Research ArticleOpen accessPhrase in the titleComparative Analysis of Deep Learning Models for Multi-Step Prediction of Financial Time SeriesSaugat Aryal, Dheynoshan Nadarajah, Prabath Lakmal Rupasinghe et al.Financial time series prediction has been a key topic of interest among researchers considering the complexity of the domain and also due to its significant impact on a wide range of applications. In contrast to one-step ahead prediction, multi-step forecasting is more desirable in the industry but the task is more challenging. In recent days, advancement in deep learning has … …Journal of Computer Science, Vol. 16, Issue 10 · 27 Oct 2020 · 6,967 accessesView PDFCite
Research ArticleOpen accessIn the keywordsData-Driven Forecasting Schemes: Evaluation and ApplicationsJosip Vrbanek Jr, Wilson WangA reliable multi-step predictor is very useful to a wide array of applications to forecast the behavior of dynamic systems. The objective of this paper is to develop a more robust data-driven predictor for time series forecasting. Based on simulation analysis, it is found that multi-step-ahead forecasting schemes based on step inputs perform better than those based on sequential inputs. … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,565 accessesView PDFCite
Review ArticleOpen accessIn the abstractDetection of Phishing Websites Hosted in Name Server Flux Networks Using Machine LearningThomas NagunwaAttackers are increasingly using Name Server IP Flux Networks (NSIFNs) to run the domain name services of their phishing websites in order to extend the duration of their phishing operations. These networks host a name server that manages the Domain Name System (DNS) records of the websites on a network of compromised machines with frequently changing IP addresses. As a … …Journal of Computer Science, Vol. 20, Issue 1 · 12 Dec 2023 · 5,596 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock price prediction using Generative Adversarial NetworksHungChun Lin, Chen Chen, GaoFeng Huang, Amir JafariDeep learning is an exciting topic. It has been utilized in many areas owing to its strong potential. For example, it has been widely used in the financial area which is vital to the society, such as high-frequency trading, portfolio optimization, fraud detection and risk management. Stock market prediction is one of the most popular and valuable areas in finance. … …Journal of Computer Science, Vol. 17, Issue 3 · 2 Apr 2021 · 17,700 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Biomechanical Composite Model to Determine Effective Elastic Moduli of the CNS Gray MatterMehdi Khoshgoftar, Siamak Najarian, Farhad Farmanzad et al.Brain tissue is a heterogeneous material with complicated microstructural features. Models based on microstructure can lead to more accurate and physically realistic predictions of mechanical characteristics of brain tissue. A two-step Mori-Tanaka/Voigt homogenization procedure is implemented into a 3D microstructurally-based multi-phase composite model, composed of randomly-oriented elastic axons, dendrites and neuronal cell bodies surrounded by an elastic matrix. The effects … …American Journal of Applied Sciences, Vol. 4, Issue 11 · 30 Nov 2007 · 7,775 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordSTRATEGY PATTERNS PREDICTION MODELAram Baruch Gonzalez Perez, Jorge Adolfo Ramirez UrestiMulti-agent systems are broadly known for being able to simulate real-life situations which require the interaction and cooperation of individuals. Opponent modeling can be used along with multi-agent systems to model complex situations such as competitions like soccer games. In this study, a model for predicting opponent moves based on their target is presented. The model is composed by an … …Journal of Computer Science, Vol. 10, Issue 1 · 12 Nov 2013 · 6,854 accessesView PDFCite