Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

The aim of this research is to study the effect of welded joint design (Butt joint and lap joint) on thejoint strength during tension and fatigue loading with different current of welding (40,50,60,70,80) ^per, and different type of wire welding. The result of this research is showed that the effect of fatigue loading on the type of joint is more than the effect of tension loading on it. And the butt joint welding is better than the lap joint welding during the fatigue loaded.The experimental results of the effect of W'elding current showed that more increasing and more decreasing the value of the heat input, during the welding was found to produce mechanical brittleness on the buttjoint welding during the static and dynamic loading. Also i

—This paper studies the control motion of a single link flexible joint robot by using a hierarchical non-singular terminal sliding mode controller (HNTSMC). In comparison to the conventional sliding mode controller (CSMC), the proposed algorithm (NTSMC) not only can conserve characteristics of the convention CSMC, such as easy implementation, guaranteed stability and good robustness against system uncertainties and external disturbances, but also can ensure a faster convergence rate of the systems states to zero in a finite time and singularity free. The flexible joint robot (FJR) is a two degree of freedom (2DOF) nonlinear and underactuated system. The system here is modeled as a fourth order system by using Lagrangian method. Based on t

The current study executes a fully coupled thermomechanical simulation of friction stir welding (FSW) process of aluminum 6061-T6 alloy T-joint type using finite element method. The analysis simulation accounts for the three steps of the FSW process which includes: plunging, dwelling, and moving stages. The temperature history, associated stresses and strains generated through the FSW phases, tool reaction force, and time-dependence of the energy dissipation were evaluated. To overcome the shortcomings of purely Lagrangian and Eulerian descriptions, Arbitrary Lagrangian Eulerian (ALE) formulation, adaptive meshing, and the mass scaling were used as techniques to improve sequence modeling of the friction stir welding process. Coulomb’s fri

In this paper, a single link flexible joint robot is used to evaluate a tracking trajectory control and vibration reduction by a super-twisting integral sliding mode (ST-ISMC). Normally, the system with joint flexibility has inevitably some uncertainties and external disturbances. In conventional sliding mode control, the robustness property is not guaranteed during the reaching phase. This disadvantage is addressed by applying ISMC that eliminates a reaching phase to ensure the robustness from the beginning of a process. To design this controller, the linear quadratic regulator (LQR) controller is first designed as the nominal control to decide a desired performance for both tracking and vibration responses. Subsequently, discontinuous con

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

In unpredicted industrial environment, being able to adapt quickly and effectively to the changing is key in gaining a competitive advantage in the global market. Agile manufacturing evolves new ways of running factories to react quickly and effectively to changing markets, driven by customized requirement. Agility in manufacturing can be successfully achieved via integration of information system, people, technologies, and business processes. This article presents the conceptual model of agility in three dimensions named: driving factor, enabling technologies and evaluation of agility in manufacturing system. The conceptual model was developed based on a review of the literature. Then, the paper demonstrates the agility