activity
20202022
most citedSystematic review of deep learning and machine learning for building energy

122 citations · 200 across the 7 of their papers we have counts for

collaborators

8 papers

cs.LG2022122 cited

Systematic review of deep learning and machine learning for building energy

Ardabili Sina, Leila Abdolalizadeh, Csaba Mako +2

The building energy (BE) management has an essential role in urban sustainability and smart cities. Recently, the novel data science and data-driven technologies have shown signifi…

cs.LG20221 cited

Integration of neural network and fuzzy logic decision making compared with bilayered neural network in the simulation of daily dew point temperature

Guodao Zhang, Shahab S. Band, Sina Ardabili +2

In this research, dew point temperature (DPT) is simulated using the data-driven approach. Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized as a data-driven technique to f…

econ.GN2021

Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS

Saeed Nosratabadi, Sina Ardabili, Zoltan Lakner +2

Advancing models for accurate estimation of food production is essential for policymaking and managing national plans of action for food security. This research proposes two machin…

econ.GN202016 cited

Modelling Temperature Variation of Mushroom Growing Hall Using Artificial Neural Networks

Sina Ardabili, Amir Mosavi, Asghar Mahmoudi +3

The recent developments of computer and electronic systems have made the use of intelligent systems for the automation of agricultural industries. In this study, the temperature va…

econ.GN202045 cited

State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability

Saeed Nosratabadi, Amir Mosavi, Ramin Keivani +2

Deep learning (DL) and machine learning (ML) methods have recently contributed to the advancement of models in the various aspects of prediction, planning, and uncertainty analysis…

cs.NE202016 cited

Hybrid Machine Learning Models for Crop Yield Prediction

Saeed Nosratabadi, Felde Imre, Karoly Szell +3

Prediction of crop yield is essential for food security policymaking, planning, and trade. The objective of the current study is to propose novel crop yield prediction models based…