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357 articles for “Neural Model”
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Research ArticleOpen accessEvery word in the titleA Cost Estimation Model for Repair Bridges Based on Artificial Neural NetworkMohamed Bouabaz, Mounir HamamiEstimating the total cost of bridges repair and maintenance with high accuracy is an important components, and points to a need for a cost estimation model. This paper focuses on the development of a more accurate estimation model for repair and maintenance of bridges in developing countries using artificial neural networks. Cost and design data for two categories of repair … …American Journal of Applied Sciences, Vol. 5, Issue 4 · 30 Apr 2008 · 7,300 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleForecasting 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 · 6,968 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid Hot Strip Rolling Force Prediction using a Bayesian Trained Artificial Neural Network and Analytical ModelsAbdelkrim Moussaoui, Yacine Selaimia, Hadj A. AbbassiThe authors discuss the combination of an Artificial Neural Network (ANN) with analytical models to improve the performance of the prediction model of finishing rolling force in hot strip rolling mill process. The suggested model was implemented using Bayesian Evidence based training algorithm. It was found that the Bayesian Evidence based approach provided a superior and smoother fit to the … …American Journal of Applied Sciences, Vol. 3, Issue 6 · 30 Jun 2006 · 7,140 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHouse Price Prediction: Hedonic Price Model vs. Artificial Neural NetworkVisit Limsombunchai, Christopher Gan, Minsoo LeeThe objective of this study is to empirically compare the predictive power of the hedonic model with an artificial neural network model for house price prediction. A sample of 200 houses in Christchurch, New Zealand is randomly selected from the Harcourt website. Factors including house size, house age, house type, number of bedrooms, number of bathrooms, number of garages, amenities … …American Journal of Applied Sciences, Vol. 1, Issue 3 · 30 Sep 2004 · 9,606 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Hybrid Artificial Neural Network Model for Option PricingHanningtone Meshack Simiyu, Anthony Gichuhi Waititu, Jane Aduda AkinyiIn the absence of a well-defined input selection technique associated with the pure ANN models, Option pricing using pure ANN models while relaxing the assumption of constant volatility remains a challenge. The conservative drill espoused has been to make allowances for a large number of input lags with the confidence that the ability of ANN to integrate suppleness and redundancy … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 8 Aug 2019 · 7,415 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComparative Analysis of Neural Network Models for Predicting EUR/USD Direction: An Empirical StudyEl Badaoui Mohamed, Raouyane Brahim, El Moumen Samira, Bellafkih MostafaThis paper presents a rigorous comparative analysis of six feedforward neural network models for predicting the directional movement of the EUR/USD currency pair. The evaluated models include the Learning Vector Quantization, Cascade Neural Network, Feedforward Neural Network, Single Layer Perceptron, Multi-Layer Perceptron, and Radial Basis Function network. Utilizing daily historical data from April 2009 to May 2024, each model was … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,340 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification Model of Traditional Chinese Medicine Prescription Decocting Duration Combining Text Convolutional Neural Network with Attention MechanismZhibiao Li et al.The decocting time of Traditional Chinese Medicine (TCM) formulas is crucial for therapeutic effects. To better capture the important characteristics related to the decocting time of TCM formulas, a formula decocting time classification model TextCNN-attention that integrates the attention mechanism and Text Convolutional Neural Network is proposed. This model predicts the decocting time of formulas and divides them into long-term, … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 4 · 26 Sep 2024 · 4,372 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleQuantization and Pipelined Hardware Implementation of Deep Neural Network ModelsEl Hadrami Cheikh Tourad, Mohsine EleuldjInrecent years, Deep Neural Networks (DNNs) have garnered much interest due toadvances in computational power and data availability. Indeed, DNNs presents a considerable advantage in several challenges, suchas classification problems and video analysis. Although, such accomplishmentleads to significantly increasing energy demands, computational expenses, andmemory capacity. In addition, current efficient DNNs may have more complex andextensive structures. As a result, implementing … …Journal of Computer Science, Vol. 18, Issue 11 · 26 Oct 2022 · 5,707 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,736 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAnalysis of Artificial Neural Network Point Forecasting Models and Prediction Intervals for Solar Irradiance EstimationAntônio Fabrício Guimarães de Sousa, Helaine Cristina Moraes Furtado, Wilson Negrão Macêdo, Anderson Alvarenga de Moura MenesesAn accurate knowledge on solar irradiance prediction is particularly required for proper development and planning of Photovoltaic (PV) energy systems. The main purpose of the present research is to assess the accuracy of Artificial Neural Networks (ANN) short-term forecast of univariate solar irradiance time series, with conventional point prediction and Prediction Intervals (PIs), comparing models. The Lower Upper Bound Estimation … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 3 · 17 Jul 2020 · 7,443 accessesView PDFCite