunt active power filter operation
Published 2016“…Hence, it simplifies the controller development. Meanwhile, the Crisp-I current controller is developed to perform integral control action using a controllable gain value; to improve the steady-state control mechanism. …”
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Magnetic attitude control options for earth pointing small satellite
Published 2011“…The developed control algorithms are modeled using the MATLAB SIMULINK codes. …”
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Thesis -
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Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment
Published 2011“…The third algorithm, named as Pro-Active Intelligence algorithm has inspired autonomous action triggering for each event interoperation, using a control action statement that is generated by SOAP packets required for joint execution of tasks among heterogeneous subsystems. …”
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A hybrid database encryption algorithm based on reverse string and dynamic key
Published 2016“…Personal computers has become one of the important part of human life, especially when they using the Internet or any public networks.So, the information or data may still be deliberately or inadvertently leaked out by the insiders or customers.In this paper, we proposing new algorithm to protect any type of data, depending on the substitution techniques, using dynamic key (DK) and reveres string for each character in the text (or field in the file of the database) and each string .A special equation was developed to generate the DK, it’s depend on the length of string, order the character in the string,ASCII code of the character, and string sequence.The proposed algorithm using the reverse string before encryption, also, there are two actions after that, for the purpose of increasing the complexity of the algorithm.The results showed that The developed algorithm was successes to remove any duplicate encryption, for each character and each record even when the text duplicated.…”
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An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles
Published 2022“…Among different algorithms, this study focuses on modelling the non- recursive phasor estimation method in a power Simulink environment for a standard test system equipped with a developed algorithm to detect the fault zone. …”
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Design high frequency surgical robot controller: design FPGA-based controller for surgical robot manipulator simscape modeling
Published 2016“…In HDL integral algorithm the minimum input arrival time before clock is 15.599 ns and the maximum frequency is 64.1 MHz, but in the best design action, the maximum frequency to design this single chip algorithm should be 178.190 MHz.…”
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DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES
Published 2019“…In this study, we propose to implement a deep-learning approach for detection of ships on satellite images in various conditions. The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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Final Year Project -
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…Through this study, Q-Learning and State-Action-Reward-StateAction (SARSA) are used in this study and the comparison of results involving both the performance and effectiveness of the system based on the simulation of both methods can be seen through the analysis. …”
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