A Newton’s Method for Nonlinear Unconstrained Optimization Problems with Two Variables
Journal Title: International Journal of Science and Research (IJSR) - Year 2013, Vol 2, Issue 1
Abstract
In this paper a modification of the classical Newton Method for solving nonlinear, univariate and unconstrained optimization problems based on the development of the new variants is presented. Moreover it focuses on the applications of the method for various means such as harmonic mean, Arithmetic mean, Geometric mean etc. Furthermore, numerical examples are discussed and the graphs of the results provided using MATLAB.
Authors and Affiliations
Keywords
Related Articles
- EP ID EP334316
- DOI -
- Views 148
- Downloads 0
Taxonomical Studies of Genus Mnium From District Budgam (J&K) India
The genus Mnium Hedw., was reported for the first time from the Southern hemisphere. Plants of this genus are medium sized with fertile erect stem and prostrate sterile stem. In present investigation five species of gen...
Improvement in Wide Area Interconnected Network System Using Synchronized Phasor Measurement Unit
This paper proposes a new adaptive phasor measurement unit (PMU) based protection scheme for wide area interconnected transmission lines network. This method uses positive sequence voltage and current phasors at both end...
Evaluation of Maternal Mortality Rate (MMR) at a High Volume Tertiary Referral Centre: What are we Missing? A Study Spanning 85,404 Live Births Over 9 Years
Maternal mortality is defined internationally , as maternal death rate per 1,00,000 live births. India is among those countries, which has a very high maternal mortality ratio. The current maternal mo...
Hybrid Crossover - Mutation Pair for Genetic Algorithm in Solving Fuzzy Shortest Path Problem - Predominant and Subordinate Ants
The reasons behind the evolution of fuzzy shortest path problem are, finding the path of least cost from source vertex to the destination vertex in the graph G={V,E}. Fuzzy shortest path problem comprises of fuzzy number...
Knowledge Transfer Using Cost Sensitive Online Learning Classification
A real assumption in numerous machine learning area and data mining algorithms is that the future data and training necessary to be in the similar feature space and have the similar distribution. Moreover, in numerous ap...