El-Sayed M. El-kenawy¹, Hattan F. Abutarboush², Ali Wagdy Mohamed^3,4, Abdelhameed Ibrahim^5,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2983-2995, 2021, DOI:10.32604/cmc.2021.019114

Abstract Machine learning (ML) has taken the world by a tornado with its prevalent applications in automating ordinary tasks and using turbulent insights throughout scientific research and design strolls. ML is a massive area within artificial intelligence (AI) that focuses on obtaining valuable information out of data, explaining why ML has often been related to stats and data science. An advanced meta-heuristic optimization algorithm is proposed in this work for the optimization problem of antenna architecture design. The algorithm is designed, depending on the hybrid between the Sine Cosine Algorithm (SCA) and the Grey Wolf Optimizer (GWO), to train neural network-based… More >

Adel Hamdan Mohammad^*

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 65-80, 2021, DOI:10.32604/iasc.2021.016140

Abstract Intrusion detection is an important topic that aims at protecting computer systems. Besides, feature selection is crucial for increasing the performance of intrusion detection. This paper employs a new hybrid feature selection model for intrusion detection. The implemented model uses Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms in a new manner. In addition, this study introduces two new models called (PSO-GWO-NB) and (PSO-GWO-ANN) for feature selection and intrusion detection. PSO and GWO show emergent results in feature selection for several purposes and applications. This paper uses PSO and GWO to select features for the intrusion detection system.… More >

A. M. Abdullah¹, Hegazy Rezk^2,3,*, Abdelrahman Elbloye¹, Mohamed K. Hassan^1,4, A. F. Mohamed^1,5

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 729-740, 2021, DOI:10.32604/iasc.2021.018595

Abstract The energy harvested from a thermoelectric generator (TEG) relies mostly on the difference in temperature between the hot side and cold side of the TEG along with the connected load. Hence, a reliable maximum power point tracker is needed to force the TEG to operate close to the maximum power point (MPP) with any variation during the operation. In the current work, an optimized fractional maximum power point tracker (OFMPPT) is proposed to improve the performance of the TEG. The proposed tracker is based on fractional control. The optimal parameters of the OFMPPT have been determined using the grey wolf… More >

Rabii Fessi¹, Hegazy Rezk^2,3,*, Soufiene Bouallègue^1,4

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2265-2282, 2021, DOI:10.32604/cmc.2021.017237

Abstract The research on Unmanned Aerial Vehicles (UAV) has intensified considerably thanks to the recent growth in the fields of advanced automatic control, artificial intelligence, and miniaturization. In this paper, a Grey Wolf Optimization (GWO) algorithm is proposed and successfully applied to tune all effective parameters of Fast Terminal Sliding Mode (FTSM) controllers for a quadrotor UAV. A full control scheme is first established to deal with the coupled and underactuated dynamics of the drone. Controllers for altitude, attitude, and position dynamics become separately designed and tuned. To work around the repetitive and time-consuming trial-error-based procedures, all FTSM controllers’ parameters for… More >

Xianghui Lu¹, Junliang Fan², Lifeng Wu^1,*, Jianhua Dong³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 699-723, 2020, DOI:10.32604/cmes.2020.011004

Abstract It is important for regional water resources management to know the agricultural water consumption information several months in advance. Forecasting reference evapotranspiration (ET₀) in the next few months is important for irrigation and reservoir management. Studies on forecasting of multiple-month ahead ET₀ using machine learning models have not been reported yet. Besides, machine learning models such as the XGBoost model has multiple parameters that need to be tuned, and traditional methods can get stuck in a regional optimal solution and fail to obtain a global optimal solution. This study investigated the performance of the hybrid extreme gradient boosting (XGBoost) model… More >

G. R. Venkatakrishnan^1,*, R. Rengaraj², S. Salivahanan³

CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 25-45, 2018, DOI:10.3970/cmes.2018.115.025

Abstract A new and efficient Grey Wolf Optimization (GWO) algorithm is implemented to solve real power economic dispatch (RPED) problems in this paper. The nonlinear RPED problem is one the most important and fundamental optimization problem which reduces the total cost in generating real power without violating the constraints. Conventional methods can solve the ELD problem with good solution quality with assumptions assigned to fuel cost curves without which these methods lead to suboptimal or infeasible solutions. The behavior of grey wolves which is mimicked in the GWO algorithm are leadership hierarchy and hunting mechanism. The leadership hierarchy is simulated using… More >