Search Results - (( model mitigating ((a algorithm) OR (_ algorithm)) ) OR ( based replication swarm algorithm ))*

Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity by Ghasemi, Sepehr, Raja Ahmad, Raja Mohd Kamil, Marhaban, Mohammad Hamiruce

“…The dominant saturation nonlinearity is in the transducers, which can be represented by a Wiener model. An effective solution to mitigate such nonlinear distortion is to employ the Nonlinear Filtered-X Least Mean Square (NLFXLMS) algorithm. …”
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Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity by Dehkordi, Sepehr Ghasemi

“…The dominant saturation nonlinearity in the transducers is the loudspeaker which can be represented by a Wiener model. An effective solution to mitigate such nonlinearly distortion is to employ the Nonlinear Filtered-X Least Mean Square (NLFXLMS) algorithm. …”
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A novel peak shaving algorithm for islanded microgrid using battery energy storage system by Uddin, M., Romlie, M.F., Abdullah, M.F., Tan, C., Shafiullah, G.M., Bakar, A.H.A.

“…Effectiveness of the proposed algorithm was tested with a BESS-based MATLAB/Simulink model of an actual microgrid under realistic load conditions which were recorded. …”
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A novel peak shaving algorithm for islanded microgrid using battery energy storage system by Uddin, Moslem, Romlie, M.F., Abdullah, M.F., Tan, Chia Kwang, Shafiullah, G.M., Bakar, Ab Halim Abu

“…Effectiveness of the proposed algorithm was tested with a BESS-based MATLAB/Simulink model of an actual microgrid under realistic load conditions which were recorded. …”
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A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system by Rana, M.M., Romlie, M.F., Abdullah, M.F., Uddin, M., Sarkar, M.R.

“…The proposed algorithm has been tested with the designed IMG model. …”
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A sequential handwriting recognition model based on a dynamically configurable convolution recurrent neural network and hybrid salp swarm algorithm by Ahmed Ali Mohammed, Al-saffar

“…This research present a dynamic configurator of the CRNN (DC-CRNN), geared for sequence learning in the context of handwriting recognition, inspired by bio-inspired approaches. The built DCCRNN is based on the Salp Swarm optimization Algorithm (SSA), a processor that given a particular dataset will find the best CRNN’s structure and hyperparameters. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…This proposed algorithm also discerned linear and nonlinear subsystem variables within a continuous-time Hammerstein model utilizing input and output data. …”
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms by Almubaidin M.A., Ahmed A.N., Sidek L.M., AL-Assifeh K.A.H., El-Shafie A.

“…Each algorithm was integrated into a reservoir simulation model, focusing on finding optimal rule curves for the Mujib reservoir in Jordan from 2004 to 2019. …”

A new soft computing model for daily streamflow forecasting by Sammen S.S., Ehteram M., Abba S.I., Abdulkadir R.A., Ahmed A.N., El-Shafie A.

Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

“…Several machine learning models and related algorithms were developed for prediction of total cases and total deaths. …”
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Performance comparison of different machine learning algorithms on a time-series of covid-19 data: A case study for Saudi Arabia by Ahmad, M.T., Qaiyum, S., Alamri, A., Islam, S.

“…Several machine learning models and related algorithms were developed for prediction of total cases and total deaths. …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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Exploring nexus of social media algorithms, content creators, and gender bias: a systematic literature review by Lou, Shijun, Adzharuddin, Nor Azura, Syed Zainudin, Sharifah Sofiah, Omar, Siti Zobidah

“…The application of varied research methodologies, including experiments, surveys, and content analyses, facilitates a thorough examination of algorithmic impacts. …”
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Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…Comparing machine learning algorithms yields insights. The ElasticNet model predicts building damage grade with 92.56 test accuracy and 92.67 train accuracy. …”
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Photovoltaic shunt active power filter based on indirect self-charging with step size error cancellation and simplified adaptive linear neuron by Mohd Zainuri, Muhammad Ammirrul Atiqi

“…Therefore, this research work proposes design and development of single-phase PV SAPF with a new DC-link capacitor voltage control algorithm named as indirect self- charging with step size error cancellation, and a new harmonics extraction algorithm named as simplified ADALINE. …”
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Resource allocation techniques for interference mitigation in macro and femtocell heterogeneous network-based LTE system by Al-omari, Motea Saleh Mohammed

“…The first proposed hybrid approach consists of two combined schemes, termed as Resource Allocation based Fractional Frequency Reuse and Graph Connectivity algorithm (RAFFRGC). The second proposed interference mitigation technique is a full frequency reuse termed as Resource Allocation based Cuckoo Search Algorithm (RACSA). …”
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Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms by Essam Y., Huang Y.F., Ng J.L., Birima A.H., Ahmed A.N., El-Shafie A.

Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…Drawing from an extensive review of existing predictive models and cardiovascular health risk factors, this research proposes an enhanced ADAM optimization algorithm, integrated with advanced data processing and feature selection methodologies, to identify and refine key predictors for improved model performance. …”
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Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach by Khan, Arshad Ali, Mazlina, Abdul Majid, Dandoush, Abdulhalim

“…These improvements underscore the effectiveness of Genetic Algorithms in optimizing the model.…”
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Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster by Afan H.A., Yafouz A., Birima A.H., Ahmed A.N., Kisi O., Chaplot B., El-Shafie A.