Pub Date : 2014-06-23DOI: 10.1109/INISTA.2014.6873635
R. Ghiasi, M. Ettefagh, V. Sadeghi, Y. Ajabshirchi, M. Taki
In recent years, ANN (artificial neural network) method has been used as an effective method for analyses of the characteristic parameters in internal combustion engines. Also, determination of the best network structure is an important part of the research work in this branch. So, this subject is the main idea of the current study. The most reliable network structure has been determined for prediction of two important engine after-treatment parameters. These parameters are pressure and temperature of the gases at EVO (exhaust valve opening) time. Outputs of four ANN models have been compared with the results of a reliable developed multi-zone combustion model. The ANN models, which have been considered in this research work, are MLP (Multi Layer Perception), RBF (Radial Basis Function), SOM (Self Organized Map) and GFF (Generalized Feed Forward) with training algorithms of LM (Levenberg Marquart) and MOM (Momentum), respectively. Finally, the MLP-LM model has been proposed as the most appropriate model.
{"title":"Prediction of a diesel engine exhaust gases physical properties with artificial neural network","authors":"R. Ghiasi, M. Ettefagh, V. Sadeghi, Y. Ajabshirchi, M. Taki","doi":"10.1109/INISTA.2014.6873635","DOIUrl":"https://doi.org/10.1109/INISTA.2014.6873635","url":null,"abstract":"In recent years, ANN (artificial neural network) method has been used as an effective method for analyses of the characteristic parameters in internal combustion engines. Also, determination of the best network structure is an important part of the research work in this branch. So, this subject is the main idea of the current study. The most reliable network structure has been determined for prediction of two important engine after-treatment parameters. These parameters are pressure and temperature of the gases at EVO (exhaust valve opening) time. Outputs of four ANN models have been compared with the results of a reliable developed multi-zone combustion model. The ANN models, which have been considered in this research work, are MLP (Multi Layer Perception), RBF (Radial Basis Function), SOM (Self Organized Map) and GFF (Generalized Feed Forward) with training algorithms of LM (Levenberg Marquart) and MOM (Momentum), respectively. Finally, the MLP-LM model has been proposed as the most appropriate model.","PeriodicalId":339652,"journal":{"name":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129102775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-23DOI: 10.1109/INISTA.2014.6873650
M. A. Kizrak, K. Bayram, B. Bolat
In this work, Classical Turkish Music songs are classified into six makams. Makam is a modal framework for melodic development in Classical Turkish Music. The effect of the sound clip length on the system performance was also evaluated. The Mel Frequency Cepstral Coefficients (MFCC) were used as features. Obtained data were classified by using Probabilistic Neural Network. The best correct recognition ratio was obtained as 89,4% by using a clip length of 6 s.
{"title":"Classification of Classic Turkish Music Makams","authors":"M. A. Kizrak, K. Bayram, B. Bolat","doi":"10.1109/INISTA.2014.6873650","DOIUrl":"https://doi.org/10.1109/INISTA.2014.6873650","url":null,"abstract":"In this work, Classical Turkish Music songs are classified into six makams. Makam is a modal framework for melodic development in Classical Turkish Music. The effect of the sound clip length on the system performance was also evaluated. The Mel Frequency Cepstral Coefficients (MFCC) were used as features. Obtained data were classified by using Probabilistic Neural Network. The best correct recognition ratio was obtained as 89,4% by using a clip length of 6 s.","PeriodicalId":339652,"journal":{"name":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126274241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-06-12DOI: 10.1109/SIU.2014.6830249
Mustafa Ozcelikors, A. Coskun, M. Say, Uğur Yayan, Mehmet Akcakoca, Islam Kilic
Increasing elderly people population and people with disabilities constitute a huge demand for wheelchairs. Wheelchairs have an important role on improving the lives and mobilization of people with disabilities. Moreover, autonomous wheelchairs constitute a suitable research platform for academic and industrial researchers. In this study, Finite state machine (FSM) based high-level controller and Kinect based navigation algorithm have been developed for ATEKS (Intelligent Wheelchair) which has high-tech control mechanisms, low-cost sensors and open source software (ROS, GAZEBO, ANDROID).
{"title":"Kinect based Intelligent Wheelchair navigation with potential fields","authors":"Mustafa Ozcelikors, A. Coskun, M. Say, Uğur Yayan, Mehmet Akcakoca, Islam Kilic","doi":"10.1109/SIU.2014.6830249","DOIUrl":"https://doi.org/10.1109/SIU.2014.6830249","url":null,"abstract":"Increasing elderly people population and people with disabilities constitute a huge demand for wheelchairs. Wheelchairs have an important role on improving the lives and mobilization of people with disabilities. Moreover, autonomous wheelchairs constitute a suitable research platform for academic and industrial researchers. In this study, Finite state machine (FSM) based high-level controller and Kinect based navigation algorithm have been developed for ATEKS (Intelligent Wheelchair) which has high-tech control mechanisms, low-cost sensors and open source software (ROS, GAZEBO, ANDROID).","PeriodicalId":339652,"journal":{"name":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115204202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-04-23DOI: 10.1109/SIU.2014.6830251
Uğur Yayan, Bora Akar, Fatih Inan, A. Yazıcı
Nowadays, location based applications increasingly used in many areas. Although outdoor navigation software applications are mature and widely used, improvements are required for indoor navigation. The applications such as guidance of disabled people, applications for security, visitor tracking, address mapping, the organization of services, automatic tourist guidance etc. are also needed for indoor environments. In this study, location-based navigation software has been developed for indoor environment. New plug-ins are added to navigation software, so that it can be used in Intelligent Wheelchair (ATEKS) systems, too. Thus, the software is specialized for autonomous robot application. The software is developed on Android platform.
{"title":"Development of indoor navigation software for intelligent wheelchair","authors":"Uğur Yayan, Bora Akar, Fatih Inan, A. Yazıcı","doi":"10.1109/SIU.2014.6830251","DOIUrl":"https://doi.org/10.1109/SIU.2014.6830251","url":null,"abstract":"Nowadays, location based applications increasingly used in many areas. Although outdoor navigation software applications are mature and widely used, improvements are required for indoor navigation. The applications such as guidance of disabled people, applications for security, visitor tracking, address mapping, the organization of services, automatic tourist guidance etc. are also needed for indoor environments. In this study, location-based navigation software has been developed for indoor environment. New plug-ins are added to navigation software, so that it can be used in Intelligent Wheelchair (ATEKS) systems, too. Thus, the software is specialized for autonomous robot application. The software is developed on Android platform.","PeriodicalId":339652,"journal":{"name":"2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125351707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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