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61 results for “Back Propagation Network”
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Research ArticleOpen accessIn the abstractPower Enhancement of Weightlifters during Snatch through Reducing Torque on Joints by Particle Swarm OptimizationFirooz Salaami, Nima Jamshidi, Mostafa Rostami, Siamak NajarianIn this research, an athlete's body on sagittal plane in tension phase of snatch weightlifting has been modeled in two dimensions for calculating the generated torques in joints. The error back propagation multi-layer perceptrons has been used for modeling the torque through changing the angular velocity, angular acceleration and absolute angle of each segment. Finally, the torque in joints has … …American Journal of Applied Sciences, Vol. 5, Issue 12 · 31 Dec 2008 · 7,101 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Analysis of Structures Using Neural NetworksN. Ahmadi, R. Kamyab Moghadas, A. LavaeiIn the recent years, neural networks are considered as the best candidate for fast approximation with arbitrary accuracy in the time consuming problems. Dynamic analysis of structures against earthquake has the time consuming process. We employed two kinds of neural networks: Generalized Regression neural network (GR) and Back-Propagation Wavenet neural network (BPW), for approximating of dynamic time history response of … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,154 accessesView PDFCite
Research ArticleOpen accessIn the abstractCombustion Analysis of a CI Engine Performance Using Waste Cooking Biodiesel Fuel with an Artificial Neural Network AidGholamhassan NAJAFI, Barat GHOBADIAN, Talal F. YUSAF, Hadi RAHIMIA comprehensive combustion analysis has been conducted to evaluate the performance of a commercial DI engine, water cooled two cylinders, in-line, naturally aspirated, RD270 Ruggerini diesel engine using waste vegetable cooking oil as an alternative fuel. In order to compare the brake power and the torques values of the engine, it has been tested under same operating conditions with diesel … …American Journal of Applied Sciences, Vol. 4, Issue 10 · 31 Oct 2007 · 8,192 accessesView PDFCite
Research ArticleOpen accessIn the abstractSegmentation and Recognition of Handwritten Numeric ChainsSalim Ouchtati, Mouldi Bedda, Abderrazak LachouriAutomatic reading of numeric chains has been attempted in several application areas such as bank cheque processing, postal code recognition and form processing. Such applications have been very popular in handwriting recognition research, due to the possibility to reduce considerably the manual effort involved in these tasks. In this study we propose an off line system for the recognition of … …Journal of Computer Science, Vol. 3, Issue 4 · 30 Apr 2007 · 7,636 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn the Pulsewidth Analysis in the Presence of PMD and PDL in Optical Fibers Using Neural Network AlgorithmA. Sivasubramanian, V. C. RavichandranIn long haul networks, the random birefringence induced in the optical fiber leads to a considerable Polarization Mode Dispersion (PMD). Polarization Dependent Loss (PDL) mainly occurs in optical components and depends on the state of polarization of optical signals. The presence of PMD and PDL causes pulsewidth narrowing and the pulsewidth reduction depends on states of polarization at which the … …Journal of Computer Science, Vol. 3, Issue 4 · 30 Apr 2007 · 7,053 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting River Flow in the USA: A Comparison between Auto-Regression and Neural Network Non-Parametric ModelsAbdel K.M. Baareh, Alaa F. Sheta, Khaled A. KhnaifesForecasting a time series became one of the most challenging tasks to variety of data sets. The existence of large number of parameters to be estimated and the effect of uncertainty and outliers in the measurements makes the time series modeling too complicated. Recently, Artificial Neural Network (ANN) became quite successful tool to handle time series modeling problem. This paper … …Journal of Computer Science, Vol. 2, Issue 10 · 31 Oct 2006 · 6,962 accessesView PDFCite
Research ArticleOpen accessIn the abstractDigital Hardware Implementation of a Neural System Used for Nonlinear Adaptive PredictionHassène Faiedh, Chokri Souani, Kholdoun Torki, Kamel BesbesNeural networks have been widely used for many applications in digital communications. They are able to give solutions to complex problems due to their nonlinear processing and their learning and generalization. Neural networks are one of the key technologies for the communication domain and accordingly a special effort may be expected to be paid to real time hardware implementation issues. … …Journal of Computer Science, Vol. 2, Issue 4 · 30 Apr 2006 · 6,763 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Regularization in a Neural Network Model to Estimate Lines of Code Using Function PointsK. K. Aggarwal, Yogesh Singh, Pravin Chandra, Manimala PuriIt is a well known fact that at the beginning of any project, the software industry needs to know, how much will it cost to develop and what would be the time required ? . This paper examines the potential of using a neural network model for estimating the lines of code, once the functional requirements are known. Using the … …Journal of Computer Science, Vol. 1, Issue 4 · 31 Dec 2005 · 30,191 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnergy and Carbon Flux Coupling: Multi-ecosystem Comparisons Using Artificial Neural NetworkAssefa M. Melesse, Rodney S. HanleyA multi-ecosystems carbon flux simulation from energy fluxes is presented. A new statistical learning technique based on Artificial Neural Network (ANN) back propagation algorithm and multi-layer perceptron architecture was used in the CO2 simulation. Four input layers (net radiation, soil heat flux, sensible and latent heat flux) were used for training (calibration) and testing (verification) of model outputs. The 15-days … …American Journal of Applied Sciences, Vol. 2, Issue 2 · 28 Feb 2005 · 7,347 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordKnowledge Representation of Ion-Sensitive Field-Effect Transistor Voltage Response for Potassium Ion Concentration Detection in Mixed Potassium/Ammonium Ion SolutionsWan Fazlida Hanim Abdullah, Mohd Alaudin Mohd Ali, Md Shabiul Islam, Masuri OthmanProblem statement: The Ion-Sensitive Field-Effect Transistor (ISFET) is a metal-oxide field-effect transistor-based sensor that reacts to ionic activity at the electrolye/membrane/gate interface. The ionic sensor faces issue of selectivity from interfering ions that contribute to the sensor electrical response in mixed solutions. Approach: We present the training data collection of ISFET voltage response for the purpose of post-processing stage neural … …American Journal of Applied Sciences, Vol. 7, Issue 1 · 31 Jan 2010 · 7,816 accessesView PDFCite