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626 results for “Prediction”
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Research ArticleOpen accessIn the abstractComparative Analysis of the Artificial Neural Networks Options Pricing Model Under Constant and Time-Variant VolatilitiesHanningtone Meshack Simiyu, Anthony Gichuhi Waititu, Jane Aduda AkinyiOption pricing using artificial neural networks (ANN) model while relaxing the assumption of constant volatility still remains a challenge. The conventional practice for pure ANN models has been to either model volatility using the very ANN model and have the model output fed as an input to the ANN option pricing model, or to make allowances for a large number … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 20 Jul 2019 · 7,010 accessesView PDFCite
Research ArticleOpen accessIn the abstractToxicology of Nanomaterials on ZebrafishJimmy De León, María del C. Cotto, Francisco MárquezIncreases in the use and the progressive manufacture of new Engineered Nanomaterials (ENMs) lead to inquire about their impact on the environment. Due to the small size, high reactivity inside organisms and the unusual physicochemical properties of the ENMs, the predictions of toxicity are very complex. The zebrafish (Danio rerio) has been granted as a practical alternative to study the … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 2 · 29 May 2019 · 7,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Classification Models for Predicting Mortality Rate Using Thyroid Cancer DataNorah Saleh AlghamdiMachine Learning (ML) can potentially enhance predictions in real-life domains. This study presents an evaluation and comparison of different ML methods which can be applied on thyroid cancer dataset, called Prostate, Lung, Colorectal and Ovarian (PLCO), of approximately 155,000 participants with thyroid cancer occurrence and mortality incidence. The ML models are explored for predicting mortality rates of patients with thyroid … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 7,788 accessesView PDFCite
Research ArticleOpen accessIn the abstractCharacterization of the Changes in Opened Sufu Bottles During Storage with Mathematical ModelJingJing Liang, Dawei Li, Ruiqin Shi et al.Artificial Neural Network (ANN) is a type of nonlinear empirical model, which can clarify the complex relation between the inputs and outputs that allows it to approximate any nonlinear function for making predictions. The objective of this study is to monitor the Biogenic Amines (BAs) content and selected physicochemical properties of sufu (a traditional Chinese fermented soybean product) along time. … …American Journal of Biochemistry and Biotechnology, Vol. 14, Issue 4 · 12 Dec 2018 · 9,353 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnivariate Generalized Additive Models for Simulated Stationary and Non-Stationary Generalized Pareto DistributionMostafa Behzadi, Mohd Bakri Adam, Anwar FitriantoGeneralized additive models as a predictor in regression approaches, are made up over cubic spline basis and penalized regression splines. Despite of linear predictor in GLM, generalized additive models use a sum of smooth functions of covariates as a predictor. The data which are used in this study have generalized Pareto distribution and have been simulated by inversion method. The … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 3 Jun 2017 · 7,430 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeveloping and Testing Dynamic Models for HVAC Systems Using System Identification ApproachNabil Nassif, Jasmine Buford, Taher M. Abu-LebdehThis paper proposes integrated modeling and optimization methods for a chilled water HVAC system using a system identification approach. Two multiple input-single output models are developed to find the supply air temperature and fan power of the investigated chilled water air handling unit AHU. To test the proposed models, actual data are collected from existing HVAC systems. Different fan and … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 15 Mar 2017 · 7,710 accessesView PDFCite
Research ArticleOpen accessIn the abstractKey-Hole Notches in Isostatic Graphite: A Review of Some Recent DataA. Gagani, Relly Victoria V. Petrescu, Florian Ion T. PetrescuFracture of the breakable isostatic graphite is concerned using the experimental and theoretically, the plates containing nicks holes key subject to varying degrees of mixed task. The main purpose of this work is a double one. In the first place, in order to offer a new set of experimental results on fracture of samples of graphite scored, with different values … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 4 · 31 Dec 2016 · 8,012 accessesView PDFCite
Research ArticleOpen accessIn the abstractAmino Acid Sequence of Amylase Type Alpha, MiAmy, from Ok-Rong Mango (Mangifera indica Linn. cv. Ok-Rong)Raksmont Ubonbal, Saijai Posoongnoen, Jureerut Daduang et al.The 594-amino acid residue sequence of α-amylase, MiAmy, from the Ok-rong mango (Mangifera indica Linn. cv. Ok-rong), in the ripening stage, was determined through Reverse Transcription Polymerase Chain Reaction (RT-PCR). Sequence alignments and evolutionary tree analyses revealed its high similarity to plastid α-amylase from many other plants. The sequence was revealed to have four conserved regions with catalytic amino acid … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 3 · 19 Aug 2015 · 7,215 accessesView PDFCite
Research ArticleOpen accessIn the abstractINCORPORATING PRIOR KNOWLEDGE INTO TEMPORAL DIFFERENCE NETWORKSBritton Wolfe, James HarpeDeveloping general purpose algorithms for learning an accurate model of dynamical systems from example traces of the system is still a challenging research problem. Predictive State Representation (PSR) models represent the state of a dynamical system as a set of predictions about future events. Our work focuses on improving Temporal Difference Networks (TD Nets), a general class of predictive state … …Journal of Computer Science, Vol. 10, Issue 11 · 18 Dec 2014 · 7,837 accessesView PDFCite
EditorialOpen accessIn the abstractProblems of Ultra-High Energy Cosmic RaysAnna V. UrysonCosmic rays are energetic particles coming to the Earth from space. They bombard the atmosphere producing cascades of particles that spread over a large area when they reach the ground. Cosmic ray energies vary in the wide band from about 108 eV up to few 1020 eV. It is established that most particles with energies of ~ (108-109) eV come … …Space Science International, Vol. 2, Issue 1 · 6 Dec 2014 · 13,854 accessesView PDFCite