Mohammad Saniee Abadeh

Learn More
The process of monitoring the events occurring in a computer system or network and analyzing them for sign of intrusions is known as intrusion detection system (IDS). The objective of this paper is to extract fuzzy classification rules for intrusion detection in computer networks. The proposed method is based on the iterative rule learning approach (IRL) to(More)
Fuzzy systems have demonstrated their ability to solve different kinds of problems in various applications domains. Currently, there is an increasing interest to augment fuzzy systems with learning and adaptation capabilities. Two of the most successful approaches to hybridize fuzzy systems with learning and adaptation methods have been made in the realm of(More)
The technology of automatic document summarization is maturing and may provide a solution to the information overload problem. Nowadays, document summarization plays an important role in information retrieval. With a large volume of documents, presenting the user with a summary of each document greatly facilitates the task of finding the desired documents.(More)
A hybrid approach for intrusion detection in computer networks is presented in this paper. The proposed approach combines an evolutionary-based fuzzy system with an Ant Colony Optimization procedure to generate high-quality fuzzy-classification rules. We applied our hybrid learning approach to network security and validated it using the DARPA KDD-Cup99(More)
The leading causes of heart failure are diseases that damage the heart. One of the most well-known diseases that cause heart failure is Coronary Artery Disease. Diagnosis of Coronary Artery Disease is an important medical problem. Many researchers have tried to develop intelligent medical systems to increase the ability of physicians in detecting this(More)
Ant Colony Optimization (ACO), an inspired algorithm from nature, has been successfully applied to classification tasks of data mining in recent years. This paper proposes a rule-based system for medical data mining by using a combination of ACO and fuzzy set theory, named FACO-Miner. FACO-Miner utilizes an ACO algorithm to learn a set of fuzzy rules from(More)