Literatura académica sobre el tema "Feed-forward ANNs"
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Artículos de revistas sobre el tema "Feed-forward ANNs"
Golpour, Iman, Ana Cristina Ferrão, Fernando Gonçalves, Paula M. R. Correia, Ana M. Blanco-Marigorta y Raquel P. F. Guiné. "Extraction of Phenolic Compounds with Antioxidant Activity from Strawberries: Modelling with Artificial Neural Networks (ANNs)". Foods 10, n.º 9 (20 de septiembre de 2021): 2228. http://dx.doi.org/10.3390/foods10092228.
Texto completoO'Reilly, G., C. C. Bezuidenhout y J. J. Bezuidenhout. "Artificial neural networks: applications in the drinking water sector". Water Supply 18, n.º 6 (31 de enero de 2018): 1869–87. http://dx.doi.org/10.2166/ws.2018.016.
Texto completoDaud, Suleman, Khan Shahzada, M. Tufail y M. Fahad. "Stream Flow Modeling of River Swat Using Regression and Artificial Neural Networks (ANNs) Techniques". Advanced Materials Research 255-260 (mayo de 2011): 679–83. http://dx.doi.org/10.4028/www.scientific.net/amr.255-260.679.
Texto completoNovickis, Rihards, Daniels Jānis Justs, Kaspars Ozols y Modris Greitāns. "An Approach of Feed-Forward Neural Network Throughput-Optimized Implementation in FPGA". Electronics 9, n.º 12 (18 de diciembre de 2020): 2193. http://dx.doi.org/10.3390/electronics9122193.
Texto completoAl Khatib, Mohamed y Samer Al Martini. "A Study on the Application of Artificial Neural Networks on Green Self Consolidating Concrete (SCC) under Hot Weather". Key Engineering Materials 677 (enero de 2016): 254–59. http://dx.doi.org/10.4028/www.scientific.net/kem.677.254.
Texto completoSabir, Zulqurnain, Thongchai Botmart, Muhammad Asif Zahoor Raja, Wajaree Weera y Fevzi Erdoğan. "A stochastic numerical approach for a class of singular singularly perturbed system". PLOS ONE 17, n.º 11 (28 de noviembre de 2022): e0277291. http://dx.doi.org/10.1371/journal.pone.0277291.
Texto completoMahmoudi, Amir Hossein, Mitra Ghanbari-Matloob y Soroush Heydarian. "A Neural Networks Approach to Measure Residual Stresses Using Spherical Indentation". Materials Science Forum 768-769 (septiembre de 2013): 114–19. http://dx.doi.org/10.4028/www.scientific.net/msf.768-769.114.
Texto completoKaveh, M. y R. A. Chayjan. "Mathematical and neural network modelling of terebinth fruit under fluidized bed drying". Research in Agricultural Engineering 61, No. 2 (2 de junio de 2016): 55–65. http://dx.doi.org/10.17221/56/2013-rae.
Texto completoAbujayyab, S. K. M., M. A. S. Ahamad, A. S. Yahya y A. M. H. Y. Saad. "A NEW FRAMEWORK FOR GEOSPATIAL SITE SELECTION USING ARTIFICIAL NEURAL NETWORKS AS DECISION RULES: A CASE STUDY ON LANDFILL SITES". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-2/W2 (19 de octubre de 2015): 131–38. http://dx.doi.org/10.5194/isprsannals-ii-2-w2-131-2015.
Texto completoGallo, Mariano y Giuseppina De Luca. "Spatial Extension of Road Traffic Sensor Data with Artificial Neural Networks". Sensors 18, n.º 8 (12 de agosto de 2018): 2640. http://dx.doi.org/10.3390/s18082640.
Texto completoTesis sobre el tema "Feed-forward ANNs"
Ghosh, Ranadhir y n/a. "A Novel Hybrid Learning Algorithm For Artificial Neural Networks". Griffith University. School of Information Technology, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030808.162355.
Texto completoGhosh, Ranadhir. "A Novel Hybrid Learning Algorithm For Artificial Neural Networks". Thesis, Griffith University, 2003. http://hdl.handle.net/10072/365961.
Texto completoThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Information Technology
Full Text
Svärd, Simon. "ANN som en metod för att göra urval i spel". Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-13673.
Texto completoNigrini, L. B. y G. D. Jordaan. "Short term load forecasting using neural networks". Journal for New Generation Sciences, Vol 11, Issue 3: Central University of Technology, Free State, Bloemfontein, 2013. http://hdl.handle.net/11462/646.
Texto completoSeveral forecasting models are available for research in predicting the shape of electric load curves. The development of Artificial Intelligence (AI), especially Artificial Neural Networks (ANN), can be applied to model short term load forecasting. Because of their input-output mapping ability, ANN's are well-suited for load forecasting applications. ANN's have been used extensively as time series predictors; these can include feed-forward networks that make use of a sliding window over the input data sequence. Using a combination of a time series and a neural network prediction method, the past events of the load data can be explored and used to train a neural network to predict the next load point. In this study, an investigation into the use of ANN's for short term load forecasting for Bloemfontein, Free State has been conducted with the MATLAB Neural Network Toolbox where ANN capabilities in load forecasting, with the use of only load history as input values, are demonstrated.
Přecechtěl, Roman. "Optimalizace řízení aktivního síťového prvku". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218166.
Texto completoGosal, Gurpreet Singh. "The use of Inverse Neural Networks in the Fast Design of Printed Lens Antennas". Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32249.
