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23 articles for “Price Prediction”
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Research ArticleOpen accessPhrase in the titleComparative Study of Garuda Indonesia Stock Price Prediction Using SVM, LSTM and Multiple Linear RegressionMuhammad Naufal Luthfi, Evaristus Didik MadyatmadjaStock shares are one of the investment products or tools that have been used by many people. Shares have interesting options for saving or investment and are able to provide attractive returns based on corporate or company growth. Many factors can affect the share prices, whether internal or external companies. This research was conducted on Garuda Indonesia's stock price with … …Journal of Computer Science, Vol. 21, Issue 4 · 25 Mar 2025 · 5,032 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleStock 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 accessPhrase in the titlePrice Prediction for Agricultural Commodities in Bandung Regency Based on Functional Link Neural Network and Artifical Bee Colony AlgorithmsFhira Nhita, Deni Saepudin, Andini Paramita et al.In Indonesia, fluctuating agricultural commodity prices often impacts society negatively. In this study, farmers in Bandung Regency, West Java, Indonesia, were chosen as a case study. Fluctuating agricultural commodity prices can lead to farmers suffering losses due to the sale price being smaller or equal to the cost of planting. Price is influenced by crop productivity, while planting productivity is … …Journal of Computer Science, Vol. 15, Issue 10 · 6 Mar 2019 · 7,904 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleKalman Filtering for Stocks Price Prediction and ControlJimbo Henri Claver, Mbiazi Dave, Shu Felix CheStocks price analysis has been a critical area of research as the stock market is a very fluctuating market. Stocks price is affected by demand and supply dynamics making it difficult to forecast the price of a stock at a particular instant. The entire idea of predicting stocks price is to gain significant profits but predicting how the stock market … …Journal of Computer Science, Vol. 19, Issue 6 · 20 May 2023 · 6,367 accessesView PDFCite
Research ArticleOpen accessPhrase 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 · 9,603 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIntegrated Multiple Linear Regression-One Rule Classification Model for the Prediction of Stock Price TrendLock Siew Han, Md Jan NordinOne of the main problems of predicting stock price with regression approach is overfitting a model. An overfit model becomes tailored to fit the random noise in the dataset rather than reflecting the overall population. For this it is necessary to construct an integrated regression-classification model to approximate the true model for the entire population in the dataset. The proposed … …Journal of Computer Science, Vol. 13, Issue 9 · 18 May 2017 · 7,422 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleUltimate Prediction of Stock Market Price MovementRebwar M. Nabi, Soran Ab. M. Saeed, Habibolah Bin Harron, Hamido FujitaInvestment in the stock market is currently very popular due to its economic gain. Numerous researchers’ and academicians’ work is focused on financial time series prediction due to its data availability and profitability. Therefore, this study presents the design and implementation of a novel binary classification framework to predict stock market trends. The framework is composed of data preprocessing, feature … …Journal of Computer Science, Vol. 15, Issue 12 · 25 Dec 2019 · 8,545 accessesView PDFCite
Research ArticleOpen accessIn the keywordsStock 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 · 6,262 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Hybridization of Enhanced Artificial Bee Colony-Least Squares Support Vector Machines for Price ForecastingZuriani Mustaffa, Yuhanis YusofProblem statement: As the performance of Least Squares Support Vector Machines (LSSVM) is highly rely on its value of regularization parameter, γ and kernel parameter, σ2, man-made approach is clearly not an appropriate solution since it may lead to blindness in certain extent. In addition, this technique is time consuming and unsystematic, which consequently affect the generalization performance of LSSVM. … …Journal of Computer Science, Vol. 8, Issue 10 · 28 Aug 2012 · 6,796 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 accessesView PDFCite