Maryam Amoozegar

Maryam Amoozegar
Graduate University of Advanced Technology | kgut · Department of Information Technology

PhD

About

8
Publications
3,016
Reads
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132
Citations
Citations since 2016
2 Research Items
122 Citations
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2016201720182019202020212022010203040
2016201720182019202020212022010203040
2016201720182019202020212022010203040
Additional affiliations
May 2012 - present
Graduate University of Advanced Technology
Position
  • Instructor
January 2008 - July 2014
Shahid Bahonar University of Kerman
Position
  • Lecturer
August 2005 - December 2007
Iran University of Science and Technology
Position
  • Master's Student

Publications

Publications (8)
Article
Full-text available
Software Performance Engineering (SPE) evaluates the key performance factors such as response time and utilization in the entire life cycle of software development. One of the important issues of software performance is bottlenecks that have not been investigated much till now in the process of SPE. Meanwhile, Bottleneck detection and mitigation in...
Conference Paper
Full-text available
Parameter tuning has critical influences on the performance of evolutionary algorithms. Deliberate parameter investigation and changing the value of them is very expensive and time consuming. This paper has applied Design of Experiment (DOE) method to tune the parameters of Gravitational Search Algorithms (GSA) systematically. Also, to reduce its c...
Conference Paper
Full-text available
Proper primer design is actually one of the most important factors/steps in successful DNA sequencing. There are many constraints that should be satisfied for designing the optimal primers. In recent years, many methods have been proposed to provide feasible primer set. But designed primer sets by these methods usually do not provide a specific PCR...
Conference Paper
Full-text available
Software Performance Engineering (SPE) in the early life cycle of software development (software modeling) is very useful and cost-effective but does not guide the software architect through how to improve the design. Computing the least response time by controlling utilization and cost is a constrained optimization problem. This paper presents a c...
Article
Anomaly detection in time-evolving networks has many applications, for instance, traffic analysis in transportation networks and intrusion detection in computer networks. One group of popular methods for anomaly detection from evolving networks are robust online subspace trackers. However, these methods suffer from problem of insensitivity to drast...
Article
Feature selection is an important preprocessing task in classification that eliminates the irrelevant, redundant, and noisy features. Improving the performance of model, decreasing the computational cost, and adjusting the “curse of dimensionality” are the key advantages of feature selection task. The evolution process of the existing multi-objecti...
Research
Full-text available
this research has been supported by Electrical Distribution of south of Kerman
Article
Full-text available
Abstract Gravitational search algorithm(GSA) is a recent created metaheuristic optimization algorithm with good results in function optimization as well as real world optimization problems. Many real world problems involve multiple (often conflicting) objectives, which should be optimized simultaneously. Therefore, the aim of this paper is to propo...

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