Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Numerical analysis concerns the development of algorithms for solving various types of problems of mathematics; it is a vast-ranging field having deep interaction with computer science, mathematics, engineering, and the sciences. Numerical analysis mainly consists of Numerical Integration, Numerical Differentiation and finding Roots numerically. In this paper we develop an algorithm combination of Numerical Integration (Trapezoidal rule, Simpson’s 𝟏𝟏/𝟑𝟑 rule, Simpson’s 𝟑𝟑/𝟖𝟖 rule and Weddle’s rule.), Numerical Differentiation (Euler, modified Euler and Runge-Kutta second and fourth order) and finding Roots (Bisection method and False position method) numerically.
Nizhum Rahman. 2015. \u201cAn Algorithm for Integration, Differentiation and Finding Root Numerically\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 14 (GJRE Volume 14 Issue J7): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Total Score: 103
Country: Unknown
Subject: Global Journal of Research in Engineering - J: General Engineering
Authors: Nizhum Rahman, Aminul Islam, B. K. Datta (PhD/Dr. count: 0)
View Count (all-time): 200
Total Views (Real + Logic): 4574
Total Downloads (simulated): 2111
Publish Date: 2015 12, Thu
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Neural Networks and Rules-based Systems used to Find Rational and
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Numerical analysis concerns the development of algorithms for solving various types of problems of mathematics; it is a vast-ranging field having deep interaction with computer science, mathematics, engineering, and the sciences. Numerical analysis mainly consists of Numerical Integration, Numerical Differentiation and finding Roots numerically. In this paper we develop an algorithm combination of Numerical Integration (Trapezoidal rule, Simpson’s 𝟏𝟏/𝟑𝟑 rule, Simpson’s 𝟑𝟑/𝟖𝟖 rule and Weddle’s rule.), Numerical Differentiation (Euler, modified Euler and Runge-Kutta second and fourth order) and finding Roots (Bisection method and False position method) numerically.
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