Search Results - adaptive model difference ((extraction algorithm) OR (selection algorithm))

Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…However, the learning complexity of classification is increased due to the expansion number of learning model. 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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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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Boundary extraction of abnormality region in breast mammography image using active contours by Mohd Ghani, Noor Ain Syazwani, Jumaat, Abdul Kadir, Mahmud, Rozi

“…Active contour method has been proven to be effective to extract boundary of an image. The recent and effective selective type of active contour model, termed Primal Dual Selective Segmentation (PDSS) model, was proposed in 2019. …”
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

“…By evaluating the model on food dataset FOOD101, extracting of features take 80.23 seconds and classifying and training of incremental algorithm take 1253.36 seconds with 77.72% test accuracy. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…The proposed feature selection technique comprises of Multi-objective Binary-valued Backtracking Search Algorithm (MOBBSA). …”
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Design, Modelling And Control Of Hybrid Energy Storage System For Electric Vehicles by Taha Mohammed, Ahmed Sadeq

“…The proposed control algorithms were tested in three real drive cycles (uphill, downhill, and city-tour) at three different speeds (50, 60, and 70 Km/h) and in three different standard drive cycles (UDDS, NYCC, and Japan1015). …”
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Boundary extraction of abnormality region in breast mammography image using active contours / Noor Ain Syazwani Mohd Ghani, Abdul Kadir Jumaat and Rozi Mahmud by Mohd Ghani, Noor Ain Syazwani, Jumaat, Abdul Kadir, Mahmud, Rozi

“…Active contour method has been proven to be effective to extract boundary of an image. The recent and effective selective type of active contour model, termed Primal Dual Selective Segmentation (PDSS) model, was proposed in 2019. …”
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A New Substitution Box From Quranic Maqamat by Muhammad Fahim Bin Roslan

Novel parameter extraction for single, double, and three diodes photovoltaic models based on robust adaptive arithmetic optimization algorithm and adaptive damping method of Berndt... by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya'acob, Mohammad Effendy, Ahmadipour, Masoud

“…In this work, we present a robust adaptive Arithmetic Optimization Algorithm based on the adaptive damping Berndt-hall-hall-Hausman (RaAOAAdBHHH) approach to efficacity determine the parameters of the single, double, and three diode PV model. …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

“…The K-means++ clustering algorithm generates candidate bounding boxes, adapting to defects of different sizes and selecting finer features earlier. …”
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An Education-Based System for Two-Way Translations of Sign Language by Muhammad Faiz Aiman, Che Umar, Hock Tze, Wong@ Farrah Wong, Sariah, Abang, Jamal, Ahmad Dargham, Seng Kheau, Chung, Mazlina, Mamat

“…The 2D CNN algorithm is selected and implemented in six steps, including data acquisition from a dataset of 28 different static sign language signs obtained from Kaggle. …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

“…Data arrives from operational field in a stream model and similarity-based classification algorithms must identify them with acceptable performance. …”
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A comparative study for parameter selection in online auctions by Gan, Kim Soon

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Simplified adaptive linear neuron harmonics extraction algorithm for dynamic performance of shunt active power filter by Mohd Zainuri, Muhammad Ammirrul Atiqi, Mohd Radzi, Mohd Amran, Che Soh, Azura, Mariun, Norman, Abd Rahim, Nasrudin

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

A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process by Kong, Hong Shim

“…A neural-fuzzy model has been developed to represent machinability data selection in turning process. …”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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