Search Results - (( sequence optimization method algorithm ) OR ( using adoption optimization 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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Thesis -
2
Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…The major problems in classifying protein sequences into existing families/superfamilies are the following: the selection of a suitable sequence encoding method, the extraction of an optimized subset of features that possesses significant discriminatory information, and the adaptation of an appropriate learning algorithm that classifies protein sequences with higher classification accuracy. …”
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3
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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4
T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm
Published 2019“…In order to reduce test cases several T-way sequence input interaction strategies are explored, such as, Bee Algorithm(BA), Kuhn encoding (K) , ASP with Clasp , CP with Sugar, Erdem (ER) exact encoding, Tarui (TA) Method, U, UR, D and DR, Brain (BR). …”
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Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin
Published 2013“…The problem was initially tackled by “exact methods” such as the branch and bound method, which is based on the exhaustive enumeration of a restricted region of solutions containing exact optimal solutions. …”
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Hybrid optimisation electromagnetic interference shielding effectiveness:mechanical and physical performance of plaster mortar containing palm oil fuel ash using taguchi grey and t...
Published 2019“…Six factors namely POFA admixture percentage, topcoat powder /binder ratio (TP/B), water/binder ratio (W/B), latex agent content (LA), the particle size of POFA and curing condition are used to control the nine responses. Pre-experiment data is optimized based on Taguchi-grey and Flower Pollination Algorithm (FPA) methods. …”
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7
Fair energy-efficient resource allocation for downlink NOMA heterogeneous networks
Published 2020“…Simulation results show that the proposed NOMA with optimal power allocation method using SCP and GA (NOMA-SCP-GA) achieves fair energy efficiency performance with lower complexity compared to the benchmark methods. …”
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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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More on completion time algorithms for intermediate storage tanks in multiproduct batch process scheduling using matrix representation
Published 2008“…In this work, new completion time algorithms for UIS and FIS transfer policies are proposed using matrix representation. …”
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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…Performance metrics such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Area Under the Receiver Operating Characteristic Curve (AU-ROC), Mean Squared Error (MSE), and Mean Relative Error (MRE) are commonly used to evaluate these models. Future development of a more robust RNN-based imputation methods that integrate optimization algorithms, such as Particle Swarm Optimization (PSO) and Stochastic Gradient Descent (SGD) will further enhance the imputation accuracy and reliability.…”
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11
Computational methods for self-assembly of DNA nanostructures / Ong Hui San
Published 2016“…Several approaches have been adopted including development of an autonomous tool that incorporated evolutionary optimization algorithm in constructing these heterogeneous DNA shapes and the application of heuristic through undirected graph theory as an annotation schema to produce the connectivity maps. …”
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12
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 -
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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…Performance metrics such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Area Under the Receiver Operating Characteristic Curve (AU-ROC), Mean Squared Error (MSE), and Mean Relative Error (MRE) are commonly used to evaluate these models. Future development of a more robust RNN-based imputation methods that integrate optimization algorithms, such as Particle Swarm Optimization (PSO) and Stochastic Gradient Descent (SGD) will further enhance the imputation accuracy and reliability.…”
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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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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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