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Citations to this Journal [71 citations: 68 articles]

Articles published in Advances in Artificial Neural Systems have been cited 71 times. The following is a list of the 68 articles that have cited the articles published in Advances in Artificial Neural Systems.

  • Gang Chen, Kai Huang, Christian Buckl, and Alois Knoll, “Applying Pay-Burst-Only-Once Principle for Periodic Power Management in Hard Real-Time Pipelined Multiprocessor Systems,” Acm Transactions On Design Automation Of Electronic Systems, vol. 20, no. 2, 2015. View at Publisher · View at Google Scholar
  • Wei-Bo Chen, and Wen-Cheng Liu, “Water Quality Modeling in Reservoirs Using Multivariate Linear Regression and Two Neural Network Models,” Advances in Artificial Neural Systems, vol. 2015, pp. 1–12, 2015. View at Publisher · View at Google Scholar
  • Ali Ahmadvand, and Mohammad Reza Daliri, “Improving the runtime of MRF based method for MRI brain segmentation,” Applied Mathematics and Computation, vol. 256, pp. 808–818, 2015. View at Publisher · View at Google Scholar
  • Antonino Fiannaca, Massimo La Rosa, Riccardo Rizzo, and Alfonso Urso, “A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network,” Artificial Intelligence in Medicine, 2015. View at Publisher · View at Google Scholar
  • C. P. Jacovides, F. S. Tymvios, J. Boland, and M. Tsitouri, “Artificial Neural Network models for estimating daily solar global UV, PAR and broadband radiant fluxes in an eastern Mediterranean site,” Atmospheric Research, vol. 152, pp. 138–145, 2015. View at Publisher · View at Google Scholar
  • Ali Ahmadvand, Mohammad Sharififar, and Mohammad Reza Daliri, “Supervised segmentation of MRI brain images using combination of multiple classifiers,” Australasian Physical & Engineering Sciences in Medicine, 2015. View at Publisher · View at Google Scholar
  • Massimo La Rosa, Antonino Fiannaca, Riccardo Rizzo, and Alfonso Urso, “Probabilistic topic modeling for the analysis and classification of genomic sequences,” Bmc Bioinformatics, vol. 16, 2015. View at Publisher · View at Google Scholar
  • Ehsan Momeni, Ramli Nazir, Danial Jahed Armaghani, and Harnedi Maizir, “Application of Artificial Neural Network for Predicting Shaft and Tip Resistances of Concrete Piles,” Earth Sciences Research Journal, vol. 19, no. 1, pp. 85–93, 2015. View at Publisher · View at Google Scholar
  • Vic Norris, “Why do bacteria divide?,” Frontiers In Microbiology, vol. 6, 2015. View at Publisher · View at Google Scholar
  • Juan Luis Fernandez-Martinez, and Ana Cernea, “Exploring the Uncertainty Space of Ensemble Classifiers in Face Recognition,” International Journal Of Pattern Recognition And Artificial Intelligence, vol. 29, no. 3, 2015. View at Publisher · View at Google Scholar
  • Tarek Lajnef, Sahbi Chaibi, Perrine Ruby, Pierre-Emmanuel Aguera, Jean-Baptiste Eichenlaub, Mounir Samet, Abedennaceur Kachouri, and Karim Jerbi, “Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines,” Journal of Neuroscience Methods, 2015. View at Publisher · View at Google Scholar
  • Jun Shi, Xiao Liu, Yan Li, Qi Zhang, Yingjie Li, and Shihui Yin, “Multi-Channel EEG based Sleep Stage Classification with Joint Collaborative Representation and Multiple Kernel Learning,” Journal of Neuroscience Methods, 2015. View at Publisher · View at Google Scholar
  • Man Shan Kan, Andy C.C. Tan, and Joseph Mathew, “A review on prognostic techniques for non-stationary and non-linear rotating systems,” Mechanical Systems and Signal Processing, 2015. View at Publisher · View at Google Scholar
  • Weiping Wang, Lixiang Li, Haipeng Peng, Jürgen Kurths, Jinghua Xiao, and Yixian Yang, “Anti-synchronization Control of Memristive Neural Networks with Multiple Proportional Delays,” Neural Processing Letters, 2015. View at Publisher · View at Google Scholar
  • Juan Antonio Clemente, Wassim Mansour, Rafic Ayoubi, Felipe Serrano, Hortensia Mecha, Haissam Ziade, Wassim El Falou, and Raoul Velazco, “Hardware Implementation of a Fault-Tolerant Hopfield Neural Network on FPGAs,” Neurocomputing, 2015. View at Publisher · View at Google Scholar
