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Stacking of SVMs for Classifying Intangible Cultural Heritage Images 6th

Stacking of SVMs for Classifying Intangible Cultural Heritag...

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6th international conference on Computer Science, applied mathematics and Applications (ICCSAMA)

作者： Do, thanh-Nghi Pham, the-Phi Pham, Nguyen-Khang Nguyen, Huu-Hoa Tabia, Karim Benferhat, Salem Can Tho Univ Coll Informat Technol Can Tho Vietnam Paris 6 Pierre & Marie Curie Univ Sorbonne Univ UMI UMMISCO IRD UPMC 209UPMC Paris France CRIL CNRS CRIL UMR 8188 Arras France Artois Univ Arras France

ISBN: (纸本)9783030383640;9783030383633

Our investigation aims at classifying images of the intangible cultural heritage (ICH) in the Mekong Delta, Vietnam. We collect an images dataset of 17 ICH categories and manually annotate them. the comparative study of the ICH image classification is done by the support vector machines (SVM) and many popular vision approaches including the handcrafted features such as the scale-invariant feature transform (SIFT) and the bag-of-words (BoW) model, the histogram of oriented gradients (HOG), the GIST and the automated deep learning of invariant features like VGG19, ResNet50, Inception v3, Xception. the numerical test results on 17 ICH dataset show that SVM models learned from Inception v3 and Xception features give good accuracy of 61.54% and 62.89% respectively. We propose to stack SVM models using different visual features to improve the classification result performed by any single one. Triplets (SVM-Xception, SVM-Inception-v3, SVM-VGG19), (SVM-Xception, SVM-Inception-v3, SVM-SIFT-BoW) achieve 65.32% of the classification correctness.

关键词： Images of the intangible cultural heritage in the Mekong Delta Image classification Visual features Support vector machines Stacking

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A Hybrid Deep Learning Based Autonomous Vehicle Navigation and Obstacles Avoidance 1st

A Hybrid Deep Learning Based Autonomous Vehicle Navigation a...

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1st international conference on Artificial Intelligence and Computer Visions, AICV 2020

作者： Ibrahim, Habiba A. Azar, Ahmad Taher Ibrahim, Zahra Fathy Ammar, Hossam Hassan Nile University Shaikh Zayed City Giza12588 Egypt School of Engineering and Applied Sciences Nile University Campus Juhayna Square Sheikh Zayed District 6th of October City Giza12588 Egypt Prince Sultan University Riyadh Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University Banha Egypt

ISBN: (纸本)9783030442880

Technological revolution has reached all life activities starting from day planning reaching communication, entertainment, industry, and transportation. Each of previously mentioned categories get improved in a way making human life easier and safer. In the use of automatic control, several researches focused on automating vehicles’ systems to make driving easier and safer. the availability of autonomous vehicles will avoid accidents caused by taking a late decision or lack of driving experience in such situation. Approaching autonomous driving, an autonomous vehicle must be able to respond to the state of objects in the surrounding, be it stationary or in motion. this paper outlines the techniques which enable the car to become conscious of its immediate environment while it moves independently and to decide its next course of action to avoid obstacles. It investigates two approaches which are Neuro-Fuzzy System tuned by Particle Swarm Optimization (PSO) and Convolutional Neural Network (CNN) tuned by Adaptive Moment estimation (Adam). Such control can allow cars on roads to operate smoothly and, according to trained data, take quick accurate decisions. Results showed high performance of deep learning algorithms specially CNN with Adam;however, it needs more computational time than Neuro-Fuzzy system tuned with PSO. © 2020, Springer Nature Switzerland AG.

关键词： Fuzzy neural networks

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Discovering Systematic Relations between Alarms for Alarm Flows Reduction 6

Discovering Systematic Relations between Alarms for Alarm Fl...

