Search Results - (( sequence optimization method algorithm ) OR ( parameters optimization approach algorithm ))
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1
Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…Hence, this research’s objective aimed to propose an optimization strategy based on Structural Modification and Optimizing Training Network for improving the lacking of accuracy of response in the chatbot application, to propose the algorithm enhancement to improve the current attention mechanism in the Attentive Sequence-to-Sequence model and the network’s training optimization of its inability to memorize the dialogue history, and lastly, to evaluate the accuracy of response of the proposed solution through data training on loss function and real data testing. …”
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2
Improved opposition-based particle swarm optimization algorithm for global optimization
Published 2021“…Particle Swarm Optimization (PSO) has been widely used to solve various types of optimization problems. …”
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3
Optimizing LSTM S2S models with Evolutionary Mating Algorithm (EMA) for direct multi-step forecasting of household electrical power consumption
Published 2026“…This study proposes a hybrid approach that combines a Long Short-Term Memory Sequence to Sequence (LSTM S2S) model with the Evolutionary Mating Algorithm (EMA) to optimize the model settings. …”
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4
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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5
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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6
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
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7
Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi
Published 2019“…Genetic Algorithm(GA) is used to optimize the order of sequence of the input sample and the parameters of the Bayesian ARTMAP (BAM). …”
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8
Development of optimized maintenance scheduling model for coal-fired power plant boiler
Published 2023“…Literature revealed that mathematical methods and metaheuristic algorithms are common approaches in solving combinatorial optimization problems with a large search space in a reasonable computational run time. …”
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Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach
Published 2024“…Subsequently, simulation data from numerous cases are utilized to identify the best parameter combination using machine learning algorithms. …”
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10
Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Application of genetic algorithm method to optimize flow shop sequencing problem as the title of this project is the study about the method used in order to optimize flow shop sequencing problem. …”
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Undergraduates Project Papers -
11
Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach
Published 2025text::Thesis -
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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16
Minimization of machining process sequence based on ant colony algorithm and conventional method
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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19
MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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20
Product assembly sequence optimization based on genetic algorithm
Published 2010“…A single objective GA is used to obtain the optimal assembly sequence, exhibiting the minimum time taken. …”
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