Search Results - (( sequence optimization approach algorithm ) OR ( sequence optimization model algorithm ))*
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1
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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2
Optimization of Assembly Sequence Planning Using Soft Computing Approaches: A Review
Published 2019“…The literature review was conducted through finding related published research papers specifically on ASP that used soft computing approaches. This review focused on ASP modeling approach, optimization algorithms and optimization objectives. …”
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Modelling of Assembly Sequence Planning Problem using Base Part Concept
Published 2018“…However, this approach resulting in the large number of assembly sequence possibility, and finally make the optimization process become harder. …”
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4
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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5
Development of an augmented reality based facility layout planning and optimization / Tan Chee Hau
Published 2020“…Production line commonly used algorithm such as shortest processing time (SPT), longest processing time (LPT), cycle time optimization and centre of gravity (CoG) algorithm are coded in this system which enables the production schedule and sequence to be optimized. …”
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6
Modelling of assembly sequence planning problem using base part concept
Published 2018“…However, this approach resulting in the large number of assembly sequence possibility, and finally make the optimization process become harder. …”
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7
A comparative analysis of software engineering approaches for sequence analysis
Published 2013“…Sequence analysis problems are NP hard and need optimal solutions. …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…This study presented an intelligence based genetic algorithm approach to optimize the considered problem objectives through reducing the problem complexity. …”
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Energy efficient modeling and optimization for assembly sequence planning using moth flame optimization
Published 2019“…The problem was then optimized using moth flame optimization (MFO) and compared with well-established algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). …”
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10
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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11
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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12
Process Sequencing Modeled as TSP with Precedence Constraints - A Genetic Algorithm Approach
Published 2014“…The process sequencing problem can be modeled as the travelling salesman problem with precedence constraints (TSPPC). …”
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13
Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The advantage of the MGT algorithm is that it does not need the exact opponent’s preferences to generate Pareto-optimal offers, instead, it works with a greedy sequence. …”
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14
Multilevel optimization for dense motion estimation
Published 2011“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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15
Job sequencing and layout optimization in virtual production line
Published 2011“…The contribution of this paper is the integration of two optimization models such as: layout and sequence (job) optimization to those factories who want to produce the various kinds of products with fixed and changeable machine locations as integrated approach for designing a virtual production line. …”
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16
Multiobjective Fuzzy Mixed Assembly Line Sequencing Optimization Model
Published 2014“…It can be deduced from previous studies that there exists a research gap in assembly line sequencing optimization model for mixed-model production lines. …”
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DNA sequence design for direct-proportional length-based DNA computing: Particle swarm optimization vs population based ant colony optimization
Published 2012“…The results show that P-ACO approach can generate relatively better DNA sequences in some objectives than PSO approach and the other methods. …”
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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation
Published 2013“…Statistical tests on the algorithms' performance indicates that the proposed MODPSO algorithm presents significant improvement in terms of larger nondominated solution numbers in Pare't o optimal, compared to comparable algorithms including GA based algorithms in both single-model and mixedmodel ASP and ALB problems. …”
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19
New completion time algorithms for sequence based scheduling in multiproduct batch processes using matrix
Published 2008“…These models require good understanding in formulating the problem using programming techniques to find the optimal solution. …”
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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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