Search Results - (( using simulation method algorithm ) OR ( sequence optimization system algorithm ))
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1
A New Hybrid Image Encryption Technique Using Lorenz Chaotic System and Simulated Kalman Filter (SKF) Algorithm
Published 2022“…Nowadays, encryption is one of the most popular and effective security methods used by company and organizations. A new hybrid technique, Lorenz chaotic system and an optimization algorithm, Simulated Kalman Filter (SKF) had been proposed to solve image encryption problem. …”
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2
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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3
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. …”
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4
Design and analysis of sequence generator module using eulerian path algorithm for DNA fragment assembly: article / Mustaqim Mohd Subri
Published 2013“…Mostly, “overlap – layout - consensus” method is used to assemble DNA, but a new system need to be introduced to overcome problems in assembling long DNA sequence in this method. …”
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5
Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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6
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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7
Potential of data minimization techniques approach in improving DNA sequences alignment and comparison / Syed Abdul Mutalib Al Junid … [et al.]
Published 2012“…This study will initially involve algorithm modification, mathematical formulation, logic design and simulation for data minimization and existing DNA sequences alignment algorithm. …”
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8
Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals
Published 2012“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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9
On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems
Published 2020“…The optimization of the antenna selection and optimal transmission power with impact of pilot reuse sequences were achieved, by applying Newton’s method and the Lagrange multiplier. …”
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10
DNA sequence allignment accelerator using MATLAB / Noraminah Ismail
Published 2014“…This paper presents the development of DNA sequence alignment accelerator using MATLAB. The Smith Waterman algorithm has been developed and simulated for nucleotide sequence alignment in optimizing accelerating speed. …”
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11
Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran
Published 2018“…The minimum value of the buses voltages was between (0.9502 p.u.-0.98176 p.u.) for different systems. The power losses during optimal switching sequence process were between (365.52kW-9265.5kW) for different systems. …”
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12
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
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13
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Motivated by the limitations of the current methods, there is an advantage to using safe experimentation dynamics (SED) as a tool for optimization. …”
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14
Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System
Published 2009“…The results demonstrate that the proposed optimal maintenance scheduling method yields much better system value rather than sequencing methods. …”
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15
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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16
Design of DNA fragment assembly using IWP method on application-specific integrated-circuit / Hasniliati Hassan
Published 2017“…The method proposed is to design DNA assembly algorithms in Verilog HDL and implemented it in ASIC design flow. …”
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17
Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem
Published 2022“…Meta-heuristic method is able to escape the local optima. Simulated Annealing (SA) is used where search is done in sequence basis and to solve optimization problems. …”
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18
Development and implementation of Intelligent Soot Blowing Optimization System for TNB Janamanjung
Published 2023Conference Paper -
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Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems
Published 2021“…This formulates the optimization problem of joint optimal antenna selection, transmits power allocation and joint user selection to mitigate inter-cellinterference in downlink multi-cell massiveMIMO systems under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm (LCA) for Newton’s methods and Lagrange multipliers. …”
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20
Direct Adaptive Predictive Control For Wastewater Treatment Plant
Published 2012“…This N4SID plays the role of the software sensor for on-line estimation of prediction matrices and control matrices of the bioprocess, joint together with model predictive control (MPC) in order to obtain the optimal control sequence. The performances of both estimation and control algorithms are illustrated by simulation results. …”
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