  • Vic Norris, “What Properties of Life Are Universal? Substance-Free, Scale-free Life,” Origins of Life and Evolution of Biospheres, 2015. View at Publisher · View at Google Scholar
  • D.S. Dinesh Kumar, and P.V. Rao, “Analysis and Design of Principal Component Analysis and Hidden Markov Model for Face Recognition,” Procedia Materials Science, vol. 10, pp. 616–625, 2015. View at Publisher · View at Google Scholar
  • Isis Didier Lins, Enrique Lopez Droguett, Marcio das Chagas Moura, Enrico Zio, and Carlos Magno Jacinto, “Computing confidence and prediction intervals of industrial equipment degradation by bootstrapped support vector regression,” Reliability Engineering & System Safety, vol. 167, pp. 120–128, 2015. View at Publisher · View at Google Scholar
  • Yashwant Kashyap, Ankit Bansal, and Anil K. Sao, “Solar radiation forecasting with multiple parameters neural networks,” Renewable and Sustainable Energy Reviews, vol. 49, pp. 825–835, 2015. View at Publisher · View at Google Scholar
  • Nasser-Eddine Tatar, “Long Time Behavior for a System of Differential Equations with Non-Lipschitzian Nonlinearities,” Advances in Artificial Neural Systems, vol. 2014, pp. 1–7, 2014. View at Publisher · View at Google Scholar
  • Miguel Angelo de Abreu de Sousa, Edson Lemos Horta, Sergio Takeo Kofuji, and Emilio Del-Moral-Hernandez, “Architecture Analysis of an FPGA-Based Hopfield Neural Network,” Advances in Artificial Neural Systems, vol. 2014, pp. 1–10, 2014. View at Publisher · View at Google Scholar
  • Martti Juhola, Henry Joutsijoki, Heikki Aalto, and Timo P. Hirvonen, “On classification in the case of a medical data set with a complicated distribution,” Applied Computing and Informatics, 2014. View at Publisher · View at Google Scholar
  • T. Vihma, R. Pirazzini, I. Fer, I. A. Renfrew, J. Sedlar, M. Tjernstrom, C. Luepkes, T. Nygard, D. Notz, J. Weiss, D. Marsan, B. Cheng, G. Birnbaum, S. Gerland, D. Chechin, and J. C. Gascard, “Advances in understanding and parameterization of small-scale physical processes in the marine Arctic climate system: a review,” Atmospheric Chemistry and Physics, vol. 14, no. 17, pp. 9403–9450, 2014. View at Publisher · View at Google Scholar
  • Yahia Kourd, Dimitri Lefebvre, and Noureddine Guersi, “Neural Networks and Fault Probability Evaluation for Diagnosis Issues,” Computational Intelligence and Neuroscience, vol. 2014, pp. 1–15, 2014. View at Publisher · View at Google Scholar
  • Mohammad Heidari, Ali Heidari, and Hadi Homaei, “Analysis of Pull-In Instability of Geometrically Nonlinear Microbeam Using Radial Basis Artificial Neural Network Based on Couple Stress Theory,” Computational Intelligence and Neuroscience, vol. 2014, pp. 1–11, 2014. View at Publisher · View at Google Scholar
  • Akhter Mohiuddin Rather, Arun Agarwal, and V.N. Sastry, “Recurrent neural network and a hybrid model for prediction of stock returns,” Expert Systems with Applications, 2014. View at Publisher · View at Google Scholar
  • Mohamed A. Shahin, “Use of evolutionary computing for modelling some complex problems in geotechnical engineering,” Geomechanics and Geoengineering, vol. 10, no. 2, pp. 109–125, 2014. View at Publisher · View at Google Scholar
  • Subramanian Chitra, and Narayanasamy Devarajan, “Circuit theory approach for voltage stability assessment of reconfigured power network,” Iet Circuits Devices & Systems, vol. 8, no. 6, pp. 435–441, 2014. View at Publisher · View at Google Scholar
  • Yan Li, Pin Li, Shu-huan Lin, Yi-qing Zheng, and Xiang-xiong Zheng, “Paeonol inhibits TNF-alpha-induced GM-CSF expression in fibroblast-like synoviocytes,” International Journal Of Clinical Pharmacology And Therapeutics, vol. 52, no. 11, pp. 986–995, 2014. View at Publisher · View at Google Scholar
  • Wenkai Xu, and Eung-Joo Lee, “A hybrid method based on dynamic compensatory fuzzy neural network algorithm for face recognition,” International Journal of Control, Automation and Systems, vol. 12, no. 3, pp. 688–696, 2014. View at Publisher · View at Google Scholar
  • Mohamed A. Shahin, “Load-Settlement Modeling of Axially Loaded Drilled Shafts Using CPT-Based Recurrent Neural Networks,” International Journal of Geomechanics, vol. 14, no. 6, 2014. View at Publisher · View at Google Scholar
