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IAES International Journal of Artificial Intelligence (IJ-AI)
Published by Institute of Advanced Engineering and Science
ISSN : 20894872     EISSN : 22528938     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like genetic algorithm, ant colony optimization, etc); reasoning and evolution; intelligence applications; computer vision and speech understanding; multimedia and cognitive informatics, data mining and machine learning tools, heuristic and AI planning strategies and tools, computational theories of learning; technology and computing (like particle swarm optimization); intelligent system architectures; knowledge representation; bioinformatics; natural language processing; multiagent systems; etc.
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol 2, No 2: June 2013" : 6 Documents clear
A Data Mining Approach for the Detection of Denial of Service Attack Hoda Waguih
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (259.597 KB)

Abstract

Denial of Service (DoS) attacks constitutes one of the major threats and among the hardest security problems currently facing computer networks and particularly the Internet. A DoS attack can easily exhausts the computing and communication resources of its victim within a short period of time. Because of the seriousness of the problem many defense mechanisms have been proposed to fight these attacks. In this paper, we propose an approach that detects DoS attacks using data mining classification techniques. The approach is based on classifying “normal” traffic against “abnormal” traffic in the sense of DoS attacks. The paper investigates and evaluates the performance of J48 decision tree algorithm for the detection of DoS attacks and compares it with two rule based algorithms, namely OneR and Decision table. The selected algorithms were tested with benchmark 1998 DARPA Intrusion Detection data. Our research results show that both Decision tree and rule based classifiers deliver highly accurate results – greater than 99% accuracy – and exhibit high level of overall performance.DOI: http://dx.doi.org/10.11591/ij-ai.v2i2.1937
Counting of People in the Extremely Dense Crowd using Genetic Algorithm and Blobs Counting Muhammad Arif; Sultan Daud; Saleh Basalamah
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (862.236 KB)

Abstract

In this paper, we have proposed a framework to count the moving person in the video automatically in a very dense crowd situation. Median filter is used to segment the foreground from the background and blob analysis is done to count the people in the current frame. Optimization of different parameters is done by using genetic algorithm. This framework is used to count the people in the video recorded in the mattaf area where different crowd densities can be observed. An overall people counting accuracy of more than 96% is obtained.DOI: http://dx.doi.org/10.11591/ij-ai.v2i2.1793
Stable intelligent Controller Design for Generalized Flow Shop Systems Reza Ghasemi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (410.905 KB)

Abstract

Designing a stable fuzzy controller for a class of generalized flow shop systems is addressed in this paper based on max-plus algebra. The proposed controller is multi-input single-output. Robustness against uncertainties in the service times, stabilizing the closed loop system and withholding the blocking effect are the main properties of the proposed controller. An illustrative example is given to show the effectiveness of the proposed method.DOI: http://dx.doi.org/10.11591/ij-ai.v2i2.1325
Designing Intelligent Variable Structure Controller for HIV Infection Reza Ghasemi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (250.993 KB)

Abstract

Fuzzy adaptive controller is developed for HIV infection in which functions of the system are unknown. A non-affine nonlinear system is considered for the HIV infection dynamic model. The merits of the proposed method is as the stability of the closed-loop system (HIV + Controller), the convergence of the infected cells concentration rates to zero and the boundedness of the internal signal and infected cell concentration. The simulation results show the promising performance of the proposed method.DOI: http://dx.doi.org/10.11591/ij-ai.v2i2.2024
A Fuzzy Model for Ni-Cd Batteries Mohammad Sarvi; Masoud Safari
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.532 KB)

Abstract

The batteries models found in the literature are based mainly on mathematical descriptions of physical, chemical, and electrochemical properties which are difficult to determine. This paper presents new fuzzy based model for Nickel Cadmium (Ni-Cd) batteries. The main advantage of the proposed models is that, the proposed model is able to predict battery output voltage without knowledge of numerous factors. Inputs of the proposed model are battery current and state of charge while battery voltage is selected as the output. To check the accuracy of the proposed models, simulations results are compared with the measured battery data at different charge current as well as many other battery models for a 7Ah, size F, Ni-Cd battery. Simulated shows good agreements with measured data. The advantage of fuzzy model is that for modeling by fuzzy method experimental data isn’t needed. The proposed models can apply for modeling of other batteries types.DOI: http://dx.doi.org/10.11591/ij-ai.v2i2.1784
Artificial Bee Colony Algorithm for Economic Load Dispatch Problem Hardiansyah Hardiansyah
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 2, No 2: June 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (237.487 KB)

Abstract

In practical cases, the fuel cost of generators can be represented as a quadratic function of real power generation and satisfied constraints for minimizing of fuel cost. Artificial Bee Colony (ABC) algorithm is used for the optimization of active power dispatch of generating units. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total cost is minimized. Simulation and analysis of economic load dispatch using Artificial Bee Colony (ABC) algorithm is proposed. The obtained results are compared with the conventional method, genetic algorithm (GA) and shows that the ABC algorithm approach is more feasible and efficient for finding minimum cost.DOI: http://dx.doi.org/10.11591/ij-ai.v2i2.1613

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