Search Results - (( data application using algorithm ) OR ( parameter adoption using algorithm ))
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1
Evaluation of outlier filtering algorithms for accurate measurement of travel time reliability incorporating lane-splitting situations / Obada M. A. Asqool
Published 2022“…Thus, the Jang algorithm and TransGuide algorithm could be used after calibrating their parameters for each day. …”
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Thesis -
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Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm
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Student Project -
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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4
Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization
Published 2022“…It adopts a population-based and local search algorithm to exploit the advantages of bats’ echolocation. …”
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5
Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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6
Evolutionary algorithm approach for solving animal diet formulation
Published 2015“…Experimentation on what-if scenario has proven that this evolutionary model is robust as it can adopt to changes in the parameter.…”
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7
Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…A 20-fold cross-validation was used to validate the score metrics. Almost all the algorithms score 85% and above in terms of accuracy, precision and recall…”
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8
Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
Published 2024journal::journal article -
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Effective use of artificial intelligence by Malaysian manufacturing firms to enable sustainability 4.0
Published 2023“…In this project, Fornell-Larker parameters are used to test the measurement algorithm for the research's discriminant validity. 380 valid questionnaires returnedback and conducted the calculation of the algorithm's assessment to constructs' validity and realibility assessment, discriminant validity using HTMTand Fornell-Larker approaches. …”
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Final Year Project / Dissertation / Thesis -
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Regionalization by fuzzy expert system based approach optimized by genetic algorithm.
Published 2013“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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11
Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises
Published 2020“…After it has worked properly, it was applied to model human heart rate data. The results showed that the MCMC algorithm can estimate the parameters of the MA model. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
Published 2013“…We exploit the rank deficient of H to reduce the number of parameters that characterizes this matrix. The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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14
Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks
Published 2014“…The third scheme works on the self optimization of handover parameters using fuzzy logic control (FLC) and multiple preparation (MP) called FuzAMP. …”
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15
Wavelet network based online sequential extreme learning machine for dynamic system modeling
Published 2013“…Wavelet network (WN) has been introduced in many applications of dynamic systems modeling with different learning algorithms. …”
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16
Fuzzy Type-1 Triangular Membership Function Approximation Using Fuzzy C-Means
Published 2020“…This research focuses on generating the parametric values of the triangular membership function using a novel method. Initially, the Fuzzy C-means algorithm is utilized to generate the parameters values of the Gaussian membership function. …”
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17
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms
Published 2011“…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
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20
A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2015“…In order to investigate the expected functionality of the required standard, the prediction of the effluent quality, namely biological oxygen demand, chemical oxygen demand and total suspended solid of an SSTP was modelled using an artificial intelligence approach. In this paper, we adopt the clonal selection algorithm (CSA) to set up a prediction model, with a wellestablished method – namely the least-square support vector machine (LS-SVM) as a baseline model. …”
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