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6th international conference on Control, Decision and Information Technologies (CoDIT)

作者： Laumonier, Y. Faure, J. -M. Lesage, J. -J. Sabot, H. Univ Paris Saclay Univ Paris Sud ENS Cachan Gen Elect Digital Foundry Europe F-94235 Cachan France Univ Paris Saclay Univ Paris Sud ENS Cachan LURPA F-94235 Cachan France Univ Paris Saclay Univ Paris Sud ENS Cachan LURPASupmeca F-94235 Cachan France Gen Elect Digital Foundry Europe F-75002 Paris France

ISBN: (纸本)9781728105215

Alarm systems play an important role for the safe and efficient operation of modern industrial plants. However, in most of industrial alarm systems, alarm flows cannot always be correctly managed by the operators as they often turn into alarm floods, sequences of numerous alarms occurring in a short period of time. To reduce the alarm flows, this paper focuses on detection of redundant alarms that could be removed. this objective is met by, first, looking for two systematic causality relations between alarms, called domination and mutual dependency, in the alarm log. Once these relations discovered, alarms removal requires an expert analysis. To ease this analysis, the discovered relations are depicted in the form of Petri nets. the proposed method has been applied on a dataset coming from power industry and provided by General Electric. the results of this case study show the benefits of the approach.

关键词： Industrial alarm systems Alarm rationalization discrete Event Systems Petri nets

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A MAB-Based discrete Power Control Approach in Anti-jamming Relay Communication via three-layer Stackelberg Game

A MAB-Based Discrete Power Control Approach in Anti-jamming ...

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international conference on Computer and Communications (ICCC)

作者： Zhibin Feng Yijie Luo Xueqiang Chen Wen Li College of Communications Engineering Army Engineering University of PLA Nanjing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

In this paper, we investigate the discrete power control problem in anti-jamming relay communication networks. Based on the hierarchical competitive relationships between transmitters (user and relay) and jammer, a three-layer Stackelberg game is formulated, in which user acts as leader, relay acts as vice-leader and jammer acts as follower. From the perspective of hierarchical-game theoretic, we formulate the power optimization problem as a multi-armed bandit (MAB) problem, where user, relay and jammer act as players and each optional power strategy is considered as an arm to select. Based on MAB theory, we give the regret function to express the loss of payoff of the whole communication process. To minimize the regrets of user and relay, we propose a UCB1-based discrete power control online learning algorithm. Simulation results give the power selection rate and logarithmic incremental regrets in the proposed anti-jamming scenario. the user's and relay's utilities are also compared under different algorithms.

关键词： Transmitters Simulation Power control Games Communication networks Relays Jamming

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Ctapipe - Prototype Open Event Reconstruction Pipeline for the Cherenkov Telescope Array 38

Ctapipe - Prototype Open Event Reconstruction Pipeline for t...

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38th international Cosmic Ray conference, ICRC 2023

