Search Results - adaptive a different ((estimation algorithm) OR (extraction algorithm))*

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.

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

The noise reduction algorithm for star detection by Razaman, Anis Hannani, Ahmad, Yasser Asrul, Gunawan, Teddy Surya, Khalifa, Othman Omran, Saidin, Norazlina

“…To validate the algorithm, synthetic star images with different noise levels were tested. …”
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Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process by Jahedsaravani, A., Massinaei, Mohammad, Marhaban, Mohammad Hamiruce

“…Furthermore, the metallurgical parameters of a laboratory flotation cell were successfully predicted from the extracted froth features. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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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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Adaptive template matching of photoplethysmogram pulses to detect motion artefact by Lim, Pooi Khoon, Ng, Siew Cheok, Lovell, Nigel Hamilton, Yu, Yong Poh, Tan, Maw Pin, McCombie, Devin, Lim, Einly, Redmond, Stephen James

“…The developed algorithm was evaluated against a manually annotated 'gold standard' (GS). …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

“…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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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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Fractional chaos maps with flower pollination algorithm for chaotic systems� parameters identification by Yousri D., Allam D., Babu T.S., AbdelAty A.M., Radwan A.G., Ramachandaramurthy V.K., Eteiba M.B.

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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Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation by Cheah, Kah Wai

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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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Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems by Talebpour, Faraz

“…Offline on the other hand, is a mode where adaptive algorithms cannot estimate the imperfections in parallel with the transmission. …”
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Proactive Traffic-Adaptive Tuning of Contention Window for Wireless Sensor Network Medium-Access Control Protocol by Pirborj, Nesae Mouzehkesh

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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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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…A new algorithm of coordinate gradient descent (CGD) is developed to optimize the adaptive LASSO. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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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

“…This paper presents a single-phase shunt active power filter with artificial intelligence based algorithms by introducing a new Simplified Adaptive Linear Neuron (ADALINE) algorithm for harmonics extraction. …”
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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). It is used to search within a number of input variables combinations and to select the feature subsets, which minimizes simultaneously vice-versa the estimation error and the feature numbers. …”
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