Search Results - (( adaptive k difference evolution algorithm ) OR ( adaptive two different estimation algorithm ))*
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Techno-economic evaluation of off-grid hybrid renewable energy system for rural resort electrification in Malaysia / Monowar Hossain
Published 2017“…For these purposes, the standalone ANFIS, ANFIS-PSO (particle swarm optimization),ANFIS-GA (genetic algorithm) and ANFIS-DE (differential evolution) prediction algorithms have been developed in MATLAB platform. …”
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Digital quadrature compensators scheme for analog imperfections of quadrature modulator in wireless communication systems
Published 2016“…Adaptive algorithms used to estimate the QM’s imperfections, operate either in online or offline mode. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…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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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…A new algorithm of coordinate gradient descent (CGD) is developed to optimize the adaptive LASSO. …”
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Speed sensorless control of permanent magnet synchronous motor using model reference adaptive system and artificial neural network / Abdul Mu’iz Nazelan
Published 2019“…However, conventional adaptation scheme such as PI controller reduce the estimation accuracy for speed and position of the PMSM. …”
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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor
Published 2008“…The proposed controller is a hybrid model reference adaptive speed controller (HMRASC) which mainly consists of two functional blocks. …”
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A new LoRa based positioning algorithm utilizing sequence based deep learning technique
Published 2023“…Furthermore, an analysis of classification using different sequence length is done. Then, a new positioning algorithm is developed which incorporates distance estimation, Kalman Filter and trilateration technique according to the classification with different sequence length data and the positioning error is being analysed. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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Estimation of Examinees' Ability Through Computer Adaptive Testing Based on Neural Network Approach
Published 2010“…This work has been organized in two phases. In the first phase, we use 3-PL (three parameter logistic) dichotomous and polytomous model of IRT to estimate examinees’ ability in adaptive testing. …”
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Performance Analysis of a Real-Time Adaptive Prediction Algorithm for Traffic Congestion
Published 2018“…The approaches choose between five different prediction algorithms using the Root Mean Square Error model selection criterion. …”
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Channel quality indicator for long term evolution system based on adaptive threshold feedback compression scheme
Published 2014“…The percentage difference is 2.1%,compared with the full feedback method, with only 0.5% degradation. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
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Advanced online battery states coestimation using Kalman filter for electric vehicle Applications / Prashant Shrivastava
Published 2021“…Due to the existing correlation between the battery states, the co-estimation method for different battery states estimation is preferred over individual state estimation. …”
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