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69 results for “Statistical Error”
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Research ArticleOpen accessEvery word in the titleStatistical Size and Power of Eight Normality Tests in Presence of GARCH (1 1) ErrorsJulio César Alonso, Daniela EstradaIn this work, we assess the power and size of eight normality tests underthe assumption that errors follow a GARCH (1, 1) process by using MonteCarlo simulations. Four results stand out. First, the presence of a GARCH(1, 1) process increases the probability of making type I error. Second, Pearsonnormality test is recommended if it is assumed that errors follow a … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 11 Feb 2019 · 6,992 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEfficient Monte Carlo Algorithm Using Antithetic Variate and Brownian Bridge Techniques for Pricing the Barrier Options with Rebate PaymentsHasan AlzubaidiThe down-and-out call barrier option with rebate payment on dividend-paying stock is simulated using a new version of the Monte Carlo algorithm. The standard Monte Carlo method for simulating such an option suffers from two sources of errors: Hitting time error inherent from time stepping and the Monte Carlo statistical error. We present a modified version of Monte Carlo method … …Journal of Mathematics and Statistics, Vol. 12, Issue 1 · 22 Feb 2016 · 8,259 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 abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 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 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 abstractIntegrated Assessment of Water Resource Sustainability in the Upper Amojú River Basin, Northern Peruvian AndesJuan Eduardo Suarez-Rivadeneira, Freddy A. Manayay, Mayra Pamela Musayón Diaz et al.This study presents a comprehensive, statistically robust assessment of water resource sustainability in the upper section of the Amojú River Basin, Province of Jaén northern Peruvian Andes, using the Sarandón multi-cirteria methodology. A stratified convenience sample of n = 887 households distributed across 22 localities was surveyed, achieving a margin of error of ±2.61% at the 95% confidence level (finite-population … …OnLine Journal of Biological Sciences, Vol. 26, Issue 4 · 26 Sep 2026 · 719 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 819 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Adaptive Detail Preserving Modified Progressive Pca Thresholding Based Image DenoisingN. Anilkumar, S. Radhakrishnan, Shaik Syed Basha et al.Radiologists use medical imaging tools to assess the anatomy and function of interior organs. However, medical images are frequently distorted by various types of noise generated during the capture, transmission, and reconstruction operations, which can dramatically reduce image quality and hide critical diagnostic features. As a result, developing effective denoising algorithms that suppress noise while maintaining structural information remains a … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 529 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Non-Technical Electricity Loss Detection Using Artificial Neural Networks: Case of Cameroon Distribution NetworkLekini Nkodo Claude Bernard, Bell Serge Samuel, Nyemb Nsoga Valjacques et al.Non-Technical Losses (NTL) represent a critical challenge for power utilities, particularly in developing countries. This paper proposes an unsupervised deep learning approach based on an autoencoder to detect abnormal electricity consumption patterns in the Cameroonian distribution network. The model learns normal customer behavior using historical consumption data and identifies anomalies through reconstruction error analysis. Statistical thresholds are applied to classify … …American Journal of Engineering and Applied Sciences, Vol. 19, Issue 1 · 23 Jul 2026 · 1,225 accessesView PDFCite