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48 results for “Error Accuracy Prediction”
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Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Model for Heart Disease Classification and CategorizationSrikanth Meda, Raveendrababu BhogapathiProgressions in the coordination among the machine learning algorithms, helped to achieve high accuracy and reliability in decision-making systems. Due to the impact and importance of heart diseases in real life, designing the efficient heart disease prediction model become a pivotal aspect today. Former research scholars applied the popular supervised machine learning models like Decision Trees, Naïve Bayes, ANN's, and … …Journal of Computer Science, Vol. 18, Issue 4 · 19 Apr 2022 · 6,535 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvSVD++: 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 · 6,731 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn AI-Powered Integrated Care Model Combining Traditional Chinese Medicine and Western Medicine for Personalized Alzheimer’s Disease ManagementShurong Li, Yiming Chen, Jin Xu et al.Alzheimer's Disease (AD) gradually reduces memory and cognition. While Western medicine focuses on pharmacological treatments, it frequently ignores holistic factors such as mood and digestion. Traditional Chinese Medicine (TCM) addresses these issues through a wellness-oriented approach. However, the combination of both systems in patient care is uncommon. Current Alzheimer's disease treatments are often siloed, relying solely on Western or alternative … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 4 · 16 Feb 2026 · 2,063 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,316 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis 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 · 7,440 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Based Feature Selection of Macroeconomic Variables for Stock Market PredictionIsaac Kofi Nti, Adebayo Felix Adekoya, Benjamin Asubam WeyoriA firm’s equity price on the stock-market is reported to be closely related to the Macroeconomic Variable (MVs) of the country in which the firm trades. For this reason, researchers, market traders, financial analysts and forecasters to examine the association between MVs and stock-price have carried out numerous studies, using time-series statistical analysis methods like Autoregressive Integrated Moving Average (ARIMA), … …American Journal of Applied Sciences, Vol. 16, Issue 7 · 31 Jul 2019 · 10,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting the Number of Monthly Active Facebook and Twitter Worldwide Users Using ARMA ModelQasem Abu Al-Haija, Qian Mao, Kamal Al NasrIn this study, an Auto-Regressive Moving Average (ARMA) Model with optimal order has been developed to estimate and forecast the short term future numbers of the monthly active Facebook and Twitter worldwide users. In order to pickup the optimal estimation order, we analyzed the model order vs. the corresponding model error in terms of final prediction error. The simulation results … …Journal of Computer Science, Vol. 15, Issue 4 · 19 Apr 2019 · 8,599 accessesView PDFCite
Research ArticleOpen accessIn the abstractDefect Classification of Reinforced Concrete Structures with Nondestructive Tests Using Statistical and Machine Learning MethodsSajjad Sayyar-Roudsari, Armaghan Shalbaftabar, Farshid Damirchilo et al.In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 3 · 11 Jun 2024 · 5,258 accessesView PDFCite
Research ArticleOpen accessIn the abstractTelomere Length Measurement by Quantitative Real-time PCR: A Molecular Marker for Human Age PredictionNaglaa F. Alhusseini, Abdelmonem G. MadbolyThe fact that telomere shortening occurs with aging leads to the hypothesis that a correlation could be made between Telomere Length (TL) and suspect age. This study aimed to assess if TL can be used as an investigational tool to predict human age through developing a formula based on this correlation with accuracy suitable to be applied in forensic practice. … …American Journal of Biochemistry and Biotechnology, Vol. 12, Issue 1 · 24 Mar 2016 · 8,004 accessesView PDFCite
Research ArticleOpen accessIn the abstractFUZZY MODEL OPTIMIZATION FOR TIME SERIES DATA USING A TRANSLATION IN THE EXTENT OF MEAN ERRORNurhayadi, Subanar, Abdurakhman, Agus Maman AbadiRecently, many researchers in the field of writing about the prediction of stock price forecasting, electricity load demand and academic enrollment using fuzzy methods. However, in general, modeling does not consider the model position to actual data yet where it means that error is not been handled optimally. The error that is not managed well can reduce the accuracy of … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 2 Jun 2014 · 6,733 accessesView PDFCite