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Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los ...

Jith Sarker, Abu Shami Md. Zadid Shifat, Rezoan Ahmed Shuvro
2017 Advances in Science, Technology and Engineering Systems  
Considering all of the graphical illustrations, we do like to conclude that, graphene will be a successor in post silicon era and bring revolutionary changes in the field of fabrication technology.  ...  In the end, effect of channel length on device performance has been justified. Variation of effective mobility and minimum carrier density with respect to channel length has also been observed.  ...  We also determined the effective mobility of charge carriers and minimum carrier concentration in the channel according to channel length. Both illustration yields satisfactory outcomes.  ... 
doi:10.25046/aj0203177 fatcat:qhd2rteuajdqzo77fq74ixwevu

The effectiveness of using diversity to select multiple classifier systems with varying classification thresholds

Harris K Butler, Mark A Friend, Kenneth W Bauer, Trevor J Bihl
2018 Journal of Algorithms & Computational Technology  
Historically, classifier ensemble accuracy has been used to select which pattern recognition algorithms are included in a multiple classifier system.  ...  Using a wide range of classification data sets, methodologies, and fusion techniques, current diversity research is extended by expanding classifier domains before employing fusion methodologies.  ...  Introduction There is considerable effort in the pattern recognition field to combine the outputs of individual classifiers to create a multiple classifier system (MCS), also termed an "ensemble," which  ... 
doi:10.1177/1748301818761132 fatcat:samr6inmzvh5fmldqbt44rl4vi

Diversity in multiple classifier ensembles based on binary feature quantisation with application to face recognition

K. Sirlantzis, S. Hoque, M.C. Fairhurst
2008 Applied Soft Computing  
In this paper we present two methods to create multiple classifier systems based on an initial transformation of the original features to the binary domain and subsequent decompositions (quantisation).  ...  Rather, some type of trade off seems to be necessary between participant classifiers' accuracy and ensemble diversity in order to achieve maximum recognition gains. #  ...  Acknowledgement The authors gratefully acknowledge the support of the UK Engineering and Physical Sciences Research Council (EPSRC).  ... 
doi:10.1016/j.asoc.2005.08.002 fatcat:k6cb5c35r5eqhfkzxwx462qnbe

A Learning Scheme for Microgrid Islanding and Reconnection [article]

Carter Lassetter, Eduardo Cotilla-Sanchez, Jinsub Kim
2017 arXiv   pre-print
A dynamics simulator fed with pre-acquired system parameters is used to create training data for the SVM in various operating states.  ...  A support vector machine (SVM) leveraging real-time data from phasor measurement units (PMUs) is proposed to predict in real time whether the reconnection of a sub-network to the main grid would lead to  ...  Section II gives a brief background of Support Vector Machines (SVM). Section III covers the methodology to create a power system classifier.  ... 
arXiv:1611.05317v2 fatcat:jprvtodhnnhk3azq3tewvi65s4

Classifier Selection Based on the Correlation of Diversity Measures: When Fewer Is More

Fabio A. Faria, Jefersson A. dos Santos, Sudeep Sarkar, Anderson Rocha, Ricardo da S. Torres
2013 2013 XXVI Conference on Graphics, Patterns and Images  
Diversity measures are used to rank pairs of classifiers and the agreement among ranked lists guides the classifier selection process.  ...  Examples of successful initiatives are those dedicated to the development of learning techniques for data fusion or Multiple Classifier Systems (MCS).  ...  [10] , for example, proposed an innovative and effective ensemble system by using meta-learning based on support vector machines.  ... 
doi:10.1109/sibgrapi.2013.12 dblp:conf/sibgrapi/FariaSSRT13 fatcat:ippk2zat6zg4lndawp42lmsace


Mikhail Granik, Vinnytsia National Technical University, Vladimir Mesyura, Vinnytsia National Technical University
2018 Problems of Information Technology  
It is suggested to use number of different machine learning techniques for that and uniting them to a single system (ensemble) which predicts probability that given statement is true or not and performs  ...  The paper is devoted to an attempt of classifying statements made by public figures as true or false (fake).  ...  This makes a data set useful for creating a system which will classify statements as true or false.  ... 
doi:10.25045/jpit.v09.i2.06 fatcat:c46u2xfshjfsjpzl62hbupdsge

Wagging for Combining Weighted One-class Support Vector Machines

Bartosz Krawczyk, Michał Woźniak
2015 Procedia Computer Science  
A weighted version of boosting is used, and the output weights for each object are used directly in the process of training Weighted One-Class Support Vector Machines.  ...  This introduces a diversity into the pool of one-class classifiers and extends the competence of formed ensemble.  ...  Details of the chosen data sets are given in Table 1 . Set-up For the experiment a Weighted One-Class Support Vector Machine with a RBF kernel is used as a base classifier.  ... 
doi:10.1016/j.procs.2015.05.351 fatcat:uvdzwt2nfrdltf4tk5gctfd6g4

Multi-sensor fusion based on multiple classifier systems for human activity identification

Henry Friday Nweke, Ying Wah Teh, Ghulam Mujtaba, Uzoma Rita Alo, Mohammed Ali Al-garadi
2019 Human-Centric Computing and Information Sciences  
In addition, the study suggests a promising potential of hybrid feature selection approach, diversity-based multiple classifier systems to improve mobile and wearable sensor-based human activity detection  ...  The benefit of the proposed multisensor fusion is the ability to utilize distinct feature characteristics of individual sensor and multiple classifier systems to improve recognition accuracy.  ...  Acknowledgements The authors would like to thank University of Malaya for sponsoring the paper through the BKP Special grants and researchers that collected the datasets that were used to support this  ... 
doi:10.1186/s13673-019-0194-5 fatcat:oif3o7dfhzdwhcqeept7t5jypq

