A variable structure neural network model for mid-term load forecasting of Iran national power system. - Nariman Mahdavi Mazdeh; Aliakbar A. Gorji; Mohammad Bagher Menhaj; Saeedeh Barghinia (IJCNN, 2008)

Effect of weighting parameters on dynamical behavior of Hopfield neural networks with logistic map activation functions. - Nariman Mahdavi; Mohammad Bagher Menhaj; Ahmad Afshar (CICA, 2009)

A Novel Robust Impulsive Chaos Synchronization Approach for Uncertain Complex Dynamical Networks. - Nariman Mahdavi Mazdeh; Mohammad Bagher Menhaj; Heidar Ali Talebi (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2009)

Possibility of synchronization in Hopfield like Chaotic Neural Networks with just adding a single neuron. - Nariman Mahdavi Mazdeh; Mohammad Bagher Menhaj; Ahmad Afshar (IJCNN, 2010)

Synchronization of Hopfield Like Chaotic Neural Networks with Structure Based Learning. - Nariman Mahdavi; Jürgen Kurths (ICONIP (2), 2012)

Pinning impulsive Synchronization of Complex Dynamical Networks. - Nariman Mahdavi; Mohammad B. Menhaj; Jürgen Kurths; Jianquan Lu; Ahmad Afshar (Int. J. Bifurc. Chaos, 2012)

Synchronization Control for Nonlinear Stochastic Dynamical Networks: Pinning Impulsive Strategy. - Jianquan Lu; Jürgen Kurths; Jinde Cao; Nariman Mahdavi; Chi Huang (IEEE Trans. Neural Networks Learn. Syst., 2012)

Fuzzy Complex Dynamical Networks and Its Synchronization. - Nariman Mahdavi; Mohammad Bagher Menhaj; Jürgen Kurths; Jianquan Lu (IEEE Trans. Cybern., 2013)

Modelling the aggregate demand response of a population of air conditioners to changes in ambient temperature. - Nariman Mahdavi; Julio H. Braslavsky; Cristian Perfumo (CDC, 2015)

Model predictive control of distributed air-conditioning loads for mitigation of solar variability. - Nariman Mahdavi; Julio H. Braslavsky; María M. Seron (AuCC, 2016)

Quantifying maximum controllable energy demand in ensembles of air conditioning loads. - Nariman Mahdavi; Julio H. Braslavsky; Ruben Heersink (CDC, 2017)

Machine learning method for day classification to understand thermostatically controlled load demand. - Ying Guo 001; Nariman Mahdavi (ISGT Asia, 2017)

Model Predictive Control of Distributed Air-Conditioning Loads to Compensate Fluctuations in Solar Power. - Nariman Mahdavi; Julio H. Braslavsky; María M. Seron; Samuel R. West (IEEE Trans. Smart Grid, 2017)

Mapping the Effect of Ambient Temperature on the Power Demand of Populations of Air Conditioners. - Nariman Mahdavi; Julio H. Braslavsky; Cristian Perfumo (IEEE Trans. Smart Grid, 2018)

Modelling and Control of Ensembles of Variable-Speed Air Conditioning Loads for Demand Response. - Nariman Mahdavi; Julio H. Braslavsky (IEEE Trans. Smart Grid, 2020)

Load Balancing in Low-Voltage Distribution Networks via Optimizing Residential Phase Connections. - Bin Liu 036; Frederik Geth; Nariman Mahdavi; Jiangxia Zhong (ISGT Asia, 2021)

An automated data-driven platform for buildings simulation. - Vahid Aryai; Nariman Mahdavi; Samuel R. West; Gregor Henze (BuildSys, 2023)

Quantifying the predictability of renewable energy data for improving power systems decision-making. - Sahand Karimi-Arpanahi; S. Ali Pourmousavi; Nariman Mahdavi (Patterns, 2023)

Probabilistic Estimation of PV Generation at Customer and Distribution Feeder Levels Using Net-Demand Data. - Nariman Mahdavi; Dilusha Weeraddana; Ying Guo 001 (IEEE Trans. Smart Grid, 2023)

Battery Scheduling Optimisation in Energy and Ancillary Services Markets: Quantifying Unrealised Revenue in the Australian NEM. - Sahand Karimi-Arpanahi; Ali Pourmousavi Kani; Nariman Mahdavi (e-Energy, 2024)

Recent Trends in Demand-Side Flexibility. - Henrik Madsen; Seyed Shahabaldin Tohidi; Razgar Ebrahimy; Mohsen Banaei; Tobias K. S. Ritschel; Nariman Mahdavi (EI.A (2), 2024)

A New Definition of Demand Response in the Distributed Energy Resource Era. - Johanna L. Mathieu; Gregor Verbic; Thomas Morstyn; Mads Almassalkhi; Kyri Baker; Julio H. Braslavsky; Kenneth Bruninx; Yury Dvorkin; Gregory S. Ledva; Nariman Mahdavi; Hrvoje Pandzic; Alessandra Parisio; et al. (CoRR, 2024)