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56 results for “relative error”
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Research ArticleOpen accessIn the keywordsKalman 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 accessIn the keywordsRegionalism in East Asia: The Role of North East Asian NationsFithra Faisal HastiadiProblem statement: For the past few years, regionalism has been progressing in East Asia with the likes of China, Japan and Korea (CJK) as the most prominent actors. Unfortunately, with the absence of trade arrangement amongst the CJK, the present regional trade scheme is not sufficient to reach sustainability. Thus, the study aims to give the solution to the problem. … …American Journal of Economics and Business Administration, Vol. 3, Issue 2 · 7 Apr 2011 · 6,939 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCorrelation Based ADALINE Neural Network for Commodity TradingJ. Chandra, M. Nachamai, Anitha S. PillaiCommodity trading is one of the most popular resources owning to its eminent predictable return on investment to earn money through trading. The trading includes all kinds of commodities like agricultural goods such as wheat, coffee, cocoa etc. and hard products like gold, rubber, crude oils etc.,. The investment decision can be made very easily with the help of the … …Journal of Computer Science, Vol. 11, Issue 7 · 29 Oct 2015 · 7,825 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEvaluation of Soil Moisture Sensors under Intelligent Irrigation Systems for Economical Crops in Arid RegionsMohamed Said Abdall El Marazky, Fawzi Said Mohammad, Hussein Mohamed Al-GhobariProblem Statement: In irrigation water management, irrigation water use represents a substantial opportunity for agriculture water savings. Automation of irrigation systems, based on Soil Moisture Sensors Systems (SMSS) has the potential to provide maximum water use efficiency by maintaining soil moisture at optimum levels. Approach: The objective of this research was to evaluate the performance of soil moisture sensors under … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 2 · 24 Jun 2011 · 8,904 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSoftware Cost Estimation Model Based on Integration of Multi-agent and Case-Based ReasoningHasan Al-SakranAccurate software cost estimation is a vital task that affects the firm's software investment decisions before committing required resources to that project or bidding for a contract. This study proposes an improved Case-Based Reasoning (CBR) approach integrated with multi-agent technology to retrieve similar projects from multi-organizational distributed datasets. The study explores the possibility of building a software cost estimation model … …Journal of Computer Science, Vol. 2, Issue 3 · 31 Mar 2006 · 6,740 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEstimation Techniques for Monitoring and Controlling the Performance of the Computer Communication NetworksIbrahiem M.M. El Emary, Adanan I. Al RabiaThis study was concerned with making a comparative study between four types of time series model with the goal of choosing the optimum one to predict the performance of a computer communication network. The investigated four types of time series are: Least Square (LS), Fourier series, Exponential Weighted Moving Average (EWMA) and the Auto Regressive Integrated Moving Average (ARIMA). Comparative … …American Journal of Applied Sciences, Vol. 2, Issue 10 · 31 Oct 2005 · 7,126 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,355 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 · 5,785 accessesView PDFCite
Research ArticleOpen accessIn the abstractAbsolute Measures of Interindividual Variation: A Simulation StudyJosé Moral-de la RubiaFour absolute measures and one relative measure of interindividual variability have been defined, together with their point and interval estimation (bootstrap and asymptotic), and an R script has been developed for their computation. However, further simulation studies are required to strengthen their methodological evaluation. This study focused on the three absolute measures with potentially better regularity conditions, Mean Interindividual Differences … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 4 Aug 2026 · 957 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Cross-Validation Under Concept Drift for Time Series ForecastingKunjira Kingphai, Prapakorn Kanjina, Kamol Sanittham, Wacharong WongsanurakTime-series forecasting often involves non-stationary data, making i.i.d. validation unreliable and fixed-window protocols vulnerable to leakage and biased error estimates. We propose Adaptive Time-Series Cross-Validation (ATSCV), a drift-aware evaluation framework that uses statistical change-point detection to partition each series into contiguous, approximately stationary regimes, followed by forward-chaining folds that respect those boundaries. By aligning train–validation splits with distributional changes (with … …Journal of Computer Science, Vol. 22, Issue 7 · 7 Jul 2026 · 1,488 accessesView PDFCite