Convergence of Bisection Method
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2022.13.2.14Keywords:
Bisection method, convergence, stopping tolerance, error, percentage error, computer program, iterations.Dimensions Badge
Issue
Section
License
Copyright (c) 2022 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Fourth roots of the natural numbers from 1 to 30 have been calculated by Bisection method in the interval [0, 3] using stopping tolerance 0f 0.00001. Calculated roots have been compared with the actual values of roots to obtain error and percentage error in the calculated roots. Numerical rate of convergence has also been calculated in the determination of each fourthroot. The highest numerical rate of convergence of Bisection method has been observed in the calculation of fourth root of 2 and is equal to 1.754385964912. The lowest numerical rate of convergence of Bisection method has been observed in the calculation of fourth roots of 1, 3, -8, 10, 12 and is equal to 1.333333333333. Average error, average percentage error and average numerical rate of convergence of Bisection method have been found to be 0.000000062635, 0.000003048055 and 1.458082183940 respectivelyAbstract
How to Cite
Downloads
Similar Articles
- Neeraj ., Anita Singhrova, Quantum Key Distribution-based Techniques in IoT , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- L. Amudavalli, K. Muthuramalingam, Energy-efficient location-based routing protocol for wireless sensor networks using teaching-learning soccer league optimization (TLSLO) , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- R.R. Jenifer, V.S.J. Prakash, Detecting denial of sleep attacks by analysis of wireless sensor networks and the Internet of Things , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- N. Saranya, M. Kalpana Devi, A. Mythili, Summia P. H, Data science and machine learning methods for detecting credit card fraud , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Sahaya Jenitha A, Sinthu J. Prakash, A general stochastic model to handle deduplication challenges using hidden Markov model in big data analytics , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- A. R. Jasmine Begum, M. Parveen, S. Latha, IoT based home automation with energy management , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Aruljothi Rajasekaran, Jemima Priyadarsini R., ECDS: Enhanced Cloud Data Security Technique to Protect Data Being Stored in Cloud Infrastructure , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- A. Anand, A. Nisha Jebaseeli, AI-driven real-time performance optimization and comparison of virtual machines and containers in cloud environments , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- M. Iniyan, A. Banumathi, The WBANs: Steps towards a comprehensive analysis of wireless body area networks , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- M. Rajalakshmi, V. Sulochana, Enhancing deep learning model performance in air quality classification through probabilistic hyperparameter tuning with tree-structured Parzen estimators , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
<< < 9 10 11 12 13 14 15 16 17 18 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Lavkush Pandey, Trilokinath, Convergence of the Method of False Position , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper