Increasing consumption of energy calls for proper approximation demand towards a sustainable and cost-effective development. In this work, novel hybrid methodologies aim to predict the annual thermal (ATED) by analyzing characteristics building, such as transmission coefficients elements, glazing, air-change conditions. For objective, an adaptive neuro-fuzzy-inference system (ANFIS) was optimiz...

Abstract To address the deficiency and predict adsorption performance in different adsorbents, this study proposes a new optimizer linked to machine learning (ML) model considering of process. The main goal is under process conditions with adsorbents provide unified framework, leading prediction phenomena instead traditional isotherm models. This research focuses on predicting adsorbed amount O...

Recently, variational mode decomposition (VMD) has attracted wide attention on mechanical vibration signal analysis. However, there are still some dilemmas in the application of VMD, such as determination number K and quadratic penalty term α. In order to acquire appropriate parameters an improved parameter-adaptive VMD method based grey wolf optimizer (GWO) is developed by taking minimum avera...

Three-diode model (TDM) of photovoltaic (PV) cells is a significantly precise that addresses the electrical and optical losses in such PVs. Due to its nonlinearity multivariable characteristics, TDM complex debatable PV model. This article proposes novel hybrid African vultures–grey wolf optimizer (AV–GWO) approach precisely estimate parameters TDM. The AVO meta-heuristic inspired by vultures’ ...

The impact effect is a crucial issue in civil engineering and has received considerable attention for decades. For the first time, this study develops hybrid machine learning models that integrate novel Extreme Gradient Boosting (XGB) model with Particle Swam Optimization (PSO), Grey Wolf Optimizer (GWO), Moth Flame (MFO), Jaya (JA), Multi-Verse (MVO) algorithms predicting permanent transverse ...

<span lang="EN-US">The inverter has been attracting researchers for their application in renewable energy. So far, multilevel is considered as low distortion class, which produces output voltage imitating a pure sine waveform. However, the needs free of have motivating to improve pulse width modulation PWM generation method. In this paper, modified technique proposed reduce total harmonic...

Recently, renewable energy resources (RESs) have been utilized to supply electricity remote areas, instead of the conventional methods electrical production. In this paper, optimal design a standalone hybrid RES comprising photovoltaic (PV), wind turbine (WT), and biomass sources as well an storage system, such hydro-pumped is studied. The problem sizing generating units in proposed system form...

This article introduces a novel nature-inspired algorithm called the Plum Tree Algorithm (PTA), which has biology of plum trees as its main source inspiration. The PTA was tested and validated using 24 benchmark objective functions, it further applied compared to following selection representative state-of-the-art, algorithms: Chicken Swarm Optimization (CSO) algorithm, Particle (PSO) Grey Wolf...

Freeze–thaw damage of rock mass poses a great threat to the safety engineering, ground buildings, and low-temperature storage liquefied natural gas (LNG) in cold regions. By collecting acoustic emission (AE) signals sandstone during uniaxial compression failures, this paper analyzed critical slowdown phenomenon different types freeze–thaw failure. According auto-correlation coefficients varianc...