Under harsh geographical conditions where manned flight is not possible, the ability of unmanned aerial vehicle (UAV) to successfully carry out payload hold–release mission by avoiding obstacles depends on optimal path planning and tracking performance UAV. The UAV plan track with minimum energy time consumption possible using parameters. This study performs optimum Harris hawk optimization (HH...

Artificial Neural Networks (ANNs) are utilized to solve a variety of problems in many domains. In this type network, training and selecting parameters that define networks architecture play an important role enhancing the accuracy network's output; Therefore, Prior training, those must be optimized. Grey Wolf Optimizer (GWO) has been considered one efficient developed approaches Swarm Intellige...

Purpose: The development of metaheuristic algorithms has increased by researchers to use them extensively in the field business, science, and engineering. One common optimization is called Grey Wolf Optimization (GWO). algorithm works based on imitation wolves' searching process attacking grey wolves. main purpose this paper overcome GWO problem which trapping into local optima. Design or Metho...

Metaheuristic algorithms are widely used for optimization in both research and the industrial community simplicity, flexibility, robustness. However, multi-modal is a difficult task, even metaheuristic algorithms. Two important issues that need to be handled solving problems (a) categorize multiple local/global optima (b) uphold these till ending. Besides, robust local search ability also prere...

Abstract In view of the time-series characteristics grid load data, this paper proposes a method to predict electricity demand by optimizing long-and short-term memory (LSTM) neural network model using grey wolf optimization algorithm, taking into account effects time, weather conditions and holiday on loads. The overcomes disadvantage that backpropagation through time algorithm tends converge ...

Many feature subset selection algorithms have been proposed, but not all of them are appropriate for a given feature selection problem. At the same time, so far there is rarely a good way to choose appropriate feature subset selection algorithms for the problem at hand. Feature selection has become an essential element in the Data Mining process. In this paper, investigate the problem of effici...

Biometric authentication has been getting widespread attention over the past decade with growing demands in automated secured personal identification. Continuous Authentication (CA) system verifies the user continuously once a person is logged in. Continuous Authentication system prevents the intruders from invoking the system. A new framework for continuous user authentication that primarily u...

Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization lifetime is a challenge. This study evaluates ...