In this work, the process of dissimilar resistance spot welding (RSW) for AISI 304 and 1060 steel sheets is experimentally investigated. The effects main parameters such as current, electrode force, cycle, cooling cycle on tensile-shear strength (TSS) RSW joints are studied. To aim, using a central composite experimental design based response surface methodology (RSM), tests were performed. Fur...

Developing new optimization algorithms and data mining has improved traditional engineering structural analysis models (meaning basically swarm-based solutions). Additionally, an accurate quantification of in situ friction capacity (ISFC) driven piles is paramount importance design/construction geotechnical infrastructures. A number studies have underscored the use developed via artificial neur...

This article proposes an intelligent control strategy to enhance the frequency dynamic performance of interconnected multi-source power systems composing thermal, hydro, and gas plants high penetration level wind energy. The proposed is based on a combination fuzzy logic with proportional-integral-derivative (PID) controller overcome PID limitations during abnormal conditions. Moreover, newly a...

This paper presents a novel optimization model for the flexible-reliable operation (FRO) of energy hubs (EHs) in electricity, natural gas, and district heating networks. To achieve flexible EH presence renewable sources (RESs) combined heat power (CHP) system, storage systems (ESS) incentive-based demand response program (IDRP) are used. The proposed problem minimizes total expected costs opera...

In this work, a new and effective algorithm called hybrid teaching–learning-based optimization (TLBO) charged system search (CSS) algorithms (HTC) are proposed to solve engineering mathematical problems. The CSS is inspired by Coulomb Gauss’s electrostatic laws of physics as well the Newtonian mechanic motion. TLBO interaction between teacher student in classroom. Usually, gets trapped local op...

The teaching–learning-based optimization algorithm (TLBO) is an efficient optimizer. However, it has several shortcomings such as premature convergence and stagnation at local optima. In this paper, the strengthened (STLBO) proposed to enhance basic TLBO’s exploration exploitation properties by introducing three strengthening mechanisms: linear increasing teaching factor, elite system composed ...

This paper presents an improved Teaching-Learning-Based Optimization (TLBO) for optimal tuning of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. The original TLBO is characterized by easy implementation mainly free control parameters. Unfortunately, may suffer from population diversity losses in some cases, leading to local optimum premature convergence. In ...

The most important component that can express a person’s mental condition is facial expressions. A human communicate around 55% of information non-verbally and the remaining 45% audibly. Automatic expression recognition (FER) has now become challenging task in surveying computers. Applications FER include understanding behavior humans monitoring moods psychological states. It even penetrates ot...

Dynamic economic load dispatch (DELD), which determines the best generation scheduling for different power plants during next 24 hours in order to meet electricity demand as well minimize total energy cost, is a highly complex non-linear and non-convex problem. This study proposes an efficient modified teaching-learning-based optimization algorithm, called MTLBO, effectively solve DELD problem ...