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Web page classification using firefly optimization 网页分类使用萤火虫优化
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577619
E. Saraç, S. Ozel
{"title":"Web page classification using firefly optimization","authors":"E. Saraç, S. Ozel","doi":"10.1109/INISTA.2013.6577619","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577619","url":null,"abstract":"Increase in the amount of information on the Web has caused the need for accurate automated classifiers for Web pages to maintain Web directories and to increase search engines' performance. As every (HTML/XML) tag and every term on each Web page can be considered as a feature, we need efficient methods to select best features to reduce feature space of the Web page classification problem. In this study, our aim is to apply a recent optimization technique namely the firefly algorithm (FA), to select best features for Web page classification problem. The firefly algorithm (FA) is a metaheuristic algorithm, inspired by the flashing behavior of fireflies. In this study, we use FA to select a subset of features, and to evaluate the fitness of the selected features J48 classifier of the Weka data mining tool is employed. WebKB and Conference datasets were used to evaluate the effectiveness of the proposed feature selection system. We observed that when a subset of features are selected by using FA, WebKB and Conference datasets were classified without loss of accuracy, even more, time needed to classify new Web pages reduced sharply as the number of features were decreased.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128779355","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}
引用次数: 43
The effect of integration types on FLC based MPPT systems 集成类型对基于FLC的MPPT系统的影响
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577657
R. Çakmak, I. Altas
{"title":"The effect of integration types on FLC based MPPT systems","authors":"R. Çakmak, I. Altas","doi":"10.1109/INISTA.2013.6577657","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577657","url":null,"abstract":"Operating the photovoltaic (PV) array at its maximum power available is important to increase system efficiency. In order to operate PV systems at their maximum power point, many maximum power point tracking (MPPT) methods have been proposed. Fuzzy logic controller (FLC) based MPPT methods have some advantages over classical MPPT methods. The way of using the FLC outputs has an effective role in obtaining the desired results. In this study, the effect of a discrete-time integration method investigated in MPPT including FLC whose output is subjected to integration operation. The system has been designed and simulated in MATLAB/Simulink software. The results were given as a comparison.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127910440","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}
引用次数: 0
Developing agricultural irrigation technology compatible with national energy efficiency policy 发展与国家节能政策相适应的农业灌溉技术
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577661
Naim Karasekreter, U. Fidan
{"title":"Developing agricultural irrigation technology compatible with national energy efficiency policy","authors":"Naim Karasekreter, U. Fidan","doi":"10.1109/INISTA.2013.6577661","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577661","url":null,"abstract":"When you look at the usage percentage of water resources in the world in terms of sectors you figure out that it is mostly used in agricultural production with 69 percent of the rate. It is vital that managing such kind of resource perfectly and supplying it to the needs of human being is as important as water itself if you pay attention the earth is static and the population has been rising continuously. When the studies inspected, there are a lot of information concerning the conscious and controlled usage of agricultural water. However the studies have calculated the irrigation periods looking soil moisture, temperature, plant diversity and other parameters. In the irrigation plan offered in the study, it was determined that via night-irrigation and caring the needs of the plants, 20,46 percent of the water saving and 23,9 percent of the energy saving were provided. 20,46 percent of the water saving shows that water resources will be able to used longer if you take care that 69 percent of existing water resources is being used in agricultural irrigation.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121047920","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}
引用次数: 2
A model selection algorithm for mixture model clustering of heterogeneous multivariate data 异构多元数据混合模型聚类的模型选择算法
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577617
H. Erol
{"title":"A model selection algorithm for mixture model clustering of heterogeneous multivariate data","authors":"H. Erol","doi":"10.1109/INISTA.2013.6577617","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577617","url":null,"abstract":"A model selection algorithm is developed for finding the best model among a set of mixture of normal densities fitted to heterogeneous multivariate data. Model selection algorithm proposed first finds total number of mixture of normal densities then selects possible number of mixture of normal densities and finally searches the best model among them in mixture model clustering of heterogeneous multivariate data. Log-likelihood function, Akaike's information criteria and Bayesian information criteria values are computed and graphically ploted for each mixture of normal densities. The best model is chosen according to the values of these information criterions.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"432 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116005243","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}
引用次数: 6
Transmission expansion planning considering maximizing penetration level of renewable sources 考虑可再生能源渗透水平最大化的输电扩展规划
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577640
F. Ugranli, E. Karatepe
{"title":"Transmission expansion planning considering maximizing penetration level of renewable sources","authors":"F. Ugranli, E. Karatepe","doi":"10.1109/INISTA.2013.6577640","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577640","url":null,"abstract":"Recently, integration of intermittent sources into the power systems has gained most interest in distributed generation environment. Among the others, wind based generation is the most promising renewable based technology. The volatility of these sources requires the careful planning of power systems. This paper proposed a novel genetic algorithm based method to determine the optimal trade-off between wind energy spilled and transmission line investment by deciding the location of new transmission lines. By this way, power system planners can avoid over investment of transmission lines while providing maximum usage of wind turbines. The proposed method is illustrated using the IEEE 24 bus reliability test system.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132014755","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}
