Search Results - (( parameter optimization method algorithm ) OR ( variable optimization technique algorithm ))*
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1
Optimization of turning parameters using ant colony optimization
Published 2008“…This project proposed a new optimization technique based on the ant colony algorithm for solving single-pass turning optimization problems. …”
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Undergraduates Project Papers -
2
Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Thesis -
3
A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant
Published 2023Subjects:Conference paper -
4
Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
Article -
5
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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Thesis -
6
OPTIMIZATION OF DESIGN PARAMETERS FOR A VARIABLE FREQUENCY 3-PHASE INDUCTION MOTOR
Published 2009“…This report describes the method of optimizing a variable frequency 3-phase Induction Motor. …”
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Final Year Project -
7
A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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Thesis -
8
Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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Thesis -
9
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…Due to the high complexity of these problems, metaheuristic based global optimization techniques are usually required. One of the more recent global optimization tools in the area of discrete optimization is known as the discrete filled function method. …”
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Thesis -
10
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Thesis -
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…This approach was based on fuzzy expert system (FES) using Fuzzy Toolbox of MATLAB software. Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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Thesis -
13
Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm
Published 2025“…The MSCA method is validated using the IEEE 30-bus test case, focusing on optimal parameter tuning for population size, iterations, and key variables. …”
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Article -
14
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
Article -
15
A Stepper Motor Design Optimization Using
Published 2005“…GAs approach is selected because it is a powerful and broadly applicable stochastic search and optimization techniques that works for many problems that are very difficult to solve by conventional methods. …”
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Monograph -
16
Fuzzy modelling and control for a nonlinear reboiler system of a distillation column
Published 2006“…Genetic algorithm (GA) is used to tune the parameters of the Fuzzy controller. …”
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Thesis -
17
To develop an efficient variable speed compressor motor system
Published 2007“…To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. …”
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Other -
18
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…A spatio-statistical optimization technique that combines the Taguchi statistical method and a spatial plateau objective function (POF) was presented to improve the segmentation procedures for building footprint extraction. …”
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Thesis -
19
Power System State Estimation In Large-Scale Networks
Published 2010“…The Weighted Least Squares (WLS) method is the most popular technique of SE. This thesis provides solutions to enhance the WLS algorithm in order to increase the performance of SE. …”
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Thesis -
20
Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm
Published 2022“…Therefore, in this paper, we enhance the GMDH model by implementing the ABC algorithm to optimize the parameter of partial description GMDH model with some transfer functions, namely polynomial, radial basis, sigmoid and hyperbolic tangent function. …”
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