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Citations to this Journal [121 citations: 1–100 of 118 articles]

Articles published in Advances in Artificial Neural Systems have been cited 121 times. The following is a list of the 118 articles that have cited the articles published in Advances in Artificial Neural Systems.

  • Divya Tomar, and Sonal Agarwal, “Twin Support Vector Machine for Multiple Instance Learning Based on Bag Dissimilarities,” Advances in Artificial Intelligence, vol. 2016, pp. 1–18, 2016. View at Publisher · View at Google Scholar
  • Xiaoming Li, Zhihan Lv, Weixi Wang, Baoyun Zhang, Jinxing Hu, Ling Yin, and Shengzhong Feng, “WebVRGIS based traffic analysis and visualization system,” Advances In Engineering Software, vol. 93, pp. 1–8, 2016. View at Publisher · View at Google Scholar
  • Ivana Sušanj, Nevenka Ožanić, and Ivan Marović, “Methodology for Developing Hydrological Models Based on an Artificial Neural Network to Establish an Early Warning System in Small Catchments,” Advances in Meteorology, vol. 2016, pp. 1–14, 2016. View at Publisher · View at Google Scholar
  • N. Sriraam, T. K. Padma Shri, and Uma Maheshwari, “Recognition of wake-sleep stage 1 multichannel eeg patterns using spectral entropy features for drowsiness detection,” Australasian Physical & Engineering Sciences in Medicine, 2016. View at Publisher · View at Google Scholar
  • Youzhong Liu, Kirill Smirnov, Marianna Lucio, Regis D. Gougeon, Herve Alexandre, and Philippe Schmitt-Kopplin, “MetICA: independent component analysis for high-resolution mass-spectrometry based non-targeted metabolomics,” Bmc Bioinformatics, vol. 17, 2016. View at Publisher · View at Google Scholar
  • Ganeshbabu Oorkavalan, Sashikkumar Madurai Chidambaram, Vijayaraj Mariappan, Gokulakrishnan Kandaswamy, and Sakthieswaran Natarajan, “Cluster Analysis to Assess Groundwater Quality in Erode District, Tamil Nadu, India,” Circuits and Systems, vol. 07, no. 06, pp. 877–890, 2016. View at Publisher · View at Google Scholar
  • M. Gopila, and I. Gnanambal, “An Effective Detection of Inrush and Internal Faults in Power Transformers Using Bacterial Foraging Optimization Technique,” Circuits and Systems, vol. 07, no. 08, pp. 1569–1580, 2016. View at Publisher · View at Google Scholar
  • Mahesh R. Gadekar, and M. Mansoor Ahammed, “Coagulation/flocculation process for dye removal using water treatment residuals: modelling through artificial neural networks,” Desalination and Water Treatment, pp. 1–9, 2016. View at Publisher · View at Google Scholar
  • Yi Zhang, Yueming Jie, and Xinyou Meng, “The Modelling and Control of a Singular Biological Economic System in a Polluted Environment,” Discrete Dynamics in Nature and Society, vol. 2016, pp. 1–7, 2016. View at Publisher · View at Google Scholar
  • U. Rajendra Acharya, Shreya Bhat, Oliver Faust, Hojjat Adeli, Eric Chern-Pin Chua, Wei Jie Eugene Lim, and Joel En Wei Koh, “Nonlinear Dynamics Measures for Automated EEG-Based Sleep Stage Detection,” European Neurology, vol. 74, no. 5-6, pp. 268–287, 2016. View at Publisher · View at Google Scholar
  • Nancy X. R. Wang, Jared D. Olson, Jeffrey G. Ojemann, Rajesh P. N. Rao, and Bingni W. Brunton, “Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations,” Frontiers In Human Neuroscience, vol. 10, 2016. View at Publisher · View at Google Scholar
  • Nancy X. R. Wang, Jared D. Olson, Jeffrey G. Ojemann, Rajesh P. N. Rao, and Bingni W. Brunton, “Unsupervised Decoding of Long-Term, Naturalistic Human Neural Recordings with Automated Video and Audio Annotations,” Frontiers in Human Neuroscience, vol. 10, 2016. View at Publisher · View at Google Scholar
  • Mitsuhiro Hayashibe, “Evoked Electromyographically Controlled Electrical Stimulation,” Frontiers in Neuroscience, vol. 10, 2016. View at Publisher · View at Google Scholar
  • Bashar Tarawneh, “Predicting standard penetration test N-value from cone penetration test data using artificial neural networks,” Geoscience Frontiers, 2016. View at Publisher · View at Google Scholar
  • Zhihan Lv, Xiaoming Li, Baoyun Zhang, Weixi Wang, Yuanyuan Zhu, Jinxing Hu, and Shengzhong Feng, “Managing Big City Information Based on WebVRGIS,” IEEE Access, vol. 4, pp. 407–415, 2016. View at Publisher · View at Google Scholar
  • Weixi Gu, Longfei Shangguan, Zheng Yang, and Yunhao Liu, “Sleep Hunter: Towards Fine Grained Sleep Stage Tracking with Smartphones,” IEEE Transactions on Mobile Computing, vol. 15, no. 6, pp. 1514–1527, 2016. View at Publisher · View at Google Scholar
