M
Mohammad Reza Khosravi
Researcher at Persian Gulf University
Publications - 144
Citations - 2503
Mohammad Reza Khosravi is an academic researcher from Persian Gulf University. The author has contributed to research in topics: Computer science & Network packet. The author has an hindex of 15, co-authored 115 publications receiving 929 citations. Previous affiliations of Mohammad Reza Khosravi include Shiraz University of Technology & Shiraz University.
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Medical Image Magnification Based on Original and Estimated Pixel Selection Models.
Omid Akbarzadeh,Omid Akbarzadeh,Mohammad Reza Khosravi,Mohammad Reza Khosravi,B Khosravi,P Halvaee +5 more
TL;DR: The current research reveals the fact that selection models are not a general factor in reconstruction problems, and the structure of the basic interpolators is also a main factor which affects the final results.
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Formulizing the Fuzzy Rule for Takagi-Sugeno Model in Network Traffic Control
TL;DR: The Fuzzy Rule for Takagi-Sugeno Model in Network Traffic Control is derived using the data from the Shiraz University of Technology, Shiraz, Iran as a model for network traffic control.
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LEAESN: Predicting DDoS attack in healthcare systems based on Lyapunov Exponent Analysis and Echo State Neural Networks
TL;DR: This paper proposes a new method for prediction of DDoS attack based on Lyapunov Exponent Analysis and Echo State Network (LEAESN), and tests the method on the Darpa98 dataset which consists of a standard dataset for evaluation of intrusion detection systems.
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Combination of Pattern Classifiers Based on Naive Bayes and Fuzzy Integral Method for Biological Signal Applications
TL;DR: A theoretical frame for combination of classifiers is developed that shows that a wide range of existing algorithms could be incorporated as the particular cases of compound classification where all the pattern representations are used jointly to make an accurate decision.
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Optimal Distribution of Workloads in Cloud-Fog Architecture in Intelligent Vehicular Networks
TL;DR: A kind of Genetic Algorithm (GA) is exploited to optimize the power consumption of edge systems and reduce delays in the processing of workloads simultaneously by considering the battery depreciation, the supporting power supply, and the delay.