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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 5 Documents
 1 
Search results for , issue "Vol 4, No 2: June 2015" : 5 Documents clear
Design an Algorithm for Software Development in Cbse Environment using Feed Forward Neural Network Amit Verma; Pardeep kaur
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 2: June 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (575.229 KB) | DOI: 10.11591/ijai.v4.i2.pp53-61

Abstract

A In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into Repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there. To check the results of our algorithm based on factors like accuracy, precision and recall compare with existing technique i.e. integrated classification scheme for retrieval of components based on keyword search and results are so encouraging.
Refined Clustering of Software Components by Using K-Mean and Neural Network Indu Verma; Amarjeet Kaur; Iqbaldeep Kaur
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 2: June 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (651.011 KB) | DOI: 10.11591/ijai.v4.i2.pp62-71

Abstract

Data Mining is extraction of relevant information about data set. A data-warehouse is a location where information is stored. There are various services of data mining, clustering is one of them. Clustering is an effort to group similar data onto single cluster. In this paper we propose and implement k-mean and neural network for clustering same components in single cluster. Clustering reduces the search space by grouping similar test cases together according to the requirements and, hence minimizing the search time, for the retrieval of the test cases, resulting in reduced time complexity. In this research paper we proposed approach for re-usability of test cases by unsupervised approach and supervised approach. In unsupervised learning we proposed k-mean and in supervised learning neural network. We have designed the algorithm for requirement and test case document clustering according to its tf-idf vector space and the output is set of highly cohesive pattern groups.
Mitigation of Voltage Fluctuations using fuzzy-based D-STATCOM in High Level Penetration of DG Systems M.Padma Lalitha; R.Madhan Mohan; B.Murali Mohan Babu
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 2: June 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.057 KB) | DOI: 10.11591/ijai.v4.i2.pp72-80

Abstract

Voltage fluctuations mainly resulting from variable output power of renewable energy sources; these are strictly challenging power quality in distribution-generation systems. The paper presents a control method for fuzzy based D-STATCOM to relieve variation of positive-sequence and negative-sequence voltages. D-STATCOM continuously operates as fundamental positive–sequence admittance and negative-sequence conductance to restore the positive-sequence voltage to the nominal value and negative-sequence voltage to the allowable level. At transient period both admittance and conductance are dynamically tuned to improve the voltage regulation performance. The ability of fuzzy logic to handle rough and unpredictable real world data made it suitable for a wide variety of applications, especially, when the models are too complex to be analyzed by classical methods. This paper presents the computer simulation of fuzzy based D-STATCOM under steady and transient state condition. The reduction of total harmonic distortions (THD) and voltage imbalance factor %VUF is discussed at all buses and maintained in acceptable level.
Improvement of Power Quality for Microgrid using Fuzzy Based UPQC Controller Abdul Rasheed; G. Keshava Rao
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 2: June 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (707.728 KB) | DOI: 10.11591/ijai.v4.i2.pp37-44

Abstract

Generally, the power systems are mainly effected by the continuous changes in operational requirement and increasing amount of distributed energy systems. This paper proposes a new concept of power-control strategies for a micro grid generation system for better transfer of power. The micro grids are obtained with the general renewable energy sources and this concept provides the maximum utilization of power at environmental free conditions with low losses; then the system efficiency is also improved. This paper proposes a single stage converter based micro grid to reduce the number of converters in an individual ac or dc grid. The proposed micro grid concept can work in both stand-alone mode and also in grid interfaced mode. The distortions that occur in power system due to changes in load or because of usage of non-linear loads, can be eliminated by using control strategies designed for shunt active hybrid filters such as series and shunt converters. A conventional Proportional Integral (PI) and Fuzzy Logic Controllers are used for power quality enhancement by reducing the distortions in the output power. The simulation results are compared among the two control strategies, that fuzzy logic controller and pi controller.
A Fuzzy Controller for Compensation of Voltage Sag/Swell Problems Using Reduced Rating Dynamic Voltage Restorer Rajesh Damaraju; S.V.N.L. Lalitha
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 4, No 2: June 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (563.416 KB) | DOI: 10.11591/ijai.v4.i2.pp45-52

Abstract

Non linear loads are highly effected by variations in voltages. Dynamic voltage restorer is one of the most popular compensating devices due to its low cost and better performance. Usage of Park’s transformation technique effectively reduces the rating of Dynamic voltage restorer. Application of fuzzy logic controller for getting the better result is proposed in this paper. The results are verified in Matlab/Simulink environment.

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