Search Results - (( data application testing algorithm ) OR ( parameter extraction method algorithm ))

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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Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines by K.S.R., Rao, Z.F., Desta

“…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

“…The two diode model of a solar cell is used as the basis for the extraction problem. The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

“…This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. …”

CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…To overcome these ANN problems, the Genetic Algorithm (GA) has been most frequently used for this purpose, however, some drawbacks of GA include, slow search speed and dependence on initial parameters. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail, M.S., Moghavvemi, Mahmoud, Mahlia, T.M.I.

“…This paper details an improved modeling technique for a photovoltaic (PV) module; utilizing the optimization ability of a genetic algorithm, with different parameters of the PV module being computed via this approach. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…On the other hand, when we use computers to reduce uncertainty, the computer itself can become an expert in a specific field through a variety of methods. One such method is machine learning, which involves computer algorithm to capture hidden knowledge from data. …”
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Recent advancement of remaining useful life prediction of lithium-ion battery in electric vehicle applications: A review of modelling mechanisms, network configurations, factors, a... by Reza M.S., Mannan M., Mansor M., Ker P.J., Mahlia T.M.I., Hannan M.A.

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An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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Scene illumination classification based on histogram quartering of CIE-Y component by Hesamian, Mohammad Hesam

“…This method is a combination of physic based methods and data driven (statistical) methods that categorize the images based on statistical features extracted from illumination histogram of image. …”
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Non-fiducial based ECG biometric authentication using one-class support vector machine by Hejazi, Maryamsadat, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari, Abdul Aziz, Ahmad Fazli, Singh, Yashwant Prasad

“…This paper investigates the effect of different parameters of data set size, labeling data, configuration of training and testing data sets, feature extraction, different recording sessions, and random partition methods on accuracy and error rates of these SVM classifiers. …”
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The evolution of spectral analysis of surface wave method – a review by Mannan Mitu, Sadia Mannan Mitu, Abd. Rahman, Norinah, Mohd Taib, Aizat, Ramli, Ahmad Bukhari, Abang Hasbollah, Dayang Zulaika

“…Precise recording of amplitude value has the potential to further improve the effectiveness and develop the surface wave testing methods. Different approaches for interpreting the dispersion curve and their potential regarding sensitivity to noise, reliability, and capability to extract significant information were investigated. …”
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A New Intelligent Autoreclosing Scheme Using Artificial Neural Network and Taguchi's Methodology by K.S.R., Rao, Fitiwi, Desta Zahlay, Ibrahim, Taib

“…FFT and Prony analysis methods are employed to extract data features from each simulated fault. …”
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A New Intelligent Autoreclosing Scheme Using Artificial Neural Network and Taguchi’s Methodology by Fitiwi, Desta Zahlay, K. S., Rama Rao, Taib , Ibrahim

“…FFT and Prony analysis methods are employed to extract data features from each simulated fault. …”
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Edge detection of MRI images using artificial neural network by Gunawan, Teddy Surya, Kartiwi, Mira, Abdul Malik, Noreha

“…Introduction Many methods have been proposed for MRI tissue segmentation. …”
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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…”

Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

“…Conventionally, agarwood essential oil is graded manually by a human expert sensory panel based on its physical properties such as odor, color intensity and infection level. The method for obtaining the quality of agarwood oil is time consuming due to the large number of test samples. …”
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Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

“…Nowadays there are many related efforts in detecting spliced images, but most of them are either feature-specific or complicated algorithms. Constrained CNN is basically a Deep Learning CNN model with its first layer weights being constrained so that it only extracts splicing manipulation features instead of object features. …”
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Oil palm maturity classifier using spectrometer and machine learning by Goh, Jia Quan

“…The prediction was able to produce 100% accuracies by using Linear and Weighted KNN as classification testing algorithm. An application was built by using the NDVI prediction model. …”
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Baharuddin M.Z., Lee H.J., Omar A.R.

“…These works have shown that, despite using only the optical chromaticity of the chicken comb as the input data, the developed models (95% accuracy) have performed exceptionally well, compared to other reported results (99.469% accuracy) which utilize more sophisticated input data such as morphological and mobility features. …”