{"title":"An Efficient PSO Based Ensemble Classification Model on High Dimensional Datasets","authors":"G. Lalithakumari, N. NagamalleswaraRao.","doi":"10.5121/IJSC.2017.8401","DOIUrl":"https://doi.org/10.5121/IJSC.2017.8401","url":null,"abstract":"","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"52 1","pages":"01-11"},"PeriodicalIF":0.0,"publicationDate":"2017-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86160330","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}
U. Umoh, D. Asuquo, Imo J. Eyoh, Margaret Offisong
Call admission control (CAC), a resource management function, is required to regulate network access to provide the required levels of QoS to emerging services in Fourth Generation (4G) mobile networks. However, CAC is one of the challenging issues for quality of service (QoS) due to imprecise, uncertain and inaccurate measurements of network data. Although type-1 fuzzy system (T1FLS) can handle the uncertainties related to imprecise data, it cannot adequately handle new problems posed by the complex nature of data traffic and diversity of the QoS requirements of data users. This is because T1FLS is characterised by precise membership functions. This study presents an intelligent CAC controller for 4G network using interval type-2 fuzzy logic (IT2FL) for providing guaranteed QoS requirements. The IT2FLS with fuzzy membership functions can fully cope with uncertainties associated with such dynamic network environments by raising its accuracy for a better performance. The Karnik–Mendel (KM) iterative algorithm and Wu-Mendel (WM) approach are explored for computing the centroid and to derive innerand outer-bound sets for the type-reduced set of IT2FS respectively. The study also implements a T1FLS – CAC for comparison with the KM and WM methods. The empirical comparison is made on the designed system with synthetic datasets. Simulation and analyses of results indicate that IT2FLS-CAC using WU approach achieves minimal call blocking probability and provides high performance in CAC decision making with a more reduced root mean square error (RMSE) than IT2FLS-CAC using KM and IT1FLS approaches.
{"title":"An Intelligent Call Admission Controller for Guaranteed QoS in 4G Mobile Networks Full Text","authors":"U. Umoh, D. Asuquo, Imo J. Eyoh, Margaret Offisong","doi":"10.5121/ijsc.2017.8403","DOIUrl":"https://doi.org/10.5121/ijsc.2017.8403","url":null,"abstract":"Call admission control (CAC), a resource management function, is required to regulate network access to provide the required levels of QoS to emerging services in Fourth Generation (4G) mobile networks. However, CAC is one of the challenging issues for quality of service (QoS) due to imprecise, uncertain and inaccurate measurements of network data. Although type-1 fuzzy system (T1FLS) can handle the uncertainties related to imprecise data, it cannot adequately handle new problems posed by the complex nature of data traffic and diversity of the QoS requirements of data users. This is because T1FLS is characterised by precise membership functions. This study presents an intelligent CAC controller for 4G network using interval type-2 fuzzy logic (IT2FL) for providing guaranteed QoS requirements. The IT2FLS with fuzzy membership functions can fully cope with uncertainties associated with such dynamic network environments by raising its accuracy for a better performance. The Karnik–Mendel (KM) iterative algorithm and Wu-Mendel (WM) approach are explored for computing the centroid and to derive innerand outer-bound sets for the type-reduced set of IT2FS respectively. The study also implements a T1FLS – CAC for comparison with the KM and WM methods. The empirical comparison is made on the designed system with synthetic datasets. Simulation and analyses of results indicate that IT2FLS-CAC using WU approach achieves minimal call blocking probability and provides high performance in CAC decision making with a more reduced root mean square error (RMSE) than IT2FLS-CAC using KM and IT1FLS approaches.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"137 1","pages":"21-37"},"PeriodicalIF":0.0,"publicationDate":"2017-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87958490","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}
In this paper, the issue of passing wheeled vehicles from pits is discussed. The issue is modeled by defining the limits of passing wheeled vehicles. The proposed model has been studied based on changes in the effective parameters. Finally, in order to describe the problem, the proposed model has been solved for wheeled vehicles based on the effective parameters by using one of the numerical methods.
{"title":"Analysis of traversable pits model to make intelligent wheeled vehicles","authors":"F. Abbasi","doi":"10.5899/2017/JSCA-00100","DOIUrl":"https://doi.org/10.5899/2017/JSCA-00100","url":null,"abstract":"In this paper, the issue of passing wheeled vehicles from pits is discussed. The issue is modeled by defining the limits of passing wheeled vehicles. The proposed model has been studied based on changes in the effective parameters. Finally, in order to describe the problem, the proposed model has been solved for wheeled vehicles based on the effective parameters by using one of the numerical methods.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"20 1","pages":"67-78"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78204814","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}
In wireless sensor network, routing data efficiently to the base station is a big issue and for this purpose, a number of routing algorithms are invented by researchers. Clustering plays a very important role in the design and as well as development of wireless sensor networks for well distribution of network and also to route data efficiently. In this paper, we had done the enhancement of divide and rule strategy that is basically route information protocol based upon static clustering and dynamic cluster head selection. Simulation results show that our technique outperforms DR, LEACH, and AODV on the basis of packet loss, delay, and throughput. INDEX TERMS Routing protocols, clustering, Coverage hole and energy hole.
