Search Results - (( parameter extraction method algorithm ) OR ( parameters deviations methods algorithm ))

On the problem formulation for parameter extraction of the photovoltaic model: novel integration of hybrid evolutionary algorithm and Levenberg Marquardt based on adaptive damping... by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya'acob, Mohammad Effendy, Ahmadipour, Masoud, Ismaeel, Nooruldeen Q.

“…This paper presents an approach to determine the nine parameters of the three diode (TD) PV model based on the integration of the guaranteed convergence arithmetic optimization algorithm and Levenberg-Marquardt with adaptive damping nonlinear parameter method named as GCAOAAdLM. …”
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High Order Polynomial Surface Fitting for Measuring Roughness of Psoriasis Lesion by Ahmad Fadzil, Mohd Hani

“…In this paper, an objective 3D imaging method is proposed to assess PASI scaliness parameter of psoriasis lesions. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

“…This algorithm consists of (i) Gaussian smoothness standard deviation method that formulates informative features within sky images; (ii) nearest-threshold based technique that converts feature map into a weighted directed graph to represent relationship between features; and (iii) an ant colony system with self-adaptive parameter technique for local pheromone update. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Monitoring and assessment of weld penetration condition during pulse mode laser welding using air-borne acoustic signal by Mohd Fadhlan, Mohd Yusof

“…To develop the signal processing algorithm, multi-lag phase space (MLPS) method was adopted in which some modifications on its original algorithm were made by introducing the localized crest factor (CF) thresholding method to reduce the influence of noise. …”
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Antifriction Bearing Malfunction Detection and Diagnostics using Hybrid Approach by Omar, Noraimi

“…Various statistical features are extracted from the time domain namely kurtosis, skewness, root mean square, standard deviation, crest factor and Abbott parameters to analyse and identify the bearing fault. …”
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Antifriction Bearing Malfunction Detection and Diagnostics using Hybrid Approach by Omar, Noraimi

“…Various statistical features are extracted from the time domain namely kurtosis, skewness, root mean square, standard deviation, crest factor and Abbott parameters to analyse and identify the bearing fault. …”
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Fault detection and diagnosis using rule-based support system on fatty acid fractionation column by Yann, H. H., Ali, Mohamad Wijayanuddin, Kamsah, Mohd Zaki

“…Process history based methods (rule-based feature extraction) is used to implement the FDD rule-based support system. …”
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Establishment of spectral subtraction-based algorithm for experimental modal analysis under operating condition by Che Ku Eddy Nizwan, Che Ku Husin

“…An effective ambient magnitude parameter was introduced to improvise the gain factor in the spectral subtraction filter. …”
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Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah by Aziz Shah, Mohamad Azam Shah

“…In other words, the implementation of a multidimensional analysis to increase the knowledge of the uncertain parameters is undoubtedly necessary for the success of the SMU method. …”
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Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi by Hashim, Hadzli, Abdul Hadi, Razali

“…In this report, several psoriasis lesion group are been studied for grayscale color features extraction. The experimental work involved clinical guttate lesion images where they are processed to produce the average Gaussian mean and standard deviation indices using the conventional algorithm. …”
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Hearing disorder detection using auditory evoked potential (AEP) signals by Islam, Md Nahidul, Norizam, Sulaiman, Rashid, Mamunur, Bari, Bifta Sama, Mahfuzah, Mustafa

“…The obtained feature sets have been classified by the K-Nearest Neighbors (K-NN) algorithm. Different types of the parameter of K-NN have been investigated also to achieve the best outcome. …”
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Intelligent fault diagnosis for broken rotor bar using wavelet packet signature analysis by Zolfaghari, Sahar

“…The fault detection and classification algorithm is carried out under the unknown dataset and the off-line testing results with 98.8% classification accuracy indicate good reliability of the proposed method in identifying broken rotor bars severity.…”
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Dataset size and dimensionality reduction approaches for handwritten farsi digits and characters recognition / Mohammad Amin Shayegan by Shayegan, Mohammad Amin

“…In other part of this study, the number of extracted features is decreased by proposing a new method, which is, analyzing the one-dimensional and two-dimensional spectrum diagrams of standard deviation and minimum to maximum distributions for initial feature vector elements. …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…Model validity describes the first sub-objective, which is to solve the complexity of the nonlinear interaction of multiple MEC input variables related to the hydrogen production rate response using artificial neural networks (ANN) before validating the mathematical modeling results by comparing experimental data with the predicted substrate concentration profile and hydrogen production rate profile based on the re-estimated input values of the model parameters using single-objective optimization based on the nonlinear convex method using gradient descent algorithm. …”
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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

“…In this research, Multilayer perception (MLP) of feedforward Artificial Neural Network (ANN) has also been used as the classifier and comparison are made between the SVM and ANN method. The SVM results show that RBF kernel is superior to linear kernel in classifying the transient with average percentage of 83% This research has also proved that SVM has higher performance than the backpropagation algorithm of the ANN.…”
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Statistical Approach for Image Retrieval by Khor, Siak Wang

“…In this thesis, a novel method based on the modified generic framework of CBIR is proposed. …”
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.

“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”

Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

“…Algorithms; Diodes; Extraction; Iterative methods; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Different evolutions; Differential Evolution; Diode modeling; Electromagnetism-like algorithm; Extracting parameter; Hybrid evolutionary algorithm; Photovoltaic model; Photovoltaic modules; Evolutionary algorithms…”

A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems by Jui, Julakha Jahan, Mohd Ashraf, Ahmad

“…The results showed that the proposed method was efficient in identifying both the Hammerstein model subsystems in terms of the quadratic output estimation error and parameter deviation index. …”
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