Creating Ensemble Classifiers with Information Entropy Diversity Measure

Jiangbo Zou, Xiaokang Fu, Lingling Guo, Chunhua Ju, Jingjing Chen, Xiaokang Zhou
2021 Security and Communication Networks  
One of the major problems in creating ensemble classifiers is the classification accuracy and diversity of the component classifiers.  ...  In this algorithm, information entropy is introduced to measure the diversity of component classifiers, and a cyclic iterative optimization selection tactic is applied to select component classifiers from  ...  , or interpretation of data; the writing of the manuscript, or the decision to publish the results.  ... 
doi:10.1155/2021/9953509 fatcat:spm2o7nnc5hbji6jnetd42ntxq

Semantics-based Web service classification using morphological analysis and ensemble learning techniques

S. Sowmya Kamath, V. S. Ananthanarayana
2016 International Journal of Data Science and Analytics  
Using these feature vector models, services are classified as per their domain, using ensemble machine learning methods.  ...  To capture the functional diversity of the services, different feature vector selection techniques are used to represent a service in vector space, with the aim of finding the optimal set of features.  ...  Support Vector Machine (SVM) [15] is a supervised learning method that uses the concept of hyperplanes for classifying high-dimensional data.  ... 
doi:10.1007/s41060-016-0026-x dblp:journals/ijdsa/KamathA16 fatcat:yvigqa2tcrdgdltk3vuwtappki

A Multiple SVM System for Classification of Hyperspectral Remote Sensing Data

Behnaz Bigdeli, Farhad Samadzadegan, Peter Reinartz
2013 Journal of the Indian Society of Remote Sensing  
This paper presents a new method for classification of hyperspectral data based on a band clustering strategy through a multiple Support Vector Machine system.  ...  Referring to the limitation of single classifier in these situations, Multiple Classifier Systems (MCS) may have better performance than single classifier.  ...  It means that multiple classifier system for the AVIRIS data set exhibits higher diversity and lower correlation measures in comparison ROSIS data.  ... 
doi:10.1007/s12524-013-0286-z fatcat:xlbisnt5wjdanpjye4asmbkp4a

A New Diversity Technique for Imbalance Learning Ensembles

Hartono ., Opim Salim Sitompul, Erna Budhiarti Nababan, Tulus ., Dahlan Abdullah, Ansari Saleh Ahmar
2018 International Journal of Engineering & Technology  
Classifier Ensembles is a method often used in overcoming class imbalance problems. Data Diversity is one of the cornerstones of ensembles.  ...  This study shows that the data diversity is related to performance in the imbalance learning ensembles and the proposed methods can obtain better data diversity.  ...  Acknowledgement This work was supported by the Grant of Ministry of Research, Technology, and Higher Education (KEMENRISTEKDIKTI) of the Republic of Indonesia.  ... 
doi:10.14419/ijet.v7i2.11251 fatcat:u7lywd7gajgsfo45oahocqdicq

Multiple Video Instance Detection and Retrieval using Spatio-Temporal Analysis using Semi Supervised SVM Algorithm

R. Kousalya, S. Dharani
2017 International Journal of Computer Applications  
the present finish, the work to formulate this drawback because the spatio-temporal trajectory search downside, wherever a trajectory may be a sequence of bounding boxes that find the thing instance in  ...  The work tends to solve the key bottleneck in applying the approach to object instance search by leverage a randomized approach to change quick marking of any bounding boxes within the video volume.  ...  Geographic knowledge discovery using diverse data types GKD methods should be developed that can handle diverse data types beyond the traditional raster and vector models, including imagery and geo-referenced  ... 
doi:10.5120/ijca2017913495 fatcat:ozzueddgjnbcfhhmp3stikmpjq

Logo Recognition Based on the Dempster-Shafer Fusion of Multiple Classifiers [chapter]

Mohammad Ali Bagheri, Qigang Gao, Sergio Escalera
2013 Lecture Notes in Computer Science  
The performance of different feature extraction and shape description methods in trademark image recognition systems have been studied by several researchers.  ...  Three promising shape description techniques, including Zernike moments, generic Fourier descriptors, and shape signature are used to extract informative features from logo images, and each set of features  ...  Creating an ensemble of classifiers There are three general approaches to creating an ensemble of classifiers in stateof-the-art research, which can be considered as different ways to achieve diversity  ... 
doi:10.1007/978-3-642-38457-8_1 fatcat:b3v5mmqnk5g27jog5seylp6tgm

Multiple Classifier Systems for Embedded String Patterns [chapter]

Barbara Spillmann, Michel Neuhaus, Horst Bunke
2006 Lecture Notes in Computer Science  
We present methods for combining multiple classifiers trained on various vectorial data representations. As base classifiers we use nearest neighbor methods and support vector machine.  ...  Multiple classifier systems are a well proven and tested instrument for enhancing the recognition accuracy in statistical pattern recognition problems.  ...  Conclusions In the present paper we propose a method for creating multiple classifier systems for string patterns.  ... 
doi:10.1007/11829898_16 fatcat:wpnunok5fjc7nm3r3ml2ef4rwe
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