Search Results - (( using function based algorithm ) OR ( sequence optimization means algorithm ))
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1
Biological-based semi-supervised clustering algorithm to improve gene function prediction
Published 2011“…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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2
Hybrid multiobjective genetic algorithm for integrated dynamic scheduling and routing of jobs and automated guided vehicles in flexible manufacturing systems
Published 2014“…The algorithm used weight mapping crossover (WMX) and Insertion Mutation (IM) as genetic operators for sub-chromosomes represented with priority-based representation. …”
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3
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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4
A study on component-based technology for development of complex bioinformatics software
Published 2004“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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5
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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6
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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7
Antenna arrays in multi-user detection of spread spectrum signals
Published 2007“…A number of multi-user detection algorithms have been suggested by various authors. Optimal receivers based upon maximum likelihood sequence decoding are quite complex, their complexity increasing exponentially with the number of users in the system. …”
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8
Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…The monthly storage capacity fails in 2077, substantially earlier than the other three algorithms in Scenario 2. The LFWOA was used in this study to improve the efficacy of the algorithms by delivering a more accurate monthly storage capacity and reservoir risk assessment for Scenario 2 of RCP 2.6. …”
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9
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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10
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Article -
11
Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment
Published 2024“…A notable entrant in this domain is the harris hawks optimization (hho) algorithm, which has distinguished itself through published optimization outcomes, positioning it as a formidable competitor among state-of-the-art metaheuristics. …”
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12
A headway and order scheme based mixed integer goal programming model for railway rescheduling / Zuraida Alwadood
Published 2017“…The model is solved by means of preemptive goal programming technique, using MATLAB r2014a, which automatically generates the optimal solution to the problem. …”
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13
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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14
Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin
Published 2021“…The computation time complexity of the Q-Learning-based test coverage algorithm was also analyzed. …”
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15
Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…Then, it started to find the best sequence of jobs for each line based on the generated population by heuristic algorithm. …”
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16
Biogeography based optimization (BBO) algorithm to minimise non-productive time during hole-making process
Published 2015“…The proposed approach tackles the sequencing problem when several holes must be drilled by means of different tools to reach their desired size. …”
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17
Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem
Published 2005“…Therefore, researchers concentrated on developing branch-and-bound or heuristic algorithms. Ali Allahverdi, 1998 obtained the optimal solutions for minimizing mean flow time in a two-machine flow shop with Sequence-independent set up times by using three heuristic algorithms. …”
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18
Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…The collected data is processed by a Gaussian filtering approach that eliminates irrelevant information, reducing the overfitting issues. Then flock optimization algorithm is applied to detect the sequence; this process is used to reduce the convergence and optimization problems. …”
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19
VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…Hence, VLSI floorplanning is important in IC design. Floorplanning optimization consists of representation and optimization algorithm. …”
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20
A neural network modal decomposition mechanism in predicting network traffic
Published 2023“…Specifically, the predictive accuracy indexes such as Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) can reach a lowest optimum value of 1.1410, 0.1758 and 0.2263, and the average training time is reduced by 25.25%, 23.87% and 41.36%, respectively. …”
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