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Extension neural network and its applicationsWANG, M. H; HUNG, C. P.Neural networks. 2003, Vol 16, Num 5-6, pp 779-784, issn 0893-6080, 6 p.Conference Paper

Comparison of WAVENET and ANN for predicting the porosity obtained from well log dataSHOKOOH SALJOOGHI, B; HEZARKHANI, A.Journal of petroleum science & engineering. 2014, Vol 123, pp 172-182, issn 0920-4105, 11 p.Article

Integrating neural network and numerical simulation for production performance prediction of low permeability reservoirQINGJUN YANG; SHULIN ZHANG; QI FEI et al.Petroleum science and technology. 2005, Vol 23, Num 5-6, pp 579-590, issn 1091-6466, 12 p.Article

Modelling Hebbian cell assemblies comprised of cortical neuronsLANSNER, A; FRANSEN, E.Network (Bristol. Print). 1992, Vol 3, Num 2, pp 105-119, issn 0954-898XArticle

Improved Global Robust Stability for Interval-Delayed Hopfield Neural NetworksSINGH, Vimal.Neural processing letters. 2008, Vol 27, Num 3, pp 257-265, issn 1370-4621, 9 p.Article

An Automatically Converging Scheme Based on the Neural Network and Its Application in AntennasLEE, Kun-Chou; JHANG, Jhen-Yan; LIN, Tsung-Nan et al.IEEE transactions on antennas and propagation. 2009, Vol 57, Num 4, pp 1270-1274, issn 0018-926X, 5 p., 2Article

A novel approach to the integration of GPS and INS using recurrent neural networks with evolutionary optimization techniquesMALLESWARAN, M; VAIDEHI, V; SIVASANKARI, N et al.Aerospace science and technology (Imprimé). 2014, Vol 32, pp 169-179, issn 1270-9638, 11 p.Article

The Prediction of Permeability Using an Artificial Neural Network SystemPAZUKI, G. R; NIKOOKAR, M; DEHNAVI, M et al.Petroleum science and technology. 2012, Vol 30, Num 17-20, pp 2108-2113, issn 1091-6466, 6 p.Article

Intelligent Isochronal Test AnalysisASOODEH, M.Petroleum science and technology. 2013, Vol 31, Num 9-12, pp 932-940, issn 1091-6466, 9 p.Article

A novel tool for designing well placements by combination of modified genetic algorithm and artificial neural networkARIADJI, Tutuka; HARYADI, Febi; IRFAN TAUFIK RAU et al.Journal of petroleum science & engineering. 2014, Vol 122, pp 69-82, issn 0920-4105, 14 p.Article

The Simulation of Microbial Enhanced Oil Recovery by Using a Two-layer Perceptron Neural NetworkMORSHEDI, S; TORKAMAN, M; SEDAGHAT, M. H et al.Petroleum science and technology. 2014, Vol 32, Num 21-24, pp 2700-2707, issn 1091-6466, 8 p.Article

Wind speed estimation using multilayer perceptronVELO, Ramón; LOPEZ, Paz; MASEDA, Francisco et al.Energy conversion and management. 2014, Vol 81, pp 1-9, issn 0196-8904, 9 p.Article

Neuroet : An easy-to-use artificial neural network for ecological and biological modelingNOBLE, Peter A; TRIBOU, Erik H.Ecological modelling. 2007, Vol 203, Num 1-2, pp 87-98, issn 0304-3800, 12 p.Conference Paper

Prediction of daily global solar irradiation data using Bayesian neural network: A comparative studyYACEF, R; BENGHANEM, M; MELLIT, A et al.Renewable energy. 2012, Vol 48, pp 146-154, issn 0960-1481, 9 p.Article

Forecasting of daily total atmospheric ozone in IsfahanYAZDANPANAH, H; KARIMI, M; HEJAZIZADEH, Z et al.Environmental monitoring and assessment. 2009, Vol 157, Num 1-4, pp 235-241, issn 0167-6369, 7 p.Article

A comparative study of two modeling approaches in neural networksXU, Zong-Ben; HONG QIAO; JIGEN PENG et al.Neural networks. 2004, Vol 17, Num 1, pp 73-85, issn 0893-6080, 13 p.Article

Dynamical state transition by neuromodulation due to acetylcholine in neural network model for oscillatory phenomena in thalamusOMORI, Toshiaki; HORIGUCHI, Tsuyoshi.Journal of the Physical Society of Japan. 2004, Vol 73, Num 12, pp 3489-3494, issn 0031-9015, 6 p.Article

EPNN-based prediction of meteorological data for renewable energy systemsMELLI, A; DRIF, M; MALEK, A et al.Revue des énergies renouvelables. 2010, Vol 13, Num 1, pp 25-47, issn 1112-2242, 23 p.Article

Artificial Neural Network Modeling for the Prediction of Oil ProductionELMABROUK, S; SHIRIF, E; MAYORGA, R et al.Petroleum science and technology. 2014, Vol 32, Num 9-12, pp 1123-1130, issn 1091-6466, 8 p.Article

Generation of Asphaltene Deposition Envelope Using Artificial Neural NetworkCHALANGARAN, Vahid; FIROOZINIA, Hamed; KHARRAT, Riyaz et al.Journal of dispersion science and technology. 2014, Vol 35, Num 1-3, pp 313-321, issn 0193-2691, 9 p.Article

GA, MR, FFNN, PNN and GMM based models for automatic text summarizationMOHAMED ABDEL FATTAH; FUJI REN.Computer speech & language (Print). 2009, Vol 23, Num 1, pp 126-144, issn 0885-2308, 19 p.Article

Training neural net classifier to improve generalization capabilityKAYAMA, M; ABE, S.Systems and computers in Japan. 1994, Vol 25, Num 2, pp 101-110, issn 0882-1666Article

Artificial neural networks approach for estimating filtration properties of drilling fluidsJEIRANI, Zahra; MOHEBBI, Ali.Journal of the Japan Petroleum Institute. 2006, Vol 49, Num 2, pp 65-70, issn 1346-8804, 6 p.Article

A new strategy for predicting short-term wind speed using soft computing modelsHAQUE, Ashraf U; MANDAL, Paras; KAYE, Mary E et al.Renewable & sustainable energy review. 2012, Vol 16, Num 7, pp 4563-4573, issn 1364-0321, 11 p.Article

Practical application of hybrid modelling to naturally fractured reservoirsTRAN, N. H; CHEN, Z; RAHMAN, S. S et al.Petroleum science and technology. 2007, Vol 25, Num 9-10, pp 1263-1277, issn 1091-6466, 15 p.Article

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