Search Results - (( java implementation modified algorithm ) OR ( using control learning algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”

Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

“…The new control scheme named active force control with iterative learning control algorithm (AFCIL) is complemented by the classic proportionalintegral-derivative (PID) control incorporated and designed as the outermost control loop. …”
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The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

“…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”

Control of a robot arm using iterative learning algorithm with a stopping criterion by Mailah, Musa, Chong, Jonathan Wun Shiung

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Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms by Mailah, Musa, Ong, Miaw Yong

“…The paper highlights a novel and robust method to control a robotic arm using an iterative learning technique embedded in an active force control strategy. …”
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Active Suspension System for Passenger Vehicle using Active Force Control with Iterative Learning Algorithm by Rosmazi, Rosli, Musa, Mailah, Priyandoko, Gigih

“…The paper describes the practical implementation of a new hybrid control method to a vehicle suspension system using Active Force Control (AFC) with Iterative Learning (IL) and proportional-integralderivative (PID) control strategy. …”
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Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm by Mailah, Musa

“…The paper presents a novel approach to estimating the inertia matrix of a robot arm adaptively and on-line using an iterative learning algorithm. It is employed in conjunction with an active force control strategy which has been shown to be very effective in accommodating the disturbances. …”
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Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong by Mailah, Musa, Ong, Miaw Yong

“…The paper highlights a novel and robust method to control a robotic arm using iterative learning technique embedded in an active force control strategy. …”
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Effect of chaos noise on the learning ability of back propagation algorithm in feed forward neural network by Azian Azamimi, Uwate, Yoko, Nishio, Yoshifumi

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Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning by Zahraoui Y., Zaihidee F.M., Kermadi M., Mekhilef S., Alhamrouni I., Seyedmahmoudian M., Stojcevski A.

“…To determine the optimal parameters of the FOSMC for control speed in a PMSM drive, a neural network algorithm with reinforcement learning (RLNNA) is proposed. …”

Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

“…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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Multi-Agent Reinforcement Learning For Swarm Robots Formation by Bujang, Christina

“…The reinforcement learning algorithm offers one of the most general frameworks in learning subjects to address some of the control issues in a multi-agent system. …”
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Anomaly detection in ICS datasets with machine learning algorithms by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Abdul Rahman, Farah Diyana, Tahir, Mohammad

“…The machine learning algorithms have been performed with labeled output for prediction classification. …”
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Memory efficient BFGS neural-network learning algorithms using MLP-network: a survey by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

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The impact of virtual reality on programming algorithm courses on student learning outcomes by Dewi, Ika Parma, Ambiyar, Effendi, Hansi, Giatman, Muhammad, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…In the control class, students apply traditional learning, while the experimental class uses VR-based learning. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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