作者： Linhoff, Maximilian Beiske, Lukas Biederbeck, Noah Fröse, Stefan Kosack, Karl Nickel, Lukas Abe, K. Abe, S. Acharyya, A. Adam, R. Aguasca-Cabot, A. Agudo, I. Alfaro, J. Alvarez-Crespo, N. Alves Batista, R. Amans, J.-P. Amato, E. Ambrosino, F. Angüner, E.O. Antonelli, L.A. Aramo, C. Arcaro, C. Arrabito, L. Asano, K. Aschersleben, J. Ashkar, H. Augusto Stuani, L. Baack, D. Backes, M. Balazs, C. Balbo, M. Baquero Larriva, A. Barbosa Martins, V. de Almeida, U. Barres Barrio, J.A. Bastieri, D. Batista, P.I. Batkovic, I. Batzofin, R. Baxter, J. Beck, G. Becker Tjus, J. Beiske, L. Belardinelli, D. Benbow, W. Bernardini, E. Bernete Medrano, J. Bernlöhr, K. Berti, A. Beshley, V. Bhattacharjee, P. Bhattacharyya, S. Bi, B. Biederbeck, N. Biland, A. Bissaldi, E. Blanch, O. Blazek, J. Boisson, C. Bolmont, J. Bonnoli, G. Bordas, P. Bosnjak, Z. Bradascio, F. Braiding, C. Bronzini, E. Brose, R. Brown, A.M. Brun, F. Brunelli, G. Bulgarelli, A. Burelli, I. Burmistrov, L. Burton, M. Bylund, T. Calisse, P.G. Campoy-Ordaz, A. Cantlay, B.K. Capalbi, M. Caproni, A. Capuzzo-Dolcetta, R. Carlile, C. Caroff, S. Carosi, A. Carosi, R. Carrasco, M.-S. Cascone, E. Cassol, F. Castrejon, N. Catalani, F. Cerasole, D. Cerruti, M. Chaty, S. Chen, A.W. Chernyakova, M. Chiavassa, A. Chudoba, J. Coimbra Araujo, C.H. Conforti, V. Conte, F. Contreras, J.L. Cossou, C. Costa, A. Costantini, H. Cristofari, P. Cuevas, O. Curtis-Ginsberg, Z. D'Amico, G. D'Ammando, F. Dadina, M. Dalchenko, M. David, L. Davids, I.D. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Caprio, V. De Cesare, G. de Gouveia Dal Pino, E.M. De Lotto, B. De Lucia, M. de Menezes, R. de Naurois, M. de Ona Wilhelmi, E. De Simone, N. de Souza, V. del Peral, L. del Valle, M.V. Delagnes, E. Delgado Giler, A.G. Delgado, C. Dell'aiera, M. Della Ceca, R. Della Valle, M. della Volpe, D. Depaoli, D. Dettlaff, A. Di Girolamo, T. Di Piano, A. Di Pierro, F. Di Tria, R. Di Venere, L. Díaz-Bahamondes, C. Dib, C. Diebold, S. Dima, R. Dinesh, A. Djannati-Ataï, A. Djuvsland, J. Department of Physics Tokai University 4-1-1 Kita-Kaname Kanagawa Hiratsuka259-1292 Japan Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Kashiwa Chiba277-8582 Japan University of Alabama Tuscaloosa Department of Physics and Astronomy Gallalee Hall Box 870324 TuscaloosaAL35487-0324 United States Université Côte d'Azur Observatoire de la Côte d'Azur CNRS Laboratoire Lagrange France Laboratoire Leprince-Ringuet CNRS IN2P3 École polytechnique Institut Polytechnique de Paris Palaiseau91120 France Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 Barcelona08028 Spain Instituto de Astrofísica de Andalucía CSIC Glorieta de la Astronomía s/n Granada18008 Spain Pontificia Universidad Católica de Chile Av. Libertador Bernardo O'Higgins 340 Santiago Chile IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain Instituto de Física Teórica UAM CSIC Departamento de Física Teórica Universidad Autónoma de Madrid c/ Nicolás Cabrera 13-15 Campus de Cantoblanco UAM Madrid28049 Spain LUTH GEPI LERMA Observatoire de Paris Université PSL Université Paris Cité CNRS 5 place Jules Janssen Meudon92190 France INAF Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 Firenze50125 Italy INAF Osservatorio Astronomico di Roma Via di Frascati 33 Monteporzio Catone 00040 Italy TÜBITAK Research Institute for Fundamental Sciences Gebze Kocaeli41470 Turkey INFN Sezione di Napoli Via Cintia ed. G Napoli80126 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Laboratoire Univers et Particules de Montpellier Université de Montpellier CNRS IN2P3 CC 72 Place Eugène Bataillon 5 MontpellierF-34095 Cedex France Kapteyn Astronomical Institute University of Groningen Landleven 12 Groningen9747 AD Netherlands Instituto de Física de São Carlos Universidade de

the Cherenkov Telescope Array Observatory (CTAO) is the next-generation ground-based gamma-ray observatory currently under construction. It will improve over the current generation of imaging atmospheric Cherenkov telescopes (IACTs) by a factor of five to ten in sensitivity and it will be able to observe the whole sky from a combination of two sites: a northern site in La Palma, Spain, and a southern one in Paranal, Chile. CTAO will also be the first open ground-based gamma-ray observatory. Accordingly, the CTAO data processing pipeline is developed as open-source software and ctapipe will be a core package therein. the event reconstruction pipeline accepts raw data of the telescopes and processes it to produce suitable input for the higher-level science tools. Its primary tasks include reconstructing the physical properties of each recorded air shower and providing the corresponding instrument response functions. ctapipe is a python framework providing algorithms and command-line tools to facilitate raw data calibration, image extraction, image parametrization and event reconstruction. Its current main focus is the analysis of simulated data but it has also been successfully applied for the analysis of data obtained with the CTA prototype telescopes, and first science results have now been obtained by the LST-1 collaboration using ctapipe. A plugin system also allows the processing of nonCTA data. Recent updates, including event reconstruction using machine learning and a new plugin system as well as the roadmap towards a 1.0 release will be presented. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Open source software

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theoritecal Evaluation of Ibuprofen and Paracetamol by Fukui and Parr Fonctions Descriptors: DFT Study

Theoritecal Evaluation of Ibuprofen and Paracetamol by Fukui...

