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
- J. M. Aslam, K. M. Kumar, Enhancing security of cloud using static IP techniques , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- A. Anand, A. Nisha Jebaseeli, A comparative analysis of virtual machines and containers using queuing models , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Subin M. Varghese, K. Aravinthan, A robust finger detection based sign language recognition using pattern recognition techniques , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- O. Devipriya, K. Kungumaraj, Enhancing cloud efficiency: an intelligent virtual machine selection and migration approach for VM consolidation , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- R Prabhu, S Sathya, P Umaeswari, K Saranya, Lung cancer disease identification using hybrid models , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- D. Padma Prabha, C. Victoria Priscilla, A combined framework based on LSTM autoencoder and XGBoost with adaptive threshold classification for credit card fraud detection , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Manikannan Palanivel, Alaudeen A, Pandiyan K. S, Sivaprakasam P, Hybrid fuzzy and fire fly algorithm-based MPPT controller for PV system using super lift boost converter , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Jhankar Moolchandani, Kulvinder Singh, English language analysis using pattern recognition and machine learning , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Punithavathy E, N. Priya, A resilience framework for fault-tolerance in cloud-based microservice applications , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- C. Agilan, Lakshna Arun, Optimization-based clustering feature extraction approach for human emotion recognition , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
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