Search Results - (( based interactive method algorithm ) OR ( using factorization learning algorithm ))
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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining
Published 2009“…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq
Published 2021“…The problem-based and the game-based programming workshops utilizing our problem-solving model using sorting algorithms were the experimental groups. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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Comparison Method Q-Learning and SARSA for Simulation of Drone Controller using Reinforcement Learning
Published 2023“…One of the aspects emphasized here is the difficulty of controlling the drone, and the system developed is still under full control by the users as well. Reinforcement Learning is used to enable the system to operate automatically, thus drone will learn the next movement based on the interaction between the agent and the environment. …”
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers
Published 2009“…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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Wifi-based location-independent human activity recognition and localization using deep learning
Published 2024“…Third, recognizing the capability of location independence, we propose a novel locationindependent HAR using a self-learning CSI-based technique for wireless sensor networks. …”
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Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption
Published 2015“…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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The development of deformable bodies collision response algorithm for interactive virtual environment
Published 2006“…Physical based deformation method usually suffers from high computation cost which does not favors practical interactive applications, even if the deformation only occurs in a small area of the deformable object. …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. …”
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Efficient prime-based method for interactive mining of frequent patterns.
Published 2011“…In this paper, we propose a new method based on prime number and its characteristics mainly for interactive mining of frequent patterns. …”
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Prime-based method for interactive mining of frequent patterns
Published 2010“…As response to the above-mentioned challenges, this study is devoted towards developing an interactive mining method based on prime number and its special characteristic “uniqueness” by which the content of the relevant data is transformed into a compact layout. …”
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An experimental study of modified black hole algorithms
Published 2018“…Ultimately, seven variants of BH algorithms are established based on the white hole, local search, and gravitational interaction. …”
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Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm
Published 2020“…We created the dynamic learning rate and dynamic momentum factor for increasing the efficiency of the algorithm. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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