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international conference on Optimization and Applications (ICOA)

作者： Hayat El ouafy Latifa Amini Said Zouitina Anas Chraka Amin Moubarik Kalifa El Harfi Mohamed Mbarki Mohammed El idrissi Laboratory of Chemical Processes and Applied Materials Beni Mellal Morocco Material and Interfacial Systeme Laboratory Tetouan Morocco

ISBN: (数字)9781728166544

ISBN: (纸本)9781728166551

In the present work, we used the DFT (functional density theory) quantum method B3LYP / 6-311G (d, p) to determine the following elements: geometric optimization of interatomic distances in ibuprofen molecules and paracetamol, energies corresponding to reagents and products, electron density at certain atoms of the molecules of ibuprofen and paracetamol, electrophilic and nucleophilic nature of the molecules, Fukui indices, values of local condensed softness, local indices of electrophilicity and nucleophilicity, Mulliken charges, electronics atom populations and reactivity indices calculated using natural population analysis (NPA), and Parr's functions.

关键词： discrete Fourier transforms Chemicals Drugs Orbits Sociology Statistics

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Optimization of Watermarking in Image by Using Particle Swarm Optimization Algorithm

Optimization of Watermarking in Image by Using Particle Swar...

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international conference on Signal Processing and Communication (ICSC)

作者： Neha Yadav Dharmveer Rajpoot Shri Krishna Dhakad Jaypee Institute of Information Technology Noida Samrat Ashoka Technological Institute Vidisha

ISBN: (数字)9781728154930

ISBN: (纸本)9781728154947

the current digital era is trending with a secure and advances optimized watermarking schemes for digital images. For optimization of the result that has been obtained by applying the DCT-DWT on the original image is being accomplished by Particle Swarm Optimization (PSO). In this paper, the watermark is inserted in the DWT-DCT coefficients, where the value of the coefficients is larger than some specific value. the embedding of the watermark is in the region with low-frequency coefficients. this paper mainly focuses on DCT-DWT but SVD is also tried on the image watermarking. the PSO is first compared with proposed modified inertia weight-based PSO on standard test function and its effectiveness is proposed. Later, to check the undetectability and to gain the optimized result modified PSO is applied in the image watermarking process. It is also checked that it is robust or not by applying some attacks on the image. Simulation results show that there is a marginal difference between the original and watermarked image. the Optimization technique is successfully implemented to achieve an optimal watermarking solution.

关键词： Watermarking discrete wavelet transforms Mathematical model discrete cosine transforms Optimization Robustness

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Astronomy potential of KM3NeT/ARCA230 38

Astronomy potential of KM3NeT/ARCA230

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38th international Cosmic Ray conference, ICRC 2023

作者： van Eeden, thijs Juan Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Androutsou, E. Anguita, M. Aphecetche, L. Ardid, M. Ardid, S. Atmani, H. Aublin, J. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Basegmez du Pree, S. Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chadolias, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.B. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De Benedittis, A. De Martino, B. Decoene, V. Del Burgo, R. Di Cerbo, U.M. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diaz, C. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, E. Drouhin, D. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gabriel, J. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goupilliere, D. Gozzini, S.R. Gracia, R. Graf, K. Guidi, C. Guillon, B. Gutiérrez, M. van Haren, H. Heijboer, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Khatun, A. Kistauri, G. Kopper, C. Kouchner, A. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Larosa, G. Lastoria, C. Lazo, A. Le Stum, S. Lehaut, G. Leonora, E. Nikhef Science Park 105 Amsterdam Netherlands INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France c/Catedrático José Beltrán 2 Paterna Valencia46980 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece University of Granada Dept. of Computer Architecture and Technology/CITIC Granada18071 Spain Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie BP 20722 Nantes44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slovakia Nikhef National Institute for Subatomic Physics PO Box 41882 Amsterdam1009 DB Netherlands INFN Sezione di Bologna v.le C. Berti-Pichat 6/2 Bologna40127 Italy Università di Bologna Diparti

the KM3NeT/ARCA neutrino detector is currently under construction at the bottom of the Mediterranean Sea. the main science objective is the detection of high-energy cosmic neutrinos and the discovery of their sources. this is achieved by instrumenting a cubic kilometre of seawater with photo-multiplier tubes that detect Cherenkov radiation from neutrino interaction products. In recent years, there have been advancements in the reconstruction algorithms for muon neutrinos, along with the development of techniques for identifying and accurately reconstructing electron and tau neutrinos. this contribution will present the updated prospects for cosmic sources using the track and cascade detection signatures for the full detector. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Neutrons

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A Multilayered Convolutional Sparse Coding Framework for Modeling of Pooling Operation of Convolution Neural Networks 6

A Multilayered Convolutional Sparse Coding Framework for Mod...