  • Hermanus H. Lemmer, Dibyojyoti Bhattacharjee, and Hemanta Saikia, “A Consistency Adjusted Measure for the Success of Prediction Methods in Cricket,” International Journal of Sports Science and Coaching, vol. 9, no. 3, pp. 497–512, 2014. View at Publisher · View at Google Scholar
  • Ali Osman Pektas, and Tarkan Erdik, “Peak discharge prediction due to embankment dam break by using sensitivity analysis based ANN,” Ksce Journal Of Civil Engineering, vol. 18, no. 6, pp. 1868–1876, 2014. View at Publisher · View at Google Scholar
  • Zhang Qunli, “A Class of Vector Lyapunov Functions for Stability Analysis of Nonlinear Impulsive Differential Systems,” Mathematical Problems in Engineering, vol. 2014, pp. 1–9, 2014. View at Publisher · View at Google Scholar
  • Dhirendranath Thatoi, Punyaslok Guru, Prabir Kumar Jena, Sasanka Choudhury, and Harish Chandra Das, “Comparison of CFBP, FFBP, and RBF Networks in the Field of Crack Detection,” Modelling and Simulation in Engineering, vol. 2014, pp. 1–13, 2014. View at Publisher · View at Google Scholar
  • Martin Längkvist, Lars Karlsson, and Amy Loutfi, “A Review of Unsupervised Feature Learning and Deep Learning for Time-Series Modeling,” Pattern Recognition Letters, 2014. View at Publisher · View at Google Scholar
  • Vic Norris, Camille Ripoll, and Michel Thellier, “The Theatre Management Model of Plant Memory,” Plant Signaling & Behavior, pp. 00–00, 2014. View at Publisher · View at Google Scholar
  • S.J.S. Hakim, and H. Abdul Razak, “Modal parameters based structural damage detection using artificial neural networks - a review,” Smart Structures and Systems, vol. 14, no. 2, pp. 159–189, 2014. View at Publisher · View at Google Scholar
  • Mohamed A. Shahin, “Load–settlement modeling of axially loaded steel driven piles using CPT-based recurrent neural networks,” Soils and Foundations, 2014. View at Publisher · View at Google Scholar
  • Suwicha Jirayucharoensak, Setha Pan-Ngum, and Pasin Israsena, “EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation,” The Scientific World Journal, vol. 2014, pp. 1–10, 2014. View at Publisher · View at Google Scholar
  • Paul T. Pearson, “Visualizing Clusters in Artificial Neural Networks Using Morse Theory,” Advances in Artificial Neural Systems, vol. 2013, pp. 1–8, 2013. View at Publisher · View at Google Scholar
  • Balwinder S. Dhaliwal, and Shyam S. Pattnaik, “Artificial Neural Network Analysis of Sierpinski Gasket Fractal Antenna: A Low Cost Alternative to Experimentation,” Advances in Artificial Neural Systems, vol. 2013, pp. 1–7, 2013. View at Publisher · View at Google Scholar
  • Martti Juhola, Heikki Aalto, Henry Joutsijoki, and Timo P. Hirvonen, “The Classification of Valid and Invalid Beats of Three-Dimensional Nystagmus Eye Movement Signals Using Machine Learning Methods,” Advances in Artificial Neural Systems, vol. 2013, pp. 1–11, 2013. View at Publisher · View at Google Scholar
  • Qunli Zhang, “Matrix Measure with Application in Quantized Synchronization Analysis of Complex Networks with Delayed Time via the General Intermittent Control,” Applied Mathematics, vol. 04, no. 10, pp. 1417–1426, 2013. View at Publisher · View at Google Scholar
  • R. Neves, F. Branco, and J. de Brito, “Field assessment of the relationship between natural and accelerated concrete carbonation resistance,” Cement and Concrete Composites, vol. 41, pp. 9–15, 2013. View at Publisher · View at Google Scholar
  • L.S. Nasrat, A.F. Hamed, M.A. Hamid, and S.H. Mansour, “Study the flashover voltage for outdoor polymer insulators under desert climatic conditions,” Egyptian Journal of Petroleum, vol. 22, no. 1, pp. 1–8, 2013. View at Publisher · View at Google Scholar
  • Sarthak Salunke, Maxim Mokin, Peter Kan, and Peter D. Scott, “3D Vascular Decomposition and Classification for Computer-Aided Detection,” Ieee Transactions on Biomedical Engineering, vol. 60, no. 12, pp. 3514–3523, 2013. View at Publisher · View at Google Scholar
  • Réda Samy Zazoun, “Fracture density estimation from core and conventional well logs data using artificial neural networks: The Cambro-Ordovician reservoir of Mesdar oil field, Algeria,” Journal of African Earth Sciences, vol. 83, pp. 55–73, 2013. View at Publisher · View at Google Scholar
