In collaboration with Payame Noor University and the Iranian Society of Instrumentation and Control Engineers
Optimal Control of Infectious Diseases Using the Artificial Neural Networks

Rasoul Heydari Dastjerdi; Ghasem Ahmadi; Mahmood Dadkhah; Ayatollah Yari

Volume 8, Issue 2 , December 2023, , Pages 17-32

  This paper presents a novel approach using artificial neural networks to solve the SEIR (Susceptible‎, ‎Exposed‎, ‎Infected‎, ‎and Recovered) model of infectious diseases based on dynamical systems‎. ‎Optimal control techniques are employed to determine a vaccination schedule ...  Read More

Design of a Fuzzy System Based on Lookup Table for Diagnosis and Predicting of Metabolic Syndrome in Preschoolers‎, ‎Children‎, ‎and Adolescents

Mohammad Dehghandar; Ghasem Ahmadi; Heydar Aghebatbeen Monfared

Volume 6, Issue 1 , January 2021, , Pages 61-80

  The purpose of this study was to provide a fuzzy system for predicting and diagnosing metabolic syndrome (MetS) in preschoolers‎, ‎children‎, ‎and adolescents‎. ‎In this study‎, ‎previous research on the factors affecting metabolic syndrome‎, ‎especially in children‎, ...  Read More

Stable Rough Extreme Learning Machines for the Identification of Uncertain Continuous-Time Nonlinear Systems

Ghasem Ahmadi

Volume 4, Issue 1 , July 2019, , Pages 83-101

  ‎Rough extreme learning machines (RELMs) are rough-neural networks with one hidden layer where the parameters between the inputs and hidden neurons are arbitrarily chosen and never updated‎. ‎In this paper‎, ‎we propose RELMs with a stable online learning algorithm for the identification ...  Read More

Control and Optimization
A Higher Order Online Lyapunov-Based Emotional Learning for Rough-Neural Identifiers

Ghasem Ahmadi; Mohammad Teshnehlab; Fahimeh Soltanian

Volume 3, Issue 1 , July 2018, , Pages 87-108

  o enhance the performances of rough-neural networks (R-NNs) in the system identification‎, ‎on the base of emotional learning‎, ‎a new stable learning algorithm is developed for them‎. ‎This algorithm facilitates the error convergence by increasing the memory depth of R-NNs‎. ...  Read More

Control and Optimization
Solving Linear Semi-Infinite Programming Problems Using Recurrent Neural Networks

Alaeddin Malek; Ghasem Ahmadi; Seyyed Mehdi Mirhoseini Alizamini

Volume 1, Issue 1 , April 2016, , Pages 55-67

  ‎Linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints‎. ‎In this paper‎, ‎to solve this problem‎, ‎we combine a discretization method and a neural network method‎. ‎By a simple discretization ...  Read More