Estimating Heating Load in Residential Buildings Using Multi-Verse Optimizer, Self-Organizing Self-Adaptive, and Vortex Search Neural-Evolutionary Techniques

Abstract

Using ANN algorithms to address optimization problems has substantially benefited recent research. This study assessed the heating load (HL) of residential buildings’ heating, ventilating, and air conditioning (HVAC) systems. Multi-layer perceptron (MLP) neural network is utilized in association with the MVO (multi-verse optimizer), VSA (vortex search algorithm), and SOSA (self-organizing self-adaptive) algorithms to solve the computational challenges compounded by the model’s complexity. In a dataset that includes independent factors like overall height and glazing area, orientation, wall area, compactness, and the distribution of glazing area, HL is a goal factor. It was revealed that metaheuristic ensembles based on the MVOMLP and VSAMLP metaheuristics had a solid ability to recognize non-linear relationships between these variables. In terms of performance, the MVO-MLP model was considered superior to the VSA-MLP and SOSA-MLP models.

Enhancing the Accuracy of Low-Cost Inclinometers with Artificial Intelligence

“…Recent implementations of the MLP are exemplified by the work of Wang et al [64], who employed this tool to predict the compressive strength of geopolymer concrete. Similarly, Nejati et al [65] utilized an MLP to predict building thermal loads, while Martinez- It is crucial to emphasize that the utilization of AI tools for locally calibrating LARA is not intended to replace traditional signal processing tools and filters; rather, it serves as an additional layer complementing them. LARA has already benefitted from the ongoing research in novel signal processing tools and filters [32].…”

“…Recent implementations of the MLP are exemplified by the work of Wang et al [64], who employed this tool to predict the compressive strength of geopolymer concrete. Similarly, Nejati et al [65] utilized an MLP to predict building thermal loads, while Martinez-Comesaña et al [66] applied it to estimate the indoor environmental conditions of existing buildings.…”

The 4th Industrial Revolution Brings a Change in the Design Paradigm for New and Retrofitted Buildings

“…Finally, this integrated technology was demonstrated to function in Hungary [12], the USA [59], China [60], Poland [61], and Japan [62]. New modeling approaches have also been proposed [63].…”