Texto completoCapítulos de libros sobre el tema "Feed-forward ANNs"
Dorado, Julian, Juan R. Rabuñal, Antonino Santos, Alejandro Pazos y Daniel Rivero. "Automatic Recurrent and Feed-Forward ANN Rule and Expression Extraction with Genetic Programming". En Parallel Problem Solving from Nature — PPSN VII, 485–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45712-7_47.
Texto completoSingh, Poornima, Vinod Kumar Singh, Archana Lala y Akash Kumar Bhoi. "Design and Analysis of Microstrip Antenna Using Multilayer Feed-Forward Back-Propagation Neural Network (MLPFFBP-ANN)". En Advances in Communication, Devices and Networking, 393–98. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7901-6_43.
Texto completoYucel, Melda, Sinan Melih Nigdeli y Gebrail Bekdaş. "Artificial Neural Networks (ANNs) and Solution of Civil Engineering Problems". En Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering, 13–38. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0301-0.ch002.
Texto completoKakkar, Deepti y Ashish Raman. "Human-Machine Interface-Based Robotic Wheel Chair Control". En Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering, 1–22. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-7433-1.ch001.
Texto completoSarma, Kandarpa Kumar. "Learning Aided Digital Image Compression Technique for Medical Application". En Handbook of Research on Emerging Perspectives in Intelligent Pattern Recognition, Analysis, and Image Processing, 400–422. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8654-0.ch019.
Texto completoKumar, K. Vinoth y Prawin Angel Michael. "Detection of Stator and Rotor Faults in Asynchronous Motor Using Artificial Intelligence Method". En Advances in Computer and Electrical Engineering, 278–85. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3531-7.ch013.
Texto completoKumar, K. Vinoth, Ramya K. C. y Muhammad Irfan. "Advanced Fault Diagnosis Monitoring Scheme in Asynchronous Motor Using Soft Computing Method". En Advances in Computer and Electrical Engineering, 89–97. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-6989-3.ch004.
Texto completoEmara, Tamer. "Adaptive Power-Saving Mechanism for VoIP Over WiMAX Based on Artificial Neural Network". En Research Anthology on Artificial Neural Network Applications, 471–89. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-2408-7.ch022.
Texto completoGurjar, Arunaben Prahladbhai y Shitalben Bhagubhai Patel. "Fundamental Categories of Artificial Neural Networks". En Research Anthology on Artificial Neural Network Applications, 1–30. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-2408-7.ch001.
Texto completoGurjar, Arunaben Prahladbhai y Shitalben Bhagubhai Patel. "Fundamental Categories of Artificial Neural Networks". En Applications of Artificial Neural Networks for Nonlinear Data, 30–64. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4042-8.ch003.
Texto completoActas de conferencias sobre el tema "Feed-forward ANNs"
Rivero, Daniel, Julian Dorado, Juan Rabunal y Alejandro Pazos. "Evolving simple feed-forward and recurrent ANNs for signal classification: A comparison". En 2009 International Joint Conference on Neural Networks (IJCNN 2009 - Atlanta). IEEE, 2009. http://dx.doi.org/10.1109/ijcnn.2009.5178621.
Texto completoZinati, Reza Farshbaf y Mohammad Reza Razfar. "Constrained Optimization of Surface Roughness in Longitudinal Turning via Novel Modified Harmony Search". En ASME 2011 International Manufacturing Science and Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/msec2011-50005.
Texto completoOlausson, Pernilla, Daniel Ha¨ggsta˚hl, Jaime Arriagada, Erik Dahlquist y Mohsen Assadi. "Hybrid Model of an Evaporative Gas Turbine Power Plant Utilizing Physical Models and Artificial Neural Networks". En ASME Turbo Expo 2003, collocated with the 2003 International Joint Power Generation Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/gt2003-38116.
Texto completoRavindranath, G., G. P. Prabhukumar y B. Channamalla Devaru. "Application of an Artificial Neural Network in Gas-Solid (Air-Solid) Fluidized Bed: Heat Transfer Predictions". En ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-42881.
Texto completoGovindaswamy, Ravindranath y Savitha Srinivasan. "Application of Artificial Neural Network for Single Horizontal Bare Tube and Bare Tube Bundles in Gas-Solid (Air-Solid) Fluidized Bed of Small and Large Particles: Heat Transfer Predictions". En ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-66265.
Texto completoChong, Zyh Siong, Steven Wilcox y John Ward. "The Use of Artificial Intelligence in the Modelling and Heat Treatment Parameters Identification for Alloy-Steel Re-Heating Process". En ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-84802.
Texto completoShi, Yunye, Diego Yepes Maya y Albert Ratner. "Predicting Steam-Gasification Output Using Artificial Neural Networks". En ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-71635.
Texto completoViano, Andrea, Gabriele Ottino, Luca Ratto y Giuseppe Spataro. "Coupled CFD-ANN Procedure for Extending Heat Transfer Correlations Out of Their Range of Validity". En ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-69707.
Texto completoOvcharenko, O., V. Kazei, D. Peter, X. Zhang y T. Alkhalifah. "Low-Frequency Data Extrapolation Using a Feed-Forward ANN". En 80th EAGE Conference and Exhibition 2018. Netherlands: EAGE Publications BV, 2018. http://dx.doi.org/10.3997/2214-4609.201801231.
Texto completoKumar, Narander y Pooja Patel. "Resource Management using Feed Forward ANN-PSO in Cloud Computing Environment". En the Second International Conference. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/2905055.2905115.
Texto completoInformes sobre el tema "Feed-forward ANNs"
Arhin, Stephen, Babin Manandhar, Hamdiat Baba Adam y Adam Gatiba. Predicting Bus Travel Times in Washington, DC Using Artificial Neural Networks (ANNs). Mineta Transportation Institute, abril de 2021. http://dx.doi.org/10.31979/mti.2021.1943.
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