S. Askari

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A novel and fast MIMO fuzzy inference system based on a class of fuzzy clustering algorithms with interpretability and complexity analysis

S. Askari, S. Askari, 2017, Expert Syst. Appl..

Fuzzy C-Means clustering algorithm for data with unequal cluster sizes and contaminated with noise and outliers: Review and development

S. Askari, S. Askari, 2021, Expert Syst. Appl..

Noise-resistant fuzzy clustering algorithm

S. Askari, S. Askari, 2020, Granular Computing.

Forecasting semi-dynamic response of natural gas networks to nodal gas consumptions using genetic fuzzy systems

M. H. Fazel Zarandi, S. Askari, N Montazerin, 2015 .

A clustering based forecasting algorithm for multivariable fuzzy time series using linear combinations of independent variables

S. Askari, N Montazerin, M. H. Fazel Zarandi, 2015, Appl. Soft Comput..

Generalized Possibilistic Fuzzy C-Means with novel cluster validity indices for clustering noisy data

Mohammad Hossein Fazel Zarandi, S. Askari, N. Montazerin, 2017, Appl. Soft Comput..

Generalized entropy based possibilistic fuzzy C-Means for clustering noisy data and its convergence proof

Mohammad Hossein Fazel Zarandi, S. Askari, N. Montazerin, 2017, Neurocomputing.

High-Frequency Modeling of Natural Gas Networks From Low-Frequency Nodal Meter Readings Using Time-Series Disaggregation

Mohammad Hossein Fazel Zarandi, S. Askari, N. Montazerin, 2016, IEEE Transactions on Industrial Informatics.

A high-order multi-variable Fuzzy Time Series forecasting algorithm based on fuzzy clustering

S. Askari, N. Montazerin, N. Montazerin, 2015, Expert Syst. Appl..

A critical note on inverse fuzzy time series algorithms

S. Askari, 2021, Fuzzy Sets Syst..