Search Results - (( parameter optimization window algorithm ) OR ( variable operations learning algorithm ))

An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks by Al-Kharasani, Ameen Mohammed Abdulkarem, Othman, Mohamed, Abdullah, Azizol, Kweh, Yeah Lun

“…This article analyses and evaluates a new time sliding window traffic marker algorithm called the Optimized time sliding window Three Colour Marker (OtswTCM). …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
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Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm by Muthana, Shatha Abdulhadi, Ku Mahamud, Ku Ruhana

“…This research aims to find the optimal parameter values for the Pareto Ant Colony System (PACS) algorithm, which is used to obtain solutions for the generator maintenance scheduling problem. …”
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Design of intelligent Qira’at identification algorithm by Kamarudin, Noraziahtulhidayu

“…The process of the SPAP Algorithm is to extend parameters of the Affine Projection Block with two different selections of windowing length that affect the final accuracy on pattern classification. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems: article / Mohd Hafiz Mat Hussain by Mat Hussain, Mohd Hafiz

“…In the developed simulator, users are able to set the parameters that have influences on particle swarm optimization performance. …”
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Development of an education simulator for particle swarm optimization in solving economic dispatch problems / Mohd Hafiz Mat Hussain by Mat Hussain, Mohd Hafiz

“…In the developed simulator, users are able to set the parameters that have influences on particle swarm optimization performance. …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

“…Hence, this indicates that Invasive Weed Optimization could be implemented as a new learning algorithm for an Artificial Neural Network.…”
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Pure intelligent monitoring system for steam economizer trips by Basim Ismail F., Hamzah Abed K., Singh D., Shakir Nasif M.

“…Economizers; Failure (mechanical); Fault detection; Knowledge acquisition; Learning algorithms; Learning systems; Neural networks; Plant shutdowns; Steam; Thermoelectric power plants; Extreme learning machine; Fault detection and diagnosis systems; Intelligent modeling; Intelligent monitoring systems; Network methodologies; Operational conditions; Operational variables; Thermal power plants; Steam power plants…”

Efficient management of Top-k queries over Uncertain Data Streams with dynamic Sliding Window Model by Raja Wahab, Raja Azhan Syah

“…This method reduces computational costs by efficiently handling the insertion and exit policy for the appropriate tuple candidates within a specified window frame. The experiments in this study compare the SWMTop-kDelta algorithm with two previous researchers and two baseline approach algorithms to evaluate their effectiveness. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Synchronizing Artificial Intelligence Models for Operating the Dam and Reservoir System by Allawi, Mohammed Falah, Jaafar, Othman, Ehteram, Mohammad, Mohamad Hamzah, Firdaus, El-Shafie, Ahmed

“…It is demonstrated that shark machine learning algorithm would be a promising tool in handling the long-term optimization problem in operation a reservoir system.…”
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Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data by Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair

“…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems by Yousefi M., Darus A.N., Yousefi M., Hooshyar D.

Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning by Yingbei, Niu, Chai, Soo See

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Adaptive medium access control protocol of Wifi-Halow for home machine-to-machine network by Liew, Jiun Terng

“…Besides, the parameters of new mechanism are not defined optimally even though the procedure is detailed. …”
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models by Quadros, Jaimon Dennis, Khan, Sher Afghan, Aabid, Abdul, Baig, Muneer

“…As a result, the advantages of these results are two-fold, providing: (i) a detailed examination of the efficiency of different neural network algorithms in dealing with a genuine aerodynamic problem, and (ii) helpful insights for regulating process variables to improve technological, operational, and financial factors, simultaneously.…”
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Crossover and mutation operators of genetic algorithms by Lim, Siew Mooi, Md. Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mustapha, Aida, Leong, Kuan Yew

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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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