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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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3
MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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4
MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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5
Minimization of machining process sequence based on ant colony algorithm and conventional method
Published 2023“…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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6
MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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7
MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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8
MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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9
Optimizing optimal path trace back system for Smith-Waterman algorithm using structural modelling technique: article
Published 2012“…back system for Smith-Waterman Algorithm using Structural Modelling Technique. The objectives for this paper are to optimize the best trace back scanning performance and also to design the simple architecture in order to reduce the runtime. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…Two methods of optimization are used for CBLL. They are Cross Entropy and also Genetic Algorithm. …”
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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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Monograph -
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Optimization of Assembly Sequence Planning Using Soft Computing Approaches: A Review
Published 2019“…This review focused on ASP modeling approach, optimization algorithms and optimization objectives. …”
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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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14
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 -
15
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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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…In addition, one of the main challenges has been development of efficient algorithm for solving aforementioned model to find exact feasible optimal solution. …”
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Optimal input shaping for vibration control of a flexible manipulator using genetic algorithm
Published 2005“…This thesis presents optimization of input shaping technique for vibration control of a flexible robot manipulator using genetic algorithms (GA). …”
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Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals
Published 2012“…Results indicate that “earliest available vehicle” is the best heuristic rule for the integrated scheduling method. Moreover, it is shown that on average, the best objective values obtained by the GA and SA algorithm, are only 6.4% and 3.7% worse than the optimal ones found by the MIP model, respectively; demonstrating that both algorithms are able to achieve near optimal solutions. …”
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Thesis -
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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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Thesis -
20
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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