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6th IEEE international conference on Smart Instrumentation, Measurement and Application, ICSIMA 2019

作者： Wahid, Abdul Umar Khan, Adnan Mukhtarullah Khan, Sheroz Shah, Jawad International Islamic University Dept. of Electrical Eng. Faculty of Eng. Pakistan Dept. of Electrical Eng. National University of Computer and Emerging Sciences Islamabad Pakistan Dept. of ECE Faculty of Eng. International Islamic University Malaysia British Malaysian Institute Universiti Kuala Lumpur Kuala Lumpur50250 Malaysia

ISBN: (纸本)9781728139524

Convolutional Sparse Coding (CSC) framework has been proposed recently to explain relation between Convolutional Neural Networks (CNNs) and sparse coding theory. the multilayered version of CSC(ML-CSC) is shown to be connected to forward pass of CNNs and dictionary learning and sparse coding algorithms of this model are analyzed for solving classification and inverse problems in image processing. However open problems like effect of pooling operations, batch normalization and dictionary learning in context of ML-CSC framework remain challenging issues especially in implementation scenarios. In this work we implement the framework for multi layered version of CSC with incorporation of pooling operations applied on real images and analyze the performance of resulting model. We demonstrate that with optimal parameters selected for sparsity of feature maps, the pooling operation (here max pooling) when used layered wise in ML-CSC framework improves the effective dictionaries and resulting feature maps, which in turn improves the reconstruction accuracy of images after multilayered implementation. © 2019 IEEE.

关键词： Inverse problems

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Applying Machine Learning Classification to Determining Outliers in Effort for Embedded Software Development Projects 6

Applying Machine Learning Classification to Determining Outl...

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6th ACIS international conference on Computational Science/Intelligence and applied Informatics (CSII)

作者： Iwata, Kazunori Nakashima, Toyoshiro Anan, Yoshiyuki Ishii, Naohiro Aichi Univ Dept Business Adm Nakamura Ku 4-60-6 Hiraike Cho Nagoya Aichi 4538777 Japan Aichi Univ Inst Managerial Res Nakamura Ku 4-60-6 Hiraike Cho Nagoya Aichi 4538777 Japan Omron Software Co Ltd Informat & Syst Technol Div Proc Engn Dept Nakagyo Ku Karasuma Chuo Bldg 8F659 Tearaimizucho Kyoto 6048152 Japan Aichi Inst Technol Dept Informat Sci 1247 YachigusaYakusa Cho Toyota Aichi 4700392 Japan

ISBN: (纸本)9781728125534

this paper discusses the effect of under-sampling to determine outliers in terms of the amount of effort, which is the number of people hours needed to complete a task, in embedded software development projects. Estimating the amount of effort for new software projects is especially important. As outliers are harmful to the estimation, they are excluded from many estimation models. However, such outliers can be identified in practice once the projects are completed, and so they should not be excluded during the creation of models and when estimating the amount of effort. We have also attempted to detect outliers in the amount of effort by using an ANN and an SVM. However, the accuracy of the classifications was insufficient due to a small number of outliers. this problem is called data imbalance, and occurs in most of machine learning methods. In order to avoid this problem, we explores rebalancing methods with k-means cluster-based under-sampling. the purpose of the methods are to improve the proportion of outliers that are correctly identified, while keeping the other classification criteria high. Evaluation experiments are carried out to compare the prediction accuracy of the methods with k-means under-sampling, with random under-sampling and without under-sampling using 10-fold cross-validation. the results show that the methods with under-sampling have higher sensitivity and lower precision than these of the methods without under-sampling. the results show that the proposed methods can improve the accuracy to determine outliers;however they pick up excess samples as outliers.

关键词： support vector machine artificial neural network embedded software imbalanced data sets k-means clustering algorithms under-sampling

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