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INDONESIA
International Journal of Intelligent Systems and Applications in Engineering
Published by Ismail SARITAS
ISSN : 21476799     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Intelligent Systems and Applications in Engineering (IJISAE) is an international and interdisciplinary journal for both invited and contributed peer reviewed articles that intelligent systems and applications in engineering at all levels. The journal publishes a broad range of papers covering theory and practice in order to facilitate future efforts of individuals and groups involved in the field. IJISAE, a peer-reviewed double-blind refereed journal, publishes original papers featuring innovative and practical technologies related to the design and development of intelligent systems in engineering. Its coverage also includes papers on intelligent systems applications in areas such as nanotechnology, renewable energy, medicine engineering, Aeronautics and Astronautics, mechatronics, industrial manufacturing, bioengineering, agriculture, services, intelligence based automation and appliances, medical robots and robotic rehabilitations, space exploration and etc.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue " Vol 3, No 4 (2015)" : 5 Documents clear
The Classification of Eye State by Using kNN and MLP Classification Models According to the EEG Signals Sabancı, Kadir; Koklu, Murat
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 4 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.75836

Abstract

What is widely used for classification of eye state to detect human’s cognition state is electroencephalography (EEG). In this study, the usage of EEG signals for online eye state detection method was proposed. In this study, EEG eye state dataset that is obtained from UCI machine learning repository database was used. Continuous 14 EEG measurements forms the basic of the dataset. The duration of the measurement is 117 seconds (each measurement has14980 sample). Weka (Waikato Environment for Knowledge Analysis) program is used for classification of eye state. Classification success was calculated by using k-Nearest Neighbors algorithm and multilayer perceptron neural networks models. The obtained success of classification methods were compared. The classification success rates were calculated for various number of neurons in the hidden layer of a multilayer perceptron neural network model. The highest classification success rate have been obtained when the number of neurons in the hidden layer was equal to 7. And it was 56.45%. The classification success rates were calculated with k-nearest neighbors algorithm for different neighbourhood values. The highest success was achieved in the classification made with kNN algorithm.  In kNN models, the success rate for 3 nearest neighbor were calculated as 84.05%.
An Artificial Neural Network Model for Wastewater Treatment Plant of Konya Tumer, Abdullah Erdal; Edebali, Serpil
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 4 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.65358

Abstract

In this study, modelling of Konya wastewater treatment plant was studied by using artificial neural network with different architectures in Matlab software. All data were obtained from wastewater treatment plant of Konya during daily records over four month. Treatment efficiency of the plant was determined by taking into account of input values of pH, temperature, COD, TSS and BOD with output values TSS. Performance of the model was compared via the parameters of Mean Squared Error (MSE), and correlation coefficient (R). The suitable architecture of the neural network model is determined after several trial and error steps. According to the modelling study, the ANN can predict the plant performance with correlation coefficient (R) between the observed and predicted output variable reached up to 0.96.
CLASSIFICATION OF LEAF TYPE USING ARTIFICIAL NEURAL NETWORKS Yasar, Ali; Saritas, Ismail; Sahman, M. Akif; Dundar, A. Oktay
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 4 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.49279

Abstract

A number of shape features for automatic plant recognition based on digital image processing have been proposed by Pauwels et al. in 2009. Then Silva et al in 2014 have presented database comprises 40 different plant species. We performed in our study a classification process using dataset and artificial neural networks which have been prepared by Silva and et al. It has been determined that classification accuracy is over 92%.
Fuzzy approach to estimate the demand and supply quantitative imbalance at the labor market of information technology specialists Jabrayilova, Zarifa; Mammadova, Masuma; Mammadzade, Faig
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 4 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.24856

Abstract

This document considers the processes of modelling supply and demand interactions in the labour market for information technology experts (IT professionals) and management of their quantitative disparity at the macro level. The types of supply and demand imbalance for IT professionals are marked out. The methods are proposed for estimating the structural mismatch in the labour market for IT professionals, the degree of supply and demand imbalance for IT professionals based on fuzzy unbalance scale. The algorithm of fuzzy classification of states of imbalance is proposed.This document considers the processes of modelling supply and demand interactions in the labour market for information technology experts (IT professionals) and management of their quantitative disparity at the macro level. The types of supply and demand imbalance for IT professionals are marked out. The methods are proposed for estimating the structural mismatch in the labour market for IT professionals, the degree of supply and demand imbalance for IT professionals based on fuzzy unbalance scale. The algorithm of fuzzy classification of states of imbalance is proposed.
Cloud Computing Environments Which Can Be Used in Health Education Buber, Mustafa; Sucu, Fadime; Bulut, Ismail; Kursun, Ramazan
International Journal of Intelligent Systems and Applications in Engineering Vol 3, No 4 (2015)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.92756

Abstract

At the present time, it is known that cloud computing technologies began to be used widely in information technology. The purpose of this study is to provide information about cloud technologies that can be used in health education. For this purpose,firstly as sample of the learning content management system, Edmodo has been introduced. Hapyak Interactive Video Creation Platform which can be used for creating interactive video to enrich the learning environment that will be submitted with Edmodo, Bubbl.Us which can be benefited from summarizing the discussed and Socrative platforms which enable concept maps application and online test creation have been introduced.

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