引用次数: 5
Parameter tuning of artificial bee colony algorithm for Gaussian noise elimination on digital images 数字图像高斯噪声消噪的人工蜂群算法参数整定
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577621
S. Kockanat, N. Karaboga
{"title":"Parameter tuning of artificial bee colony algorithm for Gaussian noise elimination on digital images","authors":"S. Kockanat, N. Karaboga","doi":"10.1109/INISTA.2013.6577621","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577621","url":null,"abstract":"In this paper, the control parameters of the artificial bee colony algorithm were examined to determine for the best performance of the noise elimination problem on gray level digital images. In order to eliminate a noise, a two dimensional finite impulse response digital filter was designed and the artificial bee colony algorithm was used to adjust its coefficient matrix. For the best selected control parameters, the designed two dimensional finite impulse response digital filter was used to eliminate the Gaussian noise on the gray level digital images at different noise densities and the performance of the designed filter was compared in terms of the noise tolerance.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125364485","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}
引用次数: 10
Recognizing the dialogue phases Analysis of human-human phone calls 识别对话阶段人与人之间的电话分析
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577622
M. Koit
{"title":"Recognizing the dialogue phases Analysis of human-human phone calls","authors":"M. Koit","doi":"10.1109/INISTA.2013.6577622","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577622","url":null,"abstract":"We investigate how to determine the dialogue structure. The empirical material of the study is a small sub-corpus of telemarketing calls. Dialogue acts are annotated in the corpus. Rules for identification of different phases of a telemarketing call will be formulated on the basis of sequences of dialogue acts and their position in dialogue. The results of the study have being used in development of web-based software for automatic pragmatic analysis of dialogues which makes it possible to recognize dialogue acts as well as the general structure of dialogues and sub-dialogues.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124044106","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}
引用次数: 1
Wikipedia based semantic smoothing for twitter sentiment classification 基于维基百科的推特情感分类语义平滑
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577649
Dilara Torunoglu, Gurkan Telseren, Ozgun Sagturk, M. Ganiz
{"title":"Wikipedia based semantic smoothing for twitter sentiment classification","authors":"Dilara Torunoglu, Gurkan Telseren, Ozgun Sagturk, M. Ganiz","doi":"10.1109/INISTA.2013.6577649","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577649","url":null,"abstract":"Sentiment classification is one of the important and popular application areas for text classification in which texts are labeled as positive and negative. Moreover, Naïve Bayes (NB) is one of the mostly used algorithms in this area. NB having several advantages on lower complexity and simpler training procedure, it suffers from sparsity. Smoothing can be a solution for this problem, mostly Laplace Smoothing is used; however in this paper we propose Wikipedia based semantic smoothing approach. In our study we extend semantic approach by using Wikipedia article titles that exist in training documents, categories and redirects of these articles as topic signatures. Results of the extensive experiments show that our approach improves the performance of NB and even can exceed the accuracy of SVM on Twitter Sentiment 140 dataset.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121513423","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}
引用次数: 30
A smart solution for transmitter localization 一个智能的发射机定位解决方案
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577664
Cem Yeniceri, Tolga Tuna, A. Yazıcı, Hikmet Yucel, Uğur Yayan, Veli Bayar
{"title":"A smart solution for transmitter localization","authors":"Cem Yeniceri, Tolga Tuna, A. Yazıcı, Hikmet Yucel, Uğur Yayan, Veli Bayar","doi":"10.1109/INISTA.2013.6577664","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577664","url":null,"abstract":"Localization plays an important role in many applications such as robotic, signal processing and sensor networks. In the previous study, an indoor positioning system (İCKON) was developed. The İCKON uses only ultrasonic signals to calculate the position of mobile unit at cm level accuracy. For this accuracy, transmitter positions must be known in advance. These directly affect the mobile unit position calculation. In İCKON system transmitters' coordinates are determined by manual measurements. It needs long time depending on number of transmitters. In this study, a mobile application is developed for automatic transmitter position calculation. The mobile application uses Time of Arrival measurement and Trilateration method for the position calculation.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115551925","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}
引用次数: 9
Training ANFIS using artificial bee colony algorithm 利用人工蜂群算法训练ANFIS
2013 IEEE INISTA Pub Date : 2013-06-19 DOI: 10.1109/INISTA.2013.6577625
D. Karaboğa, Ebubekir Kaya
{"title":"Training ANFIS using artificial bee colony algorithm","authors":"D. Karaboğa, Ebubekir Kaya","doi":"10.1109/INISTA.2013.6577625","DOIUrl":"https://doi.org/10.1109/INISTA.2013.6577625","url":null,"abstract":"This paper introduces a new approach for training the adaptive network based fuzzy inference system (ANFIS). In this study, we apply one of the swarm intelligent branches, named artificial bee colony algorithm (ABC) for training. We use ABC for training the antecedent parameters and the conclusion parameters. The proposed method is applied to identification of the nonlinear system. The simulation results show that in comparison with genetic algorithm (GA), backpropagation (BP) and hybrid learning (HL) that is a combination of least-squares and backpropagation. The results show ABC optimizes ANFIS parameters are better than GA, BL and HL.","PeriodicalId":301458,"journal":{"name":"2013 IEEE INISTA","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115253442","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}
引用次数: 36
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