Search Results - (( using evaluation methods algorithm ) OR ( sequence optimization system algorithm ))
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1
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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2
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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3
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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4
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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5
Particle swarm optimization with deep learning for human action recognition
Published 2021“…The features are reduced using the particle swarm optimization detection technique in video image sequences to reduce the computational complexity. …”
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6
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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7
HSV-template matching with MEESPSO algorithm for human tracking in a crowded environment
Published 2024“…To address these issues, we introduced a new approach combining HSV-template matching with the MEESPSO algorithm. In this approach, HSV-template matching continuously detects the target object in sequence images, while the Midrange Exploration Exploitation Searching Particle Swarm Optimization (MEESPSO) algorithm searches for the target location in the frames. …”
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8
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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9
Multiple and solid data background scheme for testing static single cell faults on SRAM memories
Published 2013“…This method is evaluated in terms of function and performance differences between the proposed MTA and existing MTA using the User Defined Algorithm (UDA) available in the MBISTArchitect tool. …”
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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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11
A study on component-based technology for development of complex bioinformatics software
Published 2004“…While strength values were used to evaluate the applicability of the whole proposed computational framework to all the different computational PPI prediction methods.…”
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Monograph -
12
Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay
Published 2019“…The SED algorithm is an optimization method used as data-driven tools to find the optimal control parameters by using the input-output (I/O) data measurement in an actual system. …”
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13
Gravitational Search Algorithm for Assembly Sequence Planning
Published 2014“…In this paper, an approach using Gravitational Search Algorithm (GSA) which is a heuristic optimization algorithm that incorporates the Newton’s law of gravity and the law of motion into analytical studies of systems is proposed to solve the assembly sequence planning problem. …”
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14
A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…Performance metrics such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Area Under the Receiver Operating Characteristic Curve (AU-ROC), Mean Squared Error (MSE), and Mean Relative Error (MRE) are commonly used to evaluate these models. Future development of a more robust RNN-based imputation methods that integrate optimization algorithms, such as Particle Swarm Optimization (PSO) and Stochastic Gradient Descent (SGD) will further enhance the imputation accuracy and reliability.…”
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15
Design of DNA sequence alignment accelerated system using 2-dimensional array and custom instruction on FPGA / Nur Dalilah Ahmad Sabri
Published 2018“…Nowadays, the (deoxyribonucleic acid) DNA sequence database has been increased linearly with the time taken to comparing with the search of DNA sequence alignment system. …”
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16
Path optimization using genetic algorithm in laser scanning system
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17
BASE: a bacteria foraging algorithm for cell formation with sequence data
Published 2010“…In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. …”
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18
Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
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19
An Assembly Sequence Planning Approach with a Multi-State Particle Swarm Optimization
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20
Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines
Published 2009“…One of the most important issues for manufacturing systems is to determine the optimal job sequence over the production period. …”
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