[PDF][PDF] Metaheuristic Optimization of Time Series Models for Predicting Networks Traffic
R Alkanhel, ESM El-kenawy… - CMC-COMPUTERS …, 2023 - researchgate.net
Traffic prediction of wireless networks attracted many researchers and practitioners during
the past decades. However, wireless traffic frequently exhibits strong nonlinearities and …
the past decades. However, wireless traffic frequently exhibits strong nonlinearities and …
[PDF][PDF] Dipper Throated Algorithm for Feature Selection and Classification in Electrocardiogram.
Arrhythmia has been classified using a variety of methods. Because of the dynamic nature of
electrocardiogram (ECG) data, traditional handcrafted approaches are difficult to execute …
electrocardiogram (ECG) data, traditional handcrafted approaches are difficult to execute …
Solving optimization problems of metamaterial and double T-shape antennas using advanced meta-heuristics algorithms
This study offers an adaptive dynamic sine cosine fitness grey wolf optimizer (ADSCFGWO)
for optimizing the parameters of two types of antennas. The two types of antennas are …
for optimizing the parameters of two types of antennas. The two types of antennas are …
A novel improved whale optimization algorithm for optimization problems with multi-strategy and hybrid algorithm
H Deng, L Liu, J Fang, B Qu, Q Huang - Mathematics and Computers in …, 2023 - Elsevier
Whale optimization algorithm (WOA), as an advanced optimization algorithm with simple
structure, has been favored by various fields. However, there are some disadvantages of …
structure, has been favored by various fields. However, there are some disadvantages of …
[HTML][HTML] Machine learning-based technique for gain and resonance prediction of mid band 5G Yagi antenna
In this study, we present our findings from investigating the use of a machine learning (ML)
technique to improve the performance of Quasi-Yagi–Uda antennas operating in the n78 …
technique to improve the performance of Quasi-Yagi–Uda antennas operating in the n78 …
[PDF][PDF] Optimized Two-Level Ensemble Model for Predicting the Parameters of Metamaterial Antenna.
AA Abdelhamid, SR Alotaibi - Computers, Materials & Continua, 2022 - researchgate.net
Employing machine learning techniques in predicting the parameters of metamaterial
antennas has a significant impact on the reduction of the time needed to design an antenna …
antennas has a significant impact on the reduction of the time needed to design an antenna …
[PDF][PDF] Hybrid global optimization algorithm for feature selection
This paper proposes Parallelized Linear Time-Variant Acceleration Coefficients and Inertial
Weight of Particle Swarm Optimization algorithm (PLTVACIW-PSO). Its designed has …
Weight of Particle Swarm Optimization algorithm (PLTVACIW-PSO). Its designed has …
Forecasting of energy efficiency in buildings using multilayer perceptron regressor with waterwheel plant algorithm hyperparameter
Energy consumption in buildings is gradually increasing and accounts for around forty
percent of the total energy consumption. Forecasting the heating and cooling loads of a …
percent of the total energy consumption. Forecasting the heating and cooling loads of a …
Multiband and high gain meandered metamaterial THz MIMO antenna for highspeed wireless communication applications
The need for high gain and multiband THz antenna is increasing day by day as the
advancement in wireless technology and high-speed communication devices are occurring …
advancement in wireless technology and high-speed communication devices are occurring …
[HTML][HTML] A novel voting classifier for electric vehicles population at different locations using Al-Biruni earth radius optimization algorithm
The rising popularity of electric vehicles (EVs) can be attributed to their positive impact on
the environment and their ability to lower operational expenses. Nevertheless, the task of …
the environment and their ability to lower operational expenses. Nevertheless, the task of …