Search Results - (( based optimization based algorithm ) OR ( probable estimation using algorithm ))
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1
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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2
Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023“…Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation…”
Conference Paper -
3
Tree-based contrast subspace mining method
Published 2020“…Genetic algorithm has been widely used to find global solution to optimization and search problem. …”
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4
Compressed Sensing Implementations For Sparse Channel Estimation In OFDM Systems
Published 2018“…Fusing different reconstruction algorithms may result in the probability of fusing several incorrectly estimated indices over noisy channels. …”
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Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…Bayesian classification and decision making are based on probability theory and choosing the most probable or the lowest risk. …”
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7
Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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8
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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9
Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)
Published 2024“…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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Article -
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Reliability assessment of power generation systems using intelligent search based on disparity theory
Published 2017“…Disparity evolution is used to enhance the performance of the probability of mutation in a genetic algorithm (GA) by incorporating features from the paradigm into the disparity theory. …”
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11
Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Besides, algorithm based method has been widely used to forecast future result in various field for example art, biology, marketing including engineering. …”
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Final Year Project -
12
Reliability Assessment of Power Generation Systems Using Intelligent Search Based on Disparity Theory
Published 2017“…Disparity evolution is used to enhance the performance of the probability of mutation in a genetic algorithm (GA) by incorporating features from the paradigm into the disparity theory. …”
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13
Optimization of operational policies for the Minab Reservoir, Southern Iran
Published 2012“…Rule curve for five possible scenarios were optimized by using Genetic Algorithms. The agricultural management optimization was applied to optimize the parameters like area, relative yield water requirements and irrigation efficiency. …”
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14
Battery remaining useful life estimation based on particle swarm optimization-neural network
Published 2024“…Concerning that matter, this study proposed hybrid Particle Swarm Optimization–Neural Network (PSO NN) for estimating battery RUL. In the evaluation of the proposed method, the effectiveness is assessed using the metrics of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). …”
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15
A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources
Published 2025“…A smart memory-based strategy is incorporated into the algorithm to enhance solution optimality, convergence properties, and exploitation capabilities. …”
Review -
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Particle swarm optimization for NARX structure selection: application on DC motor model / Mohd Ikhwan Abdullah
Published 2010“…This thesis was presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. …”
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17
Estimation of transformers Health Index based on the Markov Chain
Published 2017“…Next, the average HI for each age was computed and the transition probabilities were obtained based on a nonlinear optimization technique. Finally, the future deterioration performance curve of the transformers was determined based on the MM chain algorithm. …”
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18
Probabilistic load flow�based optimal placement and sizing of distributed generators
Published 2023“…Electric load flow; Environmental impact; Genetic algorithms; Investments; Location; Operating costs; Probability distributions; Distributed generation; Distributed generation resources; Distributed generators; Distribution network; Electrical energy demand; Flow based; Location optimization; Optimal placement and sizings; Probabilistic load flow; Distributed power generation…”
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Orthogonal Frequency Division Multiple Access resource unit allocation algorithms for IEEE 802.11AX medium access control protocol
Published 2024“…First is the Versatile Shuffle Recomputation Resource Units (VSR-RUs), which use the Fisher-Yates shuffling algorithm to optimize RU utilization and reduce collisions. …”
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20
GENETIC FUZZY FILTER BASED ON MAD AND ROAD TO REMOVE MIXED IMPULSE NOISE
Published 2010“…The proposed method consists of three components, including fuzzy noise detection system, fuzzy switching scheme filtering, and fuzzy parameters optimization using genetic algorithms (GA) to perform efficient and effective noise removal. …”
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