This paper addresses the problem of end-effector formation control for manipulators that are subjected to external disturbances: input disturbance torques and disturbance forces at each end-effector. The disturbances ...
详细信息
A multi-agent system designed to achieve distance-based shape control with flocking behavior can be seen as a mechanical system described by a Lagrangian function and subject to additional external forces. Forced vari...
详细信息
The increasing prevalence of smart building architectures, driven by the integration of Internet of Things (IoT) devices and automation systems, has led to a surge in energy consumption. This research explores the app...
详细信息
ISBN:
(数字)9798350372748
ISBN:
(纸本)9798350372755
The increasing prevalence of smart building architectures, driven by the integration of Internet of Things (IoT) devices and automation systems, has led to a surge in energy consumption. This research explores the application of swarm intelligence techniques as an innovative approach to optimize neural networks, aiming to strike a balance between maintaining the desired performance levels and minimizing energy consumption. The study investigates the integration of swarm-based optimization algorithms, such as Particle Swarm Optimization (PSO) into the training and operation of neural networks. These algorithms enable the networks to dynamically adapt and optimize their parameters in response to changing environmental conditions and user requirements. The research focuses on developing a comprehensive framework that considers the specific challenges posed by smart building architectures, including real-time data processing, sensor integration, and adaptive control. The proposed approach aims to achieve optimal neural network configurations that minimize energy consumption while ensuring reliable and responsive operation of smart building systems. The results demonstrate the potential of swarm intelligence to significantly improve the energy efficiency of neural network-enabled smart building architectures, providing a promising avenue for sustainable and intelligent infrastructure. The proposed model has an accuracy of 98.23% which is 7.64% higher than that of the traditional approaches.
作者：
Urszula PawlakMarcin PawlakDepartment of Mechanics
Metal Structures and Computer Methods Faculty of Civil and Architecture Kielce University of Technology al. 1000-lecia Państwa Polskiego 7 25-314 Kielce Poland Department of Power Engineering Electronics
Faculty of Electrical Engineering Automatic Control and Computer Kielce University of Technology al. 1000-lecia Państwa Polskiego 7 25-314 Kielce Poland
In the article, the energy characteristics of a terraced house located in Kielce were assessed. The analyzed house was put into use in 1982. Due to the old manufacturing technology, mainly in the area of the materials...
In the article, the energy characteristics of a terraced house located in Kielce were assessed. The analyzed house was put into use in 1982. Due to the old manufacturing technology, mainly in the area of the materials used, to limit significant heat losses, it has been thermally renewed many times. The aim of the calculations was to indicate the financial benefits, in example to reduce the costs of maintaining the house and to provide its residents with the proper comfort of use of the building, also taking into account the health aspects. The analysis of the object was made in several stages. Proposed are changes reducing the demand for non-renewable primary energy Ep, using modern thermal insulation materials, joinery with low heat transfer coefficient and renewable energy sources. As a result, an energy-efficient building that meets WT 2017 was obtained. The annual demand for non-renewable primary energy EP was determined using the Certo 2015 program in educational version 1.3.3.0.
暂无评论