A decentralized federated learning based interoperable and heterogeneity aware predictive optimization method for energy and comfort in smart homes environment
Authors:
- Rongxu XuRXRongxu Xu
- Salabat KhanSKSalabat Khan
- Wenquan JinWJWenquan Jin
- Anam Nawaz KhanAKAnam Nawaz Khan
- Qazi Waqas KhanQKQazi Waqas Khan
- Sunhwan LimSLSunhwan Lim
- Do Hyuen KimDKDo Hyuen Kim
- 3 May 2024
- journal article
- research article
- Published by Elsevier in Applied Soft Computing
- Vol. 161
Abstract
No abstract availableKeywords
This publication has 29 references indexed in Scilit:
- Building energy consumption prediction using multilayer perceptron neural network-assisted models; comparison of different optimization algorithmsEnergy, 2023
- Optimizing energy consumption patterns of smart home using a developed elite evolutionary strategy artificial ecosystem optimization algorithmEnergy, 2023
- RETRACTED ARTICLE: Energy optimization in smart urban buildings using bio-inspired ant colony optimizationSoft Computing, 2022
- IoT edge computing-enabled collaborative tracking system for manufacturing resources in industrial parkAdvanced Engineering Informatics, 2020
- A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildingsApplied Energy, 2019
- Bi-level optimization model for integrated energy system considering the thermal comfort of heat customersApplied Energy, 2018
- A flexible control strategy for energy and comfort aware HVAC in large buildingsBuilding and Environment, 2018
- An information provision system to promote energy conservation and maintain indoor comfort in smart homes using sensed data by IoT sensorsFuture Generation Computer Systems, 2018
- Artificial neural network (ANN) based model predictive control (MPC) and optimization of HVAC systems: A state of the art review and case study of a residential HVAC systemEnergy and Buildings, 2017
- Room air temperature affects occupants’ physiology, perceptions and mental alertnessBuilding and Environment, 2010