{"title":"Comparative Analysis of Route Information Based Enhanced Divide and Rule Strategy in WSNs","authors":"Rajeev Kumar, H. Singh, Amit Sharma","doi":"10.5121/ijsc.2017.8201","DOIUrl":"https://doi.org/10.5121/ijsc.2017.8201","url":null,"abstract":"In wireless sensor network, routing data efficiently to the base station is a big issue and for this purpose, a number of routing algorithms are invented by researchers. Clustering plays a very important role in the design and as well as development of wireless sensor networks for well distribution of network and also to route data efficiently. In this paper, we had done the enhancement of divide and rule strategy that is basically route information protocol based upon static clustering and dynamic cluster head selection. Simulation results show that our technique outperforms DR, LEACH, and AODV on the basis of packet loss, delay, and throughput. INDEX TERMS Routing protocols, clustering, Coverage hole and energy hole.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"49 1","pages":"01-08"},"PeriodicalIF":0.0,"publicationDate":"2017-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74574907","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}
The increasing rate of data sharing among organizations could maximize the risk of leaking sensitive knowledge. Trying to solve this problem leads to increase the importance of privacy preserving within the process of data sharing. In this study is focused on privacy preserving in classification rules mining as a technique of data mining. We propose a blocking algorithm to hiding sensitive classification rules. In the solution, rules' hiding occurs as a result of editing a set of transactions which satisfy sensitive classification rules. The proposed approach tries to deceive and block adversaries by inserting some dummy transactions. Finally, the solution has been evaluated and compared with other available solutions. Results show that limiting the number of attributes existing in each sensitive rule will lead to a decrease in both the number of lost rules and the production rate of ghost rules.
{"title":"Using blocking approach to preserve privacy in classification rules by inserting dummy Transaction","authors":"Doryaneh Hossien Afshari, F. Z. Boroujeni","doi":"10.5899/2017/JSCA-00073","DOIUrl":"https://doi.org/10.5899/2017/JSCA-00073","url":null,"abstract":"The increasing rate of data sharing among organizations could maximize the risk of leaking sensitive knowledge. Trying to solve this problem leads to increase the importance of privacy preserving within the process of data sharing. In this study is focused on privacy preserving in classification rules mining as a technique of data mining. We propose a blocking algorithm to hiding sensitive classification rules. In the solution, rules' hiding occurs as a result of editing a set of transactions which satisfy sensitive classification rules. The proposed approach tries to deceive and block adversaries by inserting some dummy transactions. Finally, the solution has been evaluated and compared with other available solutions. Results show that limiting the number of attributes existing in each sensitive rule will lead to a decrease in both the number of lost rules and the production rate of ghost rules.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"31 1","pages":"44-52"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87487728","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}
B. Venkataramana, L. Padmasree, M. S. Rao, G. Ganesan, K. R. Krishna
As in the medical field, for one disease there require samples given by diagnosis. The samples will be analyzed by a doctor or a pharmacist. As the no. of patients increases their samples also increases, there require more time to analyze samples for deciding the stage of the disease. To analyze the sample every time requires a skilled person. The samples can be classified by applying them to clustering algorithms. Data clustering has been considered as the most important raw data analysis method used in data mining technology. Most of the clustering techniques proved their efficiency in many applications such as decision making systems, medical sciences, earth sciences etc. Partition based clustering is one of the main approach in clustering. There are various algorithms of data clustering, every algorithm has its own advantages and disadvantages. This work reports the results of classification performance of three such widely used algorithms namely K-means (KM), Fuzzy c-means and Fuzzy Possibilistic c-Means (FPCM) clustering algorithms. To analyze these algorithms three known data sets from UCI machine learning repository are taken such as thyroid data, liver and wine. The efficiency of clustering output is compared with the classification performance, percentage of correctness. The experimental results show that K-means and FCM give same performance for liver data. And FCM and FPCM are giving same performance for thyroid and wine data. FPCM has more efficient classification performance in all the given data sets.