  • Francisco Ortega-Zamorano, Jose M. Jerez, Daniel Urda Munoz, Rafael M. Luque-Baena, and Leonardo Franco, “Efficient Implementation of the Backpropagation Algorithm in FPGAs and Microcontrollers,” IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 9, pp. 1840–1850, 2016. View at Publisher · View at Google Scholar
  • M.M. Al Rahhal, Yakoub Bazi, Haikel AlHichri, Naif Alajlan, Farid Melgani, and R.R. Yager, “Deep Learning Approach for Active Classification of Electrocardiogram Signals,” Information Sciences, 2016. View at Publisher · View at Google Scholar
  • Y.H. Chok, M.B. Jaksa, W.S. Kaggwa, D.V. Griffiths, and G.A. Fenton, “Neural network prediction of the reliability of heterogeneous cohesive slopes,” International Journal for Numerical and Analytical Methods in Geomechanics, 2016. View at Publisher · View at Google Scholar
  • Minyi Cen, Miao Ge, Yonglin Liu, Congxia Wang, and Shaofang Yang, “The effect of geographical indices on left ventricular structure in healthy Han Chinese population,” International Journal of Biometeorology, 2016. View at Publisher · View at Google Scholar
  • Wei Gu, Thomas L. Saaty, and Rozann Whitaker, “Expert System for Ice Hockey Game Prediction: Data Mining with Human Judgment,” International Journal of Information Technology & Decision Making, vol. 15, no. 04, pp. 763–789, 2016. View at Publisher · View at Google Scholar
  • K. Chiteka, and C.C. Enweremadu, “Prediction of global horizontal solar irradiance in Zimbabwe using artificial neural networks,” Journal of Cleaner Production, 2016. View at Publisher · View at Google Scholar
  • Yi Su, Shilei Sun, Yusuf Ozturk, and Mao Tian, “Measurement Of Upper Limb Muscle Fatigue Using Deep Belief Networks,” Journal of Mechanics in Medicine and Biology, pp. 1640032, 2016. View at Publisher · View at Google Scholar
  • Matthew C. Menkiti, and Marcel I. Ejimofor, “Experimental and artificial neural network application on the optimization of paint effluent (PE) coagulation using novel Achatinoidea shell extract (ASE),” Journal of Water Process Engineering, vol. 10, pp. 172–187, 2016. View at Publisher · View at Google Scholar
  • Kuo-Wei Liao, Chun-Tao Chen, Bang-Ho Wu, Wei-Lun Chen, and Chih-Ming Yeh, “Investigation of chloride diffusion in cement mortar via statistical learning theory,” Magazine of Concrete Research, vol. 68, no. 5, pp. 237–249, 2016. View at Publisher · View at Google Scholar
  • Mohammad W. Dewan, Daniel J. Huggett, T. Warren Liao, Muhammad A. Wahab, and Ayman M. Okeil, “Prediction of tensile strength of friction stir weld joints with adaptive neuro-fuzzy inference system (ANFIS) and neural network,” Materials & Design, vol. 92, pp. 288–299, 2016. View at Publisher · View at Google Scholar
  • Yuehao Luo, Wen Song, and Xudong Wang, “Water repellent/wetting characteristics of various bio-inspired morphologies and fluid drag reduction testing research,” Micron, vol. 82, pp. 9–16, 2016. View at Publisher · View at Google Scholar
  • U. Rajendra Acharya, Hamido Fujita, Vidya K. Sudarshan, Shu Lih Oh, Adam Muhammad, Joel E. W. Koh, Jen Hong Tan, Chua K. Chua, Kok Poo Chua, and Ru San Tan, “Application of empirical mode decomposition (EMD) for automated identification of congestive heart failure using heart rate signals,” Neural Computing and Applications, 2016. View at Publisher · View at Google Scholar
  • M. Alfaro-Ponce, I. Salgado, A. Arguelles, and I. Chairez, “Adaptive identifier for uncertain complex-valued discrete-time nonlinear systems based on recurrent neural networks,” Neural Processing Letters, vol. 43, no. 1, pp. 133–153, 2016. View at Publisher · View at Google Scholar
  • Mohammad Reza Faraji, and Xiaojun Qi, “Face Recognition under Varying Illuminations Using Logarithmic Fractal Dimension-based Complete Eight Local Directional Patterns,” Neurocomputing, 2016. View at Publisher · View at Google Scholar
  • Musa Peker, “An efficient sleep scoring system based on EEG signal using complex-valued machine learning algorithms,” Neurocomputing, 2016. View at Publisher · View at Google Scholar
  • Sthitapragyan Mohanty, Prashanta Kumar Patra, and Sudhansu Sekhar Sahoo, “Prediction and application of solar radiation with soft computing over traditional and conventional approach – A comprehensive review,” Renewable and Sustainable Energy Reviews, vol. 56, pp. 778–796, 2016. View at Publisher · View at Google Scholar
  • Ian Sosa-Tinoco, Juan Peralta-Jaramillo, Carlos Otero-Casal, A. López- Agüera, G. Miguez-Macho, and I. Rodríguez-Cabo, “Validation of a global horizontal irradiation assessment from a numerical weather prediction model in the south of Sonora–Mexico,” Renewable Energy, vol. 90, pp. 105–113, 2016. View at Publisher · View at Google Scholar
