voltage stability issues are growing challenges in many modern power systems. this paper proposes optimizing the size and location of static var compensator (svc) devices using a fuzzy weighted seeker optimization algorithm (fwsoa), as an effective solution to overcome such issues. although the primary purpose of svc is bus voltage regulation, it can also be useful for voltage stability enhance...

The wind turbine has grown out to be one of the most common Renewable Energy Sources (RES) around the world in recent years. This study was intended to position the Wind Turbine (WT) on a wind farm to achieve the highest performance possible in Electric Distribution Network (EDN). In this paper a new optimization algorithm namely Salp Swarm Algorithm (SSA) is applied to solve the problem of opt...

Considering the great significant role that routing protocols play in transfer rate and choosing the optimum path for exchange of data packages, and further in the amount of consumed energy in the routing protocol, the present study has focused on developing an efficient compound energy algorithm based on cluster structure which is called active node with cluster structure. The purpose of this ...

materials and methods the expression of hyaluronidase antigenic fragments was optimized using iptg concentration, time of induction, temperature, culture, and absorbance of 0.6-0.8-1 at 600 nm. afterwards, the expressed proteins were purified and the enzymatic activity was assessed by turbid metric method. results data indicated that maximum protein is produced in od = 0.8, 0.5 mm isopropyl β-d...

optimization techniques can be efficiently utilized to achieve an optimal shape for arch dams. this optimal design can consider the conditions of the economy and safety simultaneously. the main aim is to present an applicable and practical model and suggest an algorithm for optimization of concrete arch dams to enhance their seismic performance. to achieve this purpose, a preliminary optimizati...

In this study, a multiobjective optimization is applied to Optimal Power Flow Problem (OPF). To effectively achieve this goal, a Multiobjective Ant Lion algorithm (MOALO) is proposed to find the Pareto optimal front for the multiobjective OPF. The aim of this work is to reach good solutions of Active and Reactive OPF problem by optimizing 4-conflicting objective functions simultaneously. Here a...

When a robotic system is faced with uncertainty, the must take calculated risks to gain information as efficiently possible while ensuring safety. The need safely and in face of uncertainty spans domains from healthcare search rescue. To learn when data scarce or difficult label, active learning acquisition functions intelligently select point that, if label were known, would most improve estim...

Active learning (AL) aims to find a better trade-off between labeling costs and model performance by consciously selecting more informative samples label. Recently, adversarial approaches have emerged as effective solutions. Most of them leverage generative networks align feature distributions labeled unlabeled data, upon which discriminators are trained distinguish them. However, these methods...