Forecasting operation of a chiller plant facility using data-driven models

Author:

Salimian Rizi Behzad,Faramarzi Afshin,Pertzborn AmandaORCID,Heidarinejad MohammadORCID

Funder

American Society of Heating Refrigerating and Air-Conditioning Engineers

Publisher

Elsevier BV

Reference54 articles.

1. A review of data-driven building energy consumption prediction studies;Amasyali;Renew. Sustain. Energy Rev.,2018

2. Analysing Seasonal Health Data;Barnett,2010

3. Building energy consumption forecasting: a comparison of gradient boosting models;Bassi,2021

4. Comparative assessment to predict and forecast water-cooled chiller power consumption using machine learning and deep learning algorithms;Chaerun Nisa;Sustainability.,2021

5. Application of artificial neural network and genetic algorithm to the optimization of load distribution for a multiple-type-chiller plant;Chan;Build. Simul.,2017

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