  • Huaguang Zhang, Jiuzhen Liang, and Zhilei Chai, “Stock Prediction Based on Phase Space Reconstruction and Echo State Networks,” Journal of Algorithms & Computational Technology, vol. 7, no. 1, pp. 87–100, 2013. View at Publisher · View at Google Scholar
  • Xiongfei Zou, Ying Tang, Shirong Bu, Zhengxiang Luo, and Shouming Zhong, “Neural-Network-Based Approach for Extracting Eigenvectors and Eigenvalues of Real Normal Matrices and Some Extension to Real Matrices,” Journal of Applied Mathematics, vol. 2013, pp. 1–13, 2013. View at Publisher · View at Google Scholar
  • Mohammad Heidari, and Hadi Homaei, “Quadratic Optimal Regulator Design of a Pneumatic Control Valve,” Modelling and Simulation in Engineering, vol. 2013, pp. 1–8, 2013. View at Publisher · View at Google Scholar
  • Liqun Zhou, “Delay-Dependent Exponential Stability of Cellular Neural Networks with Multi-Proportional Delays,” Neural Processing Letters, vol. 38, no. 3, pp. 347–359, 2013. View at Publisher · View at Google Scholar
  • Liqun Zhou, “Dissipativity of a class of cellular neural networks with proportional delays,” Nonlinear Dynamics, vol. 73, no. 3, pp. 1895–1903, 2013. View at Publisher · View at Google Scholar
  • Kevin R. Haas, Haw Yang, and Jhih-Wei Chu, “Fisher information metric for the Langevin equation and least informative models of continuous stochastic dynamics,” The Journal of Chemical Physics, vol. 139, no. 12, pp. 121931, 2013. View at Publisher · View at Google Scholar
  • Vic Norris, Ghislain Gangwe Nana, and Jean-Nicolas Audinot, “New approaches to the problem of generating coherent, reproducible phenotypes,” Theory in Biosciences, 2013. View at Publisher · View at Google Scholar
  • Amir Hossein Alavi, and Amir Hossein Gandomi, “Discussion on “Models to predict the deformation modulus and the coefficient of subgrade reaction for earth filling structures” by Ismail Dinçer [Adv. Eng. Software 42 (2011) 160–171],” Advances in Engineering Software, vol. 52, pp. 44–46, 2012. View at Publisher · View at Google Scholar
  • Vic Norris, Laurence Menu-Bouaouiche, Jean-Michel Becu, Rachel Legendre, Romain Norman, and Jason A. Rosenzweig, “Hyperstructure interactions influence the virulence of the type 3 secretion system in yersiniae and other bacteria,” Applied Microbiology and Biotechnology, vol. 96, no. 1, pp. 23–36, 2012. View at Publisher · View at Google Scholar
  • Amir Hossein Alavi, Ali Mollahasani, Amir Hossein Gandomi, and Jafar Boluori Bazaz, “Formulation of secant and reloading soil deformation moduli using multi expression programming,” Engineering Computations, vol. 29, no. 2, pp. 173–197, 2012. View at Publisher · View at Google Scholar
  • Amir Hossein Alavi, Amir Hossein Gandomi, and Seyyed Mohammad Mousavi, “Discussion on "Prediction of shear strength parameters of soils using artificial neural networks and multivariate regression methods",” Engineering Geology, vol. 137, pp. 107–108, 2012. View at Publisher · View at Google Scholar
  • J. Humberto Pérez-Cruz, A. Y. Alanis, José de Jesús Rubio, and Jaime Pacheco, “System Identification Using Multilayer Differential Neural Networks: A New Result,” Journal of Applied Mathematics, vol. 2012, pp. 1–20, 2012. View at Publisher · View at Google Scholar
  • Kamil Aydin, and Ozgur Kisi, “Damage detection in Timoshenko beam structures by multilayer perceptron and radial basis function networks,” Neural Computing and Applications, 2012. View at Publisher · View at Google Scholar
  • Takashi Watanabe, and Keisuke Fukushima, “A Study on Feedback Error Learning Controller for Functional Electrical Stimulation: Generation of Target Trajectories by Minimum Jerk Model,” Artificial Organs, vol. 35, no. 3, pp. 270–274, 2011. View at Publisher · View at Google Scholar
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  • Adem Kalinli, M. Cemal Acar, and Zeki Gunduz, “New approaches to determine the ultimate bearing capacity of shallow foundations based on artificial neural networks and ant colony optimization,” Engineering Geology, vol. 117, no. 1-2, pp. 29–38, 2011. View at Publisher · View at Google Scholar
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