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69 results for “Statistical Error”
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Research ArticleOpen accessIn the abstractApplication of Preference Selection Index and TOPSIS in Product Aspect Extraction and RankingSaif Addeen Ahmad Alrababah, Nawaf Omara AlsrehinDecision-making methodologies can differentiate between several types of criterion weights. The subjective weights of decision-makers are prone to be influenced by various factors, including their level of knowledge, experience and competency. This may result in the wrong evaluation of the criteria due to the inherent ambiguity of human judgments, leading to unavoidable assessment errors. Beyond that, while assessing the decision … …Journal of Computer Science, Vol. 20, Issue 7 · 24 May 2024 · 4,838 accessesView PDFCite
Research ArticleOpen accessIn the abstractInvestigation and Comparison of the Quantitative and Qualitative Frequency Distribution of the RiversVijay P. Singh, Mohsen Ghane, Kaveh Ostad-Ali-Askari et al.The entrance of pollutants from human activities to the surface water has seriously threatened the quality of water. TDS is an important qualitative parameter of water that describes the water salinity by measuring the concentration of total dissolved solids. First, using TDS and discharge data of the Cuyahoga River, Ohio, the partial and annual data sets were obtained. Then, partial … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 4 · 16 Oct 2017 · 8,487 accessesView PDFCite
Research ArticleOpen accessIn the abstractBuilding Energy Modeling Using Artificial Neural NetworksMaya Arida, Nabil Nassif, Rand Talib, Taher Abu-LebdehAccurate modeling of total building energy is now vital to reduce energy consumption. This is especially true for buildings since they are considered as the largest energy consumer in the United States. This paper investigates modeling methods for building energy-systems using non-linear auto-regression artificial neural networks. The proposed model can forecast the whole building energy consumptions given the four input … …Energy Research Journal, Vol. 7, Issue 2 · 6 Jun 2017 · 7,125 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeast Absolute Deviation Regression and Least Squares for Modeling Retention Indices of Set Compounds Food and Pollutants of the EnvironmentFatiha Mebarki, Khadija Amirat, Salima Ali Mokhnach, Djellol MessadiConsidering the importance of the statistical analysis of regression in modeling based separately on study for Quantitative structure retention indices on Carbowax 20 M (ICw20M) and OV-101 columns (IOV-101) relationships (QSRR) are determined for 114 pyrazines. The detection of influential observations for the standard least squares regression model is a problem which has been extensively studied. Least Absolute Deviation regression … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 5 Jun 2017 · 7,424 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffect of Temperature Change and Estradiol Levels on Cattle Oocytes Developmental Competency: Comparing X-Sexed and Non-Sexed Sperm Following in vitro FertilizationMaleke Dimpho Sebopela, Masindi Lottus Mphaphathi et al.The study aimed to investigate the effects of temperature change and estradiol (E2) hormone level on In Vitro Maturation (IVM) and fertilization of cattle oocytes using X-sexed and non-sexed sperm. In experiment 1: The oocytes were incubated at various temperatures of 35.5, 36.5, 37.5, 38.5, 39.5 and 40.5°C under similar conditions with 5% CO2, in humidified air for 22 h. … …American Journal of Animal and Veterinary Sciences, Vol. 18, Issue 4 · 16 Nov 2023 · 5,319 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL ROBUST AND EFFICIENT TOOL FOR DETECTING HETEROSCEDASTICITYWei Xiong, Maozai TianOne of the greatest values of Quantile Regression (QR) is that it provides a good procedure in the sense that QR could be much more efficient and sometimes arbitrarily more efficient in recovering the mean function than the Least Squares (LS) even when without moment conditions. However, heteroscedasticity definitely causes conditional variances of parametric or nonparametric estimates of mean functions … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 21 Mar 2014 · 6,657 accessesView PDFCite
Research ArticleOpen accessIn the abstractHEURISTIC DISCRETIZATION METHOD FOR BAYESIAN NETWORKSMariana D.C. Lima, Silvia M. Nassar, Pedro Ivo R.B.G. Rodrigues et al.Bayesian Network (BN) is a classification technique widely used in Artificial Intelligence. Its structure is a Direct Acyclic Graph (DAG) used to model the association of categorical variables. However, in cases where the variables are numerical, a previous discretization is necessary. Discretization methods are usually based on a statistical approach using the data distribution, such as division by quartiles. In … …Journal of Computer Science, Vol. 10, Issue 5 · 18 Jan 2014 · 7,054 accessesView PDFCite
Research ArticleOpen accessIn the abstractParameter Estimation and Determination of Sample Size in Logistic RegressionAdeleke Kazeem Adedayo, Dawud Adebayo AgunbiadeThe determination of Sample-Size is often an important step in planning a statistical study and it is usually a difficult task. Among the important hurdles to be surpassed, one must obtain an estimate of one or more error variances and specify an effective sample size of importance. The study was carried out to check for the estimation of parameter and … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 4 Feb 2013 · 6,915 accessesView PDFCite
Research ArticleOpen accessIn the abstractLatent Dirichlet Allocation Model for Raga Identification of Carnatic MusicRajeswari Sridhar, Manasa Subramanian, B. M. Lavanya et al.Problem statement: In this study the Raga of South Indian Carnatic music is determined by constructing a model. Raga is a pre-determined arrangement of notes, which is characterized by an Arohana and Avarohana, which is the ascending and descending arrangement of notes and Raga lakshana. Approach: In this study a Latent Dirichlet Allocation (LDA) model is constructed to identify the … …Journal of Computer Science, Vol. 7, Issue 11 · 30 Aug 2011 · 7,734 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Network in Modeling Malaysian Oil Palm YieldZuhaimy Ismail, Azme KhamisProblem statement: Forecasting of palm oil yield has become an important element in the management of oil palm industry for proper planning and decision making. The importance of yield forecasting has led us to explore modeling of palm oil yield for Malaysia using the most recent development of Artificial Neural Network (ANN). The main issue in yield forecasting is to … …American Journal of Applied Sciences, Vol. 8, Issue 8 · 19 Jul 2011 · 8,576 accessesView PDFCite