Amanote Research

Amanote Research

    RegisterSign In

Prediction of Hourly Heating Energy Use for Hvac Using Feedforward Neural Networks

doi 10.15308/sinteza-2017-297-301
Full Text
Open PDF
Abstract

Available in full text

Date

January 1, 2017

Authors
Aleksandra SretenovićRadiša JovanovićVojislav NovakovićNataša NordMaja Kostadinović
Publisher

Singidunum University


Related search

Multistage Ensemble of Feedforward Neural Networks for Prediction of Heating Energy Consumption

Thermal Science
Renewable Energythe EnvironmentSustainability
2016English

Statistical Features Based Approach (SFBA) for Hourly Energy Consumption Prediction Using Neural Network

International Journal of Information Technology and Computer Science
2017English

Adaptive Type Feedforward Feedback Controller Using Neural Networks

Transactions of the Society of Instrument and Control Engineers
1994English

Modeling of Hourly River Water Temperatures Using Artificial Neural Networks

Water Quality Research Journal of Canada
Water ScienceTechnology
2014English

Distinction of the Authors of Texts Using Multilayered Feedforward Neural Networks

Southeast Europe Journal of Soft Computing
2012English

Use of Neural Networks in Tool Wear Prediction

MATEC Web of Conferences
Materials ScienceEngineeringChemistry
2019English

Prediction of Surface Distress Using Neural Networks

2017English

Artificial Neural Networks for Prediction

English

Prediction of Gold Prices Using Artificial Neural Networks

Uluslararası Muhendislik Arastirma ve Gelistirme Dergisi
2017English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy