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90 results for “stochastic model”
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Research ArticleOpen accessIn the abstractEfficient Implementation of Stochastic Computing Based Deep Neural Network on Low Cost Hardware with Saturation ArithmeticSunny Bodiwala, Nirali NanavatiThis study presents an efficient and rapid implementation of Stochastic Computing (SC) based Deep Neural Network (DNN) on a low-cost hardware platform. The proposed technique uses bipolar signal encoding in stochastic computing which relatively gives low hardware footprint compared to binary computing. Thereinafter, stochastic max function is presented and subsequently used to approximate the hyperbolic tangent activation function in SC. … …Journal of Computer Science, Vol. 16, Issue 11 · 17 Nov 2020 · 6,875 accessesView PDFCite
Research ArticleOpen accessIn the abstractDrawdown and Drawup of Bi-Directional Grid Constrained Stochastic ProcessesAldo Taranto, Shahjahan KhanThe Grid Trading Problem (GTP) of mathematical finance, used in portfolio loss minimization, generalized dynamic hedging and algorithmic trading, is researched by examining the impact of the drawdown and drawup of discrete random walks and of Itô diffusions on the Bi-Directional Grid Constrained (BGC) stochastic process for profit Pt and equity Et over time. A comprehensive Discrete Difference Equation (DDE) … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 14 Sep 2020 · 9,153 accessesView PDFCite
Research ArticleOpen accessIn the abstractSupervised Machine Learning Model-Based Approach for Performance Prediction of StudentsAbdul Razaque, Abrar M. AlajlanPredicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine … …Journal of Computer Science, Vol. 16, Issue 8 · 28 Aug 2020 · 7,082 accessesView PDFCite
Research ArticleOpen accessIn the abstractp ≠ np: The Set of Deterministic Problems that are Solvable in Polynomial Time is Unequal to the Set of Non-Deterministic Problems that are Solvable in Polynomial TimeAndres BoldoriThis study constructs a solution to the “p vs. np” problem using complexity theory. We show through counterexamples that p ≠ np and formalize the two sets using stochastic, probabilistic and non-deterministic modeling. While the well-known sets “pspace” and “npspace”, analyzing the storage of a device, can be claimed to be equal, p and np differ and are exclusively defined … …Journal of Computer Science, Vol. 20, Issue 10 · 8 Aug 2024 · 7,106 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Review of the Recent Advances Made in the Black-Scholes Models and Respective Solutions MethodsYasir Hamad Al Saedi, Gurudeo Anand TularamThe Black-Scholes model has been a major advance in finance over a period of time; this paper examines this model in some detail, in terms of the latest developments in both analytical and numerical solutions. The paper initially briefly examines historical aspects but quickly moves to a critical analysis of the works in the applications, solutions and implications for the … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 8 Jan 2018 · 8,621 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparing the Empirical and the Theoretical Probability Density of Return in which Variance Obeying Ornstein-Uhlenbeck Process at Indonesian Stock Exchange IDXDwi Satya Palupi, Eduardus Tandelilin, Arief Hermanto, Muhammad Farchani RosyidThe distribution of the probability density of a return index with stochastic volatility has been calculated. Here the stock index is assumed to follow geometric Brownian motion, while the variance is assumed to obey Ornstein-Uhlenbeck process as in Heston model. The distribution of the probability density of the return which is obtained by solving the Fokker-Planck equation of two dimensional … …American Journal of Applied Sciences, Vol. 14, Issue 9 · 17 May 2017 · 7,625 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Optimization of Physics Simulations Through Genetic AlgorithmsOksana Shadura, Federico Carminati, Anatoliy PetrenkoThe GeantV R&D approach is revisiting the standard particle transport simulation approach to be able to benefit from “Single Instruction, Multiple Data” (SIMD) computational architectures or extremely parallel systems like coprocessors and GPUs. The goal of this work is to develop a mechanism for optimizing the programs used for High-Energy Physics (HEP) particle transport simulations using a “black-box” optimization approach. … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 8,091 accessesView PDFCite
Research ArticleOpen accessIn the abstractParametrical Tuning of Twisting GeneratorsAleksei F. Deon, Yulian A. MenyaevGenerators of uniformly distributed random numbers are broadly applied in simulations of stochastic processes that rely on normal and other distributions. In a point of fact, the uniform random numbers are actively used for applications that range from, modeling different phenomena such as theoretical mathematics and technical designing, to evidence-based medicine. This paper proposes a novel approach which consists of … …Journal of Computer Science, Vol. 12, Issue 8 · 7 Oct 2016 · 11,836 accessesView PDFCite