In this paper, an artificial-based optimizes and analysis of an optimal proportional, integral, derivative (PID) controller is introduced for a hydro-turbine generator governor. The main purpose, optimization PID controller parameters of hydro-turbine connected to the network for damping output frequency oscillation. In The proposed approach, an optimal and evolutionary based proportional, inte...

There are several major threats to crop production. As herbicide use has become overly reliant on weed control, herbicide-resistant weeds have evolved and pose an increasing threat the environment, food safety, human health. Convolutional neural networks (CNNs) demonstrated exceptional results in analysis of images for identification from that captured by drones. Manually designing such archite...

Clustering is an unsupervised learning method that is used to group similar objects. One of the most popular and efficient clustering methods is K-means, as it has linear time complexity and is simple to implement. However, it suffers from gets trapped in local optima. Therefore, many methods have been produced by hybridizing K-means and other methods. In this paper, we propose a hybrid method ...

The genetic basis of weedy and invasive traits and their evolution remain poorly understood, but genomic approaches offer tremendous promise for elucidating these important features of weed biology. However, the genomic tools and resources available for weed research are currently meager compared with those available for many crops. Because genomic methodologies are becoming increasingly access...

This paper proposes the application of differential evolution (DE) algorithm for the optimal tuning of proportional-integral (PI) controller designed to improve the small signal dynamic response of a stand-alone solid oxide fuel cell (SOFC) system. The small signal model of the study system is derived and considered for the controller design as the target here is to track small variations in SO...