Search Results - (( sequence optimization _ algorithm ) OR ( using optimization window algorithm ))
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1
Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm
Published 2016“…This signifies that the training was successful based on the fitted values of the window size. Thus the proposed model trained with the CS algorithm provides a high convergence rate to the true global minimum and a better optimal solution. …”
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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex
Published 2012“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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Optimized crossover genetic algorithm for vehicle routing problem with time windows
Published 2010“…Conclusion/Recommendations: This study presented a genetic algorithm for solving vehicle routing problem with time windows using an optimized crossover operator. …”
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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows
Published 2017“…This paper presents a stochastic partially optimized cyclic shift crossover operator for the optimization of the multi-objective vehicle routing problem with time windows using genetic algorithms. …”
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Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
Published 2022“…Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). …”
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Final Year Project / Dissertation / Thesis -
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Ensemble learning using multi-objective optimisation for arabic handwritten words
Published 2021“…In this thesis, new type of feature for handwriting using Segments Interpolation (SI) to find the best fitting line in each of the windows with a model for finding the best operating point window size for SI features. …”
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Thesis -
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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows
Published 2017“…This paper presents a stochastic partially optimized cyclic shift crossover operator for the optimization of the multi-objective vehicle routing problem with time windows using genetic algorithms. …”
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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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Assembly sequence optimization using the bees algorithm
Published 2022“…As a result, the Bees Algorithm outperforms other algorithms in dealing with the multi-modal optimization problem of assembly sequence optimization.…”
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Book Chapter -
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An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks
Published 2016“…This article analyses and evaluates a new time sliding window traffic marker algorithm called the Optimized time sliding window Three Colour Marker (OtswTCM). …”
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Enhancement on the modified artificial bee colony algorithm to optimize the vehicle routing problem with time windows
Published 2022“…The proposed algorithm was evaluated using benchmark datasets comprising 56 VRPTW instances and 56 Pickup and Delivery Problems with Time Windows (PDPTW). …”
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Thesis -
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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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Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems
Published 2021“…These algorithms can influence the convergence to find an efficient optimal solution. …”
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Assessment of integrated assembly sequence planning and line balancing optimization using metaheuristic algorithms
Published 2024“…These algorithms include Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). …”
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Conference or Workshop Item -
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Gravitational Search Algorithm for Assembly Sequence Planning
Published 2014“…Thus, it is needed to find the optimal sequence from the feasible assembly sequences. …”
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Simulation for dynamic patients scheduling based on many objective optimization and coordinator
Published 2024“…Finally, the role of the coordinator is to select a subset of patients from the window and pass them to the optimization algorithm. …”
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Application of the Bees Algorithm to find optimal drill path sequence
Published 2024“…These results show that the Bees Algorithm can be an alternative approach to find the optimal drilling sequence.…”
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Proceeding Paper -
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Removal of high density salt and pepper noise from image and video based on optimal decision based algorithm
Published 2014“…Detection is provided by using statistical analysis in each window, then the appropriate replacement for the noisy pixel is conducted from given values inside the current window or adjacent reconstructed pixels based on mean calculation and also, for very high density of noise which density of noise is bigger than 80%, the reconstruction is based on a recursive approach. …”
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Conference or Workshop Item -
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A filtering algorithm for efficient retrieving of DNA sequence
Published 2009“…The algorithm filtered the expected irrelevant DNA sequences in database from being computed for dynamic programming based optimal alignment process. …”
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Article -
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Single Step Multivariate Solar Power Forecasting using Adaptive Learning Rate LSTM Model with Optimized Window Size
Published 2024Conference Paper
