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223 results for “performance prediction”
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Research ArticleOpen accessIn the abstractCommunity Aware Recommendation System with Explicit and Implicit Link PredictionMuhammed E Abd Alkhalec Tharwat, Mohd Farhan Md Fudzee, Shahreen Kasim et al.Recommendation systems are essential tools that help users discover content they may be interested in, amidst the vast amount of information available online. However, current methods, such as using historical user-item interactions and collaborative filtering, have limitations in accurately predicting user preferences. Our research aims to address these challenges and improve the performance of recommendation systems. In this article, we … …Journal of Computer Science, Vol. 19, Issue 8 · 19 Jul 2023 · 5,866 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,077 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of Customer Predictive Model for Investment Using Ensemble Learning TechniqueThongchai Kaewkiriya, Kittipol WisaengMany new investors that want to purchase a fund might be disappointed with the return-on-investment value. This problem occurs because they do not know important factors that could affect the market value. Plus, some assets might not be suitable for the investor's investment style. To reduce the mentioned problems, many asset management companies research the systems that could find a … …Journal of Computer Science, Vol. 19, Issue 6 · 25 May 2023 · 5,477 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Multi-Layer Perceptron in Ensemble Using Random Search for Bankruptcy PredictionBambang Siswoyo, Zuraida Abal Abas, Ahmad Naim Che Pee et al.A corporation is in financial trouble if it has money problems but has yet to be bankrupt. Companies' financial woes must be identified early to implement various bankruptcy avoidance strategies. This study discusses the optimization of the multi-layer perceptron ensemble stacking classifier hyperparameter by majority voting as a methodology for constructing a classification model for bankruptcy prediction (MLP-STM). The primary … …Journal of Computer Science, Vol. 19, Issue 2 · 5 Feb 2023 · 7,240 accessesView PDFCite
Research ArticleOpen accessIn the abstractHuman Age Predication from Face Images Based on Combining Deep Wavelet Network and Machine Learning AlgorithmsZahraa Salam Abu Ghrban, Nidhal K. EL AbbadiDue to the numerous variances in face appearance, age estimation using facial images is a difficult subject. Many factors can affect the estimation of human age such as race, face post, gender, lifestyle, etc. By considering more factors, the optimum performance may be obtained. In this study, we proposed a method to predict the age of facial images. The proposed … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 5,573 accessesView PDFCite
Research ArticleOpen accessIn the abstractStroke Risk Assessment with Classical ML MethodsMohammad Aref Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh et al.Stroke, often caused by a disruption in the supply of essential oxygen, blood, and nutrients to the brain, represents a significant global health challenge. Due to limited resources, developing countries like Ethiopia face unique obstacles in identifying and treating strokes. This study explores the potential of Machine Learning (ML) techniques to predict stroke risk and facilitate early detection and intervention. … …Journal of Computer Science, Vol. 21, Issue 1 · 18 Dec 2024 · 4,657 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock Closing Price Forecasting Using LSTM, Sentiment Analysis, Kalman FilterAssel Abdildayeva, Galymzhan Nurtugan, Guldana Taganova, Ardak AkhmetovaThe article explores the problem of predicting the closing prices of stocks using an innovative approach that combines methods of machine learning, sentiment analysis and noise filtering. The focus is on the development and testing of a comprehensive model that integrates recurrent neural networks (LSTM) for time series analysis, the GPT-3 language model for processing and analyzing textual data from … …Journal of Computer Science, Vol. 20, Issue 11 · 4 Sep 2024 · 6,266 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultiple Linear Regression to Predict Electrical Energy Consumption Based on Meteorological Data: Application to Some Sites Supplied by the CEB in TogoApaloo Bara Komla Kpomonè et al.The prediction model developed in this article is based on the use of meteorological variables to estimate the consumption of electrical energy at the substations of the Electric Community of Benin. The objective is to predict this consumption in order to adapt production to it. The posts (Lomé Aflao, Légbasito, and Lomé port) are the targets that were used in … …American Journal of Applied Sciences, Vol. 21, Issue 1 · 10 Jun 2024 · 5,790 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Multi-Split Cross-Strategy for Enhancing Machine Learning Algorithms Prediction Results with Data Generated by Conditional Generative Adversarial NetworkAbdelfattah Abassi, Brahim Bakkas et al.In this study, we present a Multi-Split Cross-Strategy (MSC-Strategy) designed to leverage synthetic tabular data generated by a Conditional Generative Adversarial Network (CGAN). Our study aims to investigate the potential of synthetic data in comparison to real-world data for improving machine learning predictive results. Firstly, we develop a CGAN architecture tailored to generate synthetic tabular data, trained on a comprehensive … …Journal of Computer Science, Vol. 20, Issue 7 · 9 Apr 2024 · 6,701 accessesView PDFCite
Research ArticleOpen accessIn the abstractShelf-Life Prediction of Specialty Coffees using the Arrhenius ModelFrank Fernández Rosillo, María Alina Cueva Ríos, Lenin Quiñones Huatangari, Carla Guianella Samaniego LalanguiThe study estimated the shelf life of roasted and ground specialty coffees in bi-laminated and tri-laminated packaging concerning cup score, using the Acceleration Test at temperatures of 40, 50, and 60°C. The sensory evaluation was carried out by Q Grader tasters. Based on the higher value of the coefficient of determination of the regressions resulting from the cup and temperature … …OnLine Journal of Biological Sciences, Vol. 23, Issue 1 · 23 Dec 2022 · 6,885 accessesView PDFCite