  • Kahina Dahmani, Gilles Notton, Cyril Voyant, Rabah Dizene, Marie Laure Nivet, Christophe Paoli, and Wani Tamas, “Multilayer Perceptron approach for estimating 5-min and hourly horizontal global irradiation from exogenous meteorological data in locations without solar measurements,” Renewable Energy, vol. 90, pp. 267–282, 2016. View at Publisher · View at Google Scholar
  • Kunjumon I. Vadakkana, “The functional role of all postsynaptic potentials examined from a first-person frame of reference,” Reviews In The Neurosciences, vol. 27, no. 2, pp. 159–184, 2016. View at Publisher · View at Google Scholar
  • Josenildo Brito Oliveira, Renato Silva Lima, and José Arnaldo Barra Montevechi, “Perspectives and relationships in Supply Chain Simulation: A systematic literature review,” Simulation Modelling Practice and Theory, vol. 62, pp. 166–191, 2016. View at Publisher · View at Google Scholar
  • Shuma Adhikari, Nidul Sinha, and Thingam Dorendrajit, “Fuzzy logic based on-line fault detection and classification in transmission line,” SpringerPlus, vol. 5, no. 1, 2016. View at Publisher · View at Google Scholar
  • Kittikhun Thongpull, and Andreas Koenig, “Advance and case studies of the DAICOX framework for automated design of multi-sensor intelligent measurement systems,” Tm-Technisches Messen, vol. 83, no. 4, pp. 234–243, 2016. View at Publisher · View at Google Scholar
  • Junming Zhang, Yan Wu, Jing Bai, and Fuqiang Chen, “Automatic sleep stage classification based on sparse deep belief net and combination of multiple classifiers,” Transactions Of The Institute Of Measurement And Control, vol. 38, no. 4, pp. 435–451, 2016. View at Publisher · View at Google Scholar
  • 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
  • Ahmed Majid Taha, Soong-Der Chen, and Aida Mustapha, “Bat Algorithm Based Hybrid Filter-Wrapper Approach,” Advances in Operations Research, vol. 2015, pp. 1–5, 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
  • G. Vishnuvarthanan, M. Pallikonda Rajasekaran, P. Subbaraj, and Anitha Vishnuvarthanan, “An Unsupervised Learning Method with a Clustering Approach for Tumor Identification and Tissue Segmentation in Magnetic Resonance Brain Images,” Applied Soft Computing, 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
  • Woubishet Zewdu Taffese, Esko Sistonen, and Jari Puttonen, “CaPrM: Carbonation prediction model for reinforced concrete using machine learning methods,” Construction and Building Materials, vol. 100, pp. 70–82, 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
  • Fatima Adly, Omar Alhussein, Paul D. Yoo, Yousof Al-Hammadi, Kamal Taha, Sami Muhaidat, Young-Seon Jeong, Uihyoung Lee, and Mohammed Ismail, “Simplified Subspaced Regression Network for Identification of Defect Patterns in Semiconductor Wafer Maps,” Ieee Transactions On Industrial Informatics, vol. 11, no. 6, pp. 1267–1276, 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
  • Wenkai Xu, Suk-Hwan Lee, and Eung-Joo Lee, “A Robust Method for Partially Occluded Face Recognition,” Ksii Transactions On Internet And Information Systems, vol. 9, no. 7, pp. 2667–2682, 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
  • M. S. Cao, L. X. Pan, Y. F. Gao, D. Novák, Z. C. Ding, D. Lehký, and X. L. Li, “Neural network ensemble-based parameter sensitivity analysis in civil engineering systems,” Neural Computing and Applications, 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
  • Xingchen Wu, Guihe Qin, He Yu, Song Gao, Liu Liu, and Yang Xue, “Using improved chaotic ant swarm to tune PID controller on cooperative adaptive cruise control,” Optik - International Journal for Light and Electron Optics, 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
  • T. V. Dixit, Anamika Yadav, and S. Gupta, “Optimization of PV array inclination in India using ANN estimator: Method comparison study,” Sadhana-Academy Proceedings In Engineering Sciences, vol. 40, no. 5, pp. 1457–1472, 2015. View at Publisher · View at Google Scholar
  • Omar Naifar, Ghada Boukettaya, and Abderrazak Ouali, “Robust software sensor with online estimation of stator resistance applied to WECS using IM,” The International Journal of Advanced Manufacturing Technology, 2015. View at Publisher · View at Google Scholar
  • Vic Norris, Laura Norris, and Wing-Keung Wong, “The Positive Feedback Advantages of Combining Buying and Investing,” Theoretical Economics Letters, vol. 05, no. 05, pp. 659–669, 2015. 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
  • 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
  • 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
  • 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
  • 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
  • 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