Search Results - (( using application optimization algorithm ) OR ( using action method algorithm ))
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A Newton Cooperative Genetic Algorithm Method for In Silico Optimization of Metabolic Pathway Production
Published 2015“…The NCGA used Newton method in dealing with the metabolic pathway, and then integrated genetic algorithm and cooperative co-evolutionary algorithm. …”
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A new ant based rule extraction algorithm for web classification
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Monograph -
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A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network
Published 2023“…The multi-criterion energyefficient routing mechanism uses the ACO algorithm, inspired by ants' foraging behaviour. …”
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Prediction analysis of COVID-19 in Selangor by using Backpropagation Algorithm with Conjugate Gradient Method
Published 2024“…The Fletcher-Reeves approach can improve the efficiency of the backpropagation algorithm by having a faster convergence rate than other methods such as the scaled conjugate gradient method. …”
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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation
Published 2025“…A thematic analysis of 40 peer-reviewed articles was conducted using ATLAS.ti, revealing three dominant research themes: intelligent algorithms, building performance simulation techniques, and adaptive design for climate change. …”
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Modular motor driver with torque control for gripping mechanism
Published 2023“…Using the same hardware configuration, the different algorithms produced different outcomes on the output of the controller. …”
Conference paper -
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A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems
Published 2010“…Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
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Deep Reinforcement Learning For Control
Published 2021“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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Monograph -
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Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System
Published 2009“…It plays the role of objective function of the maintenance scheduling optimization problem. Using a production related heuristic method which is called system value method, the value of each workstation is determined. …”
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Development of Fuzzy Multi-Criteria Analysis Method for Tender Cleaning Service Selection
Published 2017“…The subjective assessment process is model using fuzzy number and linguistic terms. The model is solved using algorithms which integrates the decision maker’s decision for assessments on criteria weight with the performance ratings. …”
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Final Year Project -
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Design of field programmable gate array-based proportional-integral-derivative fuzzy logic controller with tunable ganin
Published 2010“…This block involves a tuning via scaling the universe of discourse and is able to accept optimal scaling gains. The particle swarm optimization method (PSO) is used to obtain the optimal values of these gains. …”
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HELM based Reinforcement Learning for Goal Localization
Published 2016“…Hierarchical Extreme Learning Machine (H-ELM) algorithm was used to find good features for effective representation. …”
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Proceeding Paper -
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Modeling sub-event dynamics in first-person action recognition
Published 2017“…First-person videos have unique characteristics such as heavy egocentric motion, strong preceding events, salient transitional activities and post-event impacts. Action recognition methods designed for third person videos may not optimally represent actions captured by first-person videos. …”
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Proceeding Paper -
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Hierarchical extreme learning machine based reinforcement learning for goal localization
Published 2017“…In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. …”
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Proceeding Paper -
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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin
Published 2021“…Instead of randomly selecting the inputs, the test generator learns how to act in an optimal way that explores new states by using new actions to gain more rewards. …”
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Thesis
