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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 4 Documents
 1 
Search results for , issue "Vol 4, No 4: December 2015" : 4 Documents clear
Optimal Placement of SVC Using Fuzzy and Firefly Algorithm P.SURESH BABU; P.B. CHENNAIAH; M. SREEHARI
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 4: December 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (378.377 KB) | DOI: 10.11591/ijai.v4.i4.pp113-117

Abstract

Voltage stability is major phenomena in any power system network for reliability and continuity operation. But the tight operation of power system due to overloading or fault on the system which is evitable and major threat to the power system. So it is necessary to maintain the voltages within the constraints at the overloading conditions also by placing of Static VAR Compensator (SVC) at optimal locations. New approaches are used to find the placement and size of the SVC at different locations. Fuzzy is used to find the location and the size of the SVC is fined by the Firefly algorithm. This paper considers different loading conditions of the power system network (125,150,175over loading conditions). From the results we can conclude that the power losses are reduced and the voltages can be maintained within the limits .IEEE 14 bus, IEEE 30 bus system is taken for the implementing the above techniques.
Conventional DC Voltage Operating System for High Speeed Traction Power Supplies Using LLC-HPQC Control Ch. Lenin Babu; P. Harinath Reddy; T. Reddi Sekhar
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 4: December 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (983.056 KB) | DOI: 10.11591/ijai.v4.i4.pp118-128

Abstract

In this paper a hybrid power quality compensator (HPQC) is proposed for compensation in cophase traction power supply and minimum dc operation voltage is achievable for high-speed traction power supply. The parameter design procedure for minimum dc operation voltage in HPQC as well as minimum voltage rating with load PF is discussed. The detailed discussions of proposed circuit configurations of HPQC are provided in section II, together with comparison with conventional RPC. In comparison with conventional railway power compensator proposed HPQC can achieve reduced dc link voltage level. It is also verified through simulations results that the LLC-HPQC would operate at the minimum voltage with the proposed parameter design. HPQC is able to provide system unbalances, reactive power, and harmonic compensation in cophase traction power with reduced operation voltage. The cophase traction power supply with proposed HPQC is suitable for high-speed traction applications.
Narx Based Short Term Wind Power Forecasting Model M. NANDANA JYOTHI; V. DINAKAR; N. S S RAVI TEJA
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 4: December 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (597.742 KB) | DOI: 10.11591/ijai.v4.i4.pp129-138

Abstract

This paper contributes a short-term wind power forecasting through Artificial Neural Network with nonlinear autoregressive exogenous inputs (NARX) model. The meteorological parameters like wind speed, temperature, pressure, and air density are considered as input parameters collected from KL University area and the calculated generated power as output parameters of neural network to predict the wind power generation. Based on hybrid forecasting technique a code is developed in MATLAB at different hidden layers and delay times.
Type-2 Fuzzy Logic Control of a Doubly-Fed Induction Machine (DFIM) Loukal Keltoum; Benalia Leila
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 4: December 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (576.821 KB) | DOI: 10.11591/ijai.v4.i4.pp139-152

Abstract

The fuzzy controllers have demonstrated their effectiveness in the control of nonlinear systems, and in many cases have established their robust and that their performance is less sensitive to parameter variations over conventional controllers. In this paper, Interval Type-2 Fuzzy Logic Controller (IT2FLC) method is proposed for controlling the speed with a direct stator flux orientation control of doubly-fed induction motor (DFIM), we made a comparison between the Type-1 Fuzzy Logic Control (T1FLC) and IT2FLC of the DFIM, first a modeling of DFIM is expressed in a (d-q) synchronous rotating frame. After the development and the synthesis of a stabilizing control laws design based on IT2FLC. We use this last approach to the control of the DFIM under different operating conditions such as load torque and in the presence of parameter variation. The obtained simulation results show the feasibility and the effectiveness of the suggested method.

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