{"title":"Implementation of Clustering Algorithms for real datasets in Medical Diagnostics using MATLAB","authors":"B. Venkataramana, L. Padmasree, M. S. Rao, G. Ganesan, K. R. Krishna","doi":"10.5899/2017/JSCA-00087","DOIUrl":"https://doi.org/10.5899/2017/JSCA-00087","url":null,"abstract":"As in the medical field, for one disease there require samples given by diagnosis. The samples will be analyzed by a doctor or a pharmacist. As the no. of patients increases their samples also increases, there require more time to analyze samples for deciding the stage of the disease. To analyze the sample every time requires a skilled person. The samples can be classified by applying them to clustering algorithms. Data clustering has been considered as the most important raw data analysis method used in data mining technology. Most of the clustering techniques proved their efficiency in many applications such as decision making systems, medical sciences, earth sciences etc. Partition based clustering is one of the main approach in clustering. There are various algorithms of data clustering, every algorithm has its own advantages and disadvantages. This work reports the results of classification performance of three such widely used algorithms namely K-means (KM), Fuzzy c-means and Fuzzy Possibilistic c-Means (FPCM) clustering algorithms. To analyze these algorithms three known data sets from UCI machine learning repository are taken such as thyroid data, liver and wine. The efficiency of clustering output is compared with the classification performance, percentage of correctness. The experimental results show that K-means and FCM give same performance for liver data. And FCM and FPCM are giving same performance for thyroid and wine data. FPCM has more efficient classification performance in all the given data sets.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"15 1","pages":"53-66"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81828213","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}
{"title":"A Proposed Multi-Domain Approach for Automatic Classification of Text Documents","authors":"Abdelrahman M. Arab, A. Gadallah, A. Salah","doi":"10.5121/IJSC.2017.8101","DOIUrl":"https://doi.org/10.5121/IJSC.2017.8101","url":null,"abstract":"","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"2 1","pages":"01-12"},"PeriodicalIF":0.0,"publicationDate":"2017-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87150533","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}
The distributed system of Grid subscribes the non-homogenous sources at a vast level in a dynamic manner. The resource discovery manner is very influential on the efficiency and of quality the system functionality. The “Bitmap” model is based on the hierarchical and conscious search model that allows for less traffic and low number of messages in relation to other methods in this respect. This proposed method is based on the hierarchical and conscious search model that enhances the Bitmap method with the objective to reduce traffic, reduce the load of resource management processing, reduce the number of emerged messages due to resource discovery and increase the resource according speed. The proposed method and the Bitmap method are simulated through Arena tool. This proposed model is abbreviated as RNTL.
{"title":"Resource discovery algorithm based on hierarchical model and Conscious search in Grid computing system","authors":"Nasim Nickbakhsh, M. Aghaei","doi":"10.5899/2017/JSCA-00086","DOIUrl":"https://doi.org/10.5899/2017/JSCA-00086","url":null,"abstract":"The distributed system of Grid subscribes the non-homogenous sources at a vast level in a dynamic manner. The resource discovery manner is very influential on the efficiency and of quality the system functionality. The “Bitmap” model is based on the hierarchical and conscious search model that allows for less traffic and low number of messages in relation to other methods in this respect. This proposed method is based on the hierarchical and conscious search model that enhances the Bitmap method with the objective to reduce traffic, reduce the load of resource management processing, reduce the number of emerged messages due to resource discovery and increase the resource according speed. The proposed method and the Bitmap method are simulated through Arena tool. This proposed model is abbreviated as RNTL.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"37 1","pages":"24-43"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85064239","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}
In this paper we propose Runge-Kutta Fehlberg method for solving fully fuzzy differential equations (FFDEs) of the form $y^{'}(t)=aotimes y(t), y(0)=y_{0}, tin[0,T] $ under strongly generalized H-differentiability. The algorithm used here is based on cross product of two fuzzy numbers. Using cross product we investigate the problem of finding a numerical approximation of solutions. The convergence of this method is discussed and numerical example is included to verify the reliability of proposed method.
在强广义h -可微性条件下，给出了求解形式为$y^{'}(t)=a o_ y(t)， y(0)=y_{0}， t In [0, t] $的全模糊微分方程的Runge-Kutta Fehlberg方法。这里使用的算法是基于两个模糊数的外积。利用叉乘研究了求解的数值逼近问题。讨论了该方法的收敛性，并通过数值算例验证了该方法的可靠性。
{"title":"Numerical solution of first-order fully fuzzy differential equations by Runge-Kutta Fehlberg method under strongly generalized H-differentiability","authors":"D. Vivek, K. Kanagarajan, S. Harikrishnan","doi":"10.5899/2017/JSCA-00069","DOIUrl":"https://doi.org/10.5899/2017/JSCA-00069","url":null,"abstract":"In this paper we propose Runge-Kutta Fehlberg method for solving fully fuzzy differential equations (FFDEs) of the form $y^{'}(t)=aotimes y(t), y(0)=y_{0}, tin[0,T] $ under strongly generalized H-differentiability. The algorithm used here is based on cross product of two fuzzy numbers. Using cross product we investigate the problem of finding a numerical approximation of solutions. The convergence of this method is discussed and numerical example is included to verify the reliability of proposed method.","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"176 1","pages":"1-23"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79825444","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}
{"title":"Face Sketch Generation Using Evolutionary Computing","authors":"K. BansodeN, K. SinhaP.","doi":"10.5121/IJSC.2016.7401","DOIUrl":"https://doi.org/10.5121/IJSC.2016.7401","url":null,"abstract":"","PeriodicalId":38638,"journal":{"name":"International Journal of Advances in Soft Computing and its Applications","volume":"93 1","pages":"01-10"},"PeriodicalIF":0.0,"publicationDate":"2016-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75016703","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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