Search Results - (( using estimation using algorithm ) OR ( based optimisation based algorithm ))
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1
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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Thesis -
2
Augmented model based double iterative loop techniques for integrated system optimisation and parameter estimation of large scale industrial processes
Published 1993“…The double iterative loop structures of the proposed algorithms use the real process measurement within the outer loops while the inner loops involve model based computation only. …”
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3
Fuzzy rank cluster top k Euclidean distance and triangle based algorithm for magnetic field indoor positioning system
Published 2021“…However, the problem of using the KNN algorithm is the fixed K value does not guarantee accurate estimation at every position. …”
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4
Genetic algorithm for control and optimisation of exothermic batch process
Published 2013“…As such, another approach, GA is proposed to optimise the productivity without referring to a predetermined profile, namely genetic algorithm optimiser (GAO). …”
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5
INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
Published 2023“…First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. …”
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6
The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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7
Novel techniques for voltage stability assessment and improvement in power system / Ismail Musirin.
Published 2004“…A new Evolutionary programming (EP) based acceleration search algorithm was developed to accelerate the process in estimating maximum load ability in a power system. …”
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8
Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search
Published 2014“…These problems resulted in estimation errors and high computational cost. Hybrid genetic algorithm (GA) and Nelder-Mead local search mode 1 has been used to minimize demand estimation errors. …”
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9
Analysis of the ECG signal using SVD-based parametric modelling technique
Published 2011“…A two-stage procedure is then used to estimate the EDS model parameters. Prony’s algorithm is first used to obtain initial estimates of the model, while the Gauss-Newton method is applied to solve the non-linear least-square optimisation problem. …”
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Proceeding Paper -
10
An extended adaptive mechanism of evolutionary based channel assignment via reinforcement
Published 2012“…Initial channel assignment parameters are obtained using self-learning scheme and evolutionary algorithms is used to fine-tune the estimated parameters from reinforcement learning algorithm to optimise the channel assignment problem in wireless mobile networks. …”
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Research Report -
11
Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor
Published 2008“…An estimation method based on the back EMF and flux estimation is presented to calculate the rotor position for medium to high speed. …”
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12
Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…Consequently, seeking managing of reservoir optimisation operations had always been at the forefront and to improve managing, algorithms have had been presented over the past few decades, beginning with conventional algorithms, followed by heuristic algorithms, and finally, the meta-heuristic algorithms (MHAs). …”
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Final Year Project / Dissertation / Thesis -
13
Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…The estimation of SL values was achieved using inputs of previous SL and streamflow values provided to the models. …”
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14
Using genetic algorithms to optimise land use suitability
Published 2012“…The Erosion Potential Method (EPM) used in erosion estimation and sediment yield of the study. …”
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15
Gravitational Search Algorithm Based LSTM Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction With Uncertainty
Published 2025“…An accurate estimation of the remaining useful life (RUL) and capacity of lithium-ion batteries (LIBs) can guarantee safe and reliable operation and help to make wise replacement decisions. …”
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16
Optimal control of batch reactors using generic model control (GMC) and neural network
Published 2000“…Neural Network technique is used as the on-line estimator to estimate the amount of heat released by the chemical reaction. …”
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17
Development of a particle swarm optimisation model for estimating the homogeneity of a mixture inside a newly designed CNG-H2-AIR mixer for a dual fuel engine: an experimental and...
Published 2018“…The basis of the proposal model (empirical equation) is from the best values determined for the unknown constant F so that the equation for UI estimation could be formulated. The particle swarm optimisation (PSO) algorithm was used to solve an optimisation problem and achieve this outcome. …”
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18
Improvement of routing protocol in wireless sensor network for energy consumption to maximize network lifetime
Published 2013“…This document is a study about hierarchical cluster-based routing protocol algorithm where the implementation was done using Matlab simulator to study the performance of this algorithm in term of lifetime. …”
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19
Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…The advantage of using these algorithms is obvious as they would speed up the computation to obtain higher accuracy with less computation effort. …”
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20
PATCH-IQ: A Patch Based Learning Framework For Blind Image Quality Assessment
Published 2017“…Most well-known blind image quality assessment (BIQA) models usually follow a two-stage framework whereby various types of features are first extracted and used as an input to a regressor. The regression algorithm is used to model human perceptual measures based on a training set of distorted images. …”
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