Search Results - (( using function based algorithm ) OR ( sequence optimization model algorithm ))
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1
Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…An example of the DNN model is the Attentive Sequence-to-Sequence (Seq2Seq) model that was first created to tackle a problem setting in language processing. …”
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Thesis -
2
Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm
Published 2017“…In this article, we have proposed a distance-based sequence encoding algorithm that captures the sequence's statistical characteristics along with amino acids sequence order information. …”
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Article -
3
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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Conference or Workshop Item -
4
Optimized tree-classification algorithm for classification of protein sequences
Published 2016“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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5
Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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6
Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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Indexed Article -
7
Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review
Published 2023“…This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. …”
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8
Assisted History Matching by Using Genetic Algorithm and Discrete Cosine Transform
Published 2014“…Next, fluid flow equations were derived to obtain the forward model and eventually, the objective function. Later, an algorithm combining both Genetic Algorithm and Discrete Cosine Transform was proposed, which shows the step-by-step sequence of both methods. …”
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Final Year Project -
9
Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…Thus, a reliable optimization technique such as Nature Inspired Metaheuristic Algorithms (NIMA) is crucial to address this issue. …”
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10
Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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11
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…These steps have conducted using the MEMPHA model and ROA algorithm to optimize three metrics: execution time, total communication volume, and imbalance ratio (load balancing). …”
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12
Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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13
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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14
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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15
Protein Sequences Classification Using Modular RBF Neural Networks
Published 2002“…These algorithms compare an unseen protein sequence with all the identified protein sequences and returned the higher scored protein sequences. …”
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Book Chapter -
16
Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…The Whale Optimisation Algorithm (WOA), Harris Hawks Optimisation (HHO) Algorithm, Lévy Flight WOA (LFWOA) and the Opposition-Based Learning of HHO (OBL-HHO) were proposed to simulate the initial model’s response and optimise the Klang Gate Dam (KGD) release operation with observed inflow, water level (storage), release, and evaporation rate (loss). …”
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Final Year Project / Dissertation / Thesis -
17
Conceptual Design And Dynamical Analysis Of Aerostat System
Published 2020“…The dynamical analysis of the aerostat is conducted by developing a three degree of freedom simulation model. Simscape MultibodyTM, an extension of MATLAB®/Simulink that employs a block-based modelling technique is used to develop the three degrees of freedom model. …”
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18
Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System
Published 2009“…Then, using genetic algorithm-based software which is called SimRunner and has been embedded by ProModel, the scheduling optimization procedure is run to find optimum maintenance schedule. …”
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19
Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
Published 2014“…An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
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Article -
20
Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model
Published 2019“…The required memory of this algorithm is also time independent. In addition, the optimal state sequence obtained by the EVRA algorithm is the same as that obtained by the classical Viterbi algorithm for HHMM.…”
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