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55 articles for “Artificial-Neural-Networks (ANN)”
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Research ArticleOpen accessIn the abstractComparative Analysis of the Artificial Neural Networks Options Pricing Model Under Constant and Time-Variant VolatilitiesHanningtone Meshack Simiyu, Anthony Gichuhi Waititu, Jane Aduda AkinyiOption pricing using artificial neural networks (ANN) model while relaxing the assumption of constant volatility still remains a challenge. The conventional practice for pure ANN models has been to either model volatility using the very ANN model and have the model output fed as an input to the ANN option pricing model, or to make allowances for a large number … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 20 Jul 2019 · 7,010 accessesView PDFCite
Research ArticleOpen accessIn the abstractElectrical Load Forecasting Using Artificial Neural Network: The Case Study of the Grid Inter-Connected Network of Benin Electricity Community (CEB)Adekunlé Akim Salami, Ayité Sénah Akoda Ajavon, Koffi A. Dotche, Koffi-Sa BedjaThe low rate of electrification seems challenging in many West African countries and many strategies are underway to improve upon. In this regard, the target of achieving the universal access and services calls for a stable and reliable electrical network. Forecasting of electrical load on a connected grid network is very delicate and requires tremendous task from the utilities (billing … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 2 · 11 Apr 2018 · 9,143 accessesView PDFCite
InvestigationOpen accessIn the abstractBackpropagation Vs. Radial Basis Function Neural Model: Rainfall Intensity Classification For Flood Prediction Using Meteorology DataSoo See Chai, Wei Keat Wong, Kok Luong GohRainfall is one of the important weather variables that vary in space and time. High mean daily rainfall (>30 mm) has a high possibility of resulting in flood. Accurate prediction of this variable would save human lives and properties. Soft computing methods have been widely applied in this field. Among the various soft computing methods, Artificial Neural Network (ANN) is … …Journal of Computer Science, Vol. 12, Issue 4 · 15 Apr 2016 · 8,705 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm for Variable and Samples Selection in Multivariate Calibration ProblemsKelton de Souza Santiago, Anderson Silva Soares, Telma Woerle de Lima et al.One of the main problems of quantitative analytical chemistry is to estimate the concentration of one or more species from the values of certain physicochemical properties of the system of interest. For this it is necessary to construct a calibration model, i.e., to determine the relationship between measured properties and concentrations. The multivariate calibration is one of the most successful … …Journal of Computer Science, Vol. 11, Issue 4 · 8 Jun 2015 · 7,381 accessesView PDFCite
Research ArticleOpen accessIn the abstractA COMPARATIVE ANALYSIS OF OPTIMIZATION TECHNIQUES FOR ARTIFICIAL NEURAL NETWORK IN BIO MEDICAL APPLICATIONSV. Saishanmuga Raja, S. P. RajagopalanIn this study we compare the performance of three evolutionary algorithms such as Genetic Algorithm (GA) Particle Swarm Optimization (PSO) and Ant-Colony Optimization (ACO) which are used to optimize the Artificial Neural Network (ANN). Optimization of Neural Networks improves speed of recall and may also improve the efficiency of training. Here we have used the Ant colony optimization, Particle Swarm … …Journal of Computer Science, Vol. 10, Issue 1 · 12 Nov 2013 · 7,287 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Channel Equalization Using Multiplicative Neural Network for Rayleigh Faded ChannelP. Sivakumar, N. Chithra, S. N. Sivanandam, M. RajaramProblem statement: Digital transmission over band-limited communication channel largely suffers from ISIS and various noise sources. The presence of ISI and noise causes bit errors in the received signal. Equalization is necessary at the receiver to overcome these channel impairment to recover the original transmitted sequence. Traditionally equalization is considered as equivalent to inverse filtering and implemented using linear-perform under … …Journal of Computer Science, Vol. 7, Issue 11 · 18 Aug 2011 · 6,931 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Network in Modeling Malaysian Oil Palm YieldZuhaimy Ismail, Azme KhamisProblem statement: Forecasting of palm oil yield has become an important element in the management of oil palm industry for proper planning and decision making. The importance of yield forecasting has led us to explore modeling of palm oil yield for Malaysia using the most recent development of Artificial Neural Network (ANN). The main issue in yield forecasting is to … …American Journal of Applied Sciences, Vol. 8, Issue 8 · 19 Jul 2011 · 8,576 accessesView PDFCite
Research ArticleOpen accessIn the abstractIndoor Positioning System Using Artificial Neural NetworkHamid Mehmood, Nitin K. Tripathi, Taravudh TipdechoProblem statement: Location knowledge in indoor environment using Indoor Positioning Systems (IPS) has become very useful and popular in recent years. A number of Location Based Services (LBS) have been developed, which are based on IPS, these LBS include asset tracking, inventory management and security based applications. Many next-generation LBS applications such as social networking, local search, advertising and geo-tagging … …Journal of Computer Science, Vol. 6, Issue 10 · 30 Aug 2010 · 8,838 accessesView PDFCite
Research ArticleOpen accessIn the abstractAsymptotic Behavior of an Artificial Neural Network Defined on Multipartite Directed GraphN. C. Majee, A. B. RoyProblem statement: Artificial Neural Network (ANN) are simple models to mimic some essential features of the complex central nervous system. ANN models are realistic due to their inherent stochastic nature of neural computation and strong synchronicity. Different ANN models are associated with directed and signed graphs. The present study proceeded by relaxing certain simplifying assumptions in the ANN model. Approach: … …OnLine Journal of Biological Sciences, Vol. 10, Issue 1 · 30 Jun 2010 · 7,476 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Optimization with Multilayer Perceptron Neural Network and Using New Pattern in Decision Tree ComparativelyMurat Kayri, Omay CoklukProblem statement: The aim of the present study is to exemplify the use of Artificial Neural Networks (ANN) for parameter prediction. Missing value or unreal approach to some questions in scale is a problem for unbiased findings. To learn a real pattern with ANN provides robust and unbiased parameter estimation. Approach: To this end, data was collected from 906 students … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,200 accessesView PDFCite