Convergence of the Method of False Position
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2022.13.2.13Keywords:
Method of false position, rate of convergence, percentage error, trend, algorithm, accuracy, 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.
The method of false position has been applied to calculate the fourth roots of the natural numbers from 1 to 30 in the interval [0, 3] with the stopping tolerance of 0.00001 using C++ computer program. The minimum error 0.000000029282 and minimum percentage error 0.000001251170 have been obtained in the determination of fourth roots of 30. The maximum error 0.000002324581 and maximum percentage error 0.000232458100 have been obtained in the determination of fourth roots of 1. The average value of the error is 0.000000392037 and the average value of percentage error is 0.000027500512. Minimum, maximum and average values the numerical rate of convergence have been found to be 0.239808153477, 1.851851851852 and 1.197514787730 respectively.Abstract
How to Cite
Downloads
Similar Articles
- M. Prabhu, A. Chandrabose, Optimization based energy aware scheduling in wireless sensor networks , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Olivia C. Gold, Jayasimman Lawrence, Enhanced LSTM for heart disease prediction in IoT-enabled smart healthcare systems , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Somalee Mahapatra, Manoranjan Dash, Subhashis Mohanty, Adoption of artificial intelligence and the internet of things in dental biomedical waste management , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Viji Parthasarathy, Manikandasaran S S, Feature Selection Techniques for IOT Crop Yield Prediction Using Smart Farming Sensor Data , The Scientific Temper: Vol. 17 No. 01 (2026): The Scientific Temper
- S. Mohamed Iliyas, M. Mohamed Surputheen, A.R. Mohamed Shanavas, Enhanced Block Chain Financial Transaction Security Using Chain Link Smart Agreement based Secure Elliptic Curve Cryptography , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- Rekha R., P. Meenakshi Sundaram, Trust aware clustering approach for the detection of malicious nodes in the WSN , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Thangatharani T, M. Subalakshmi, Development of an adaptive machine learning framework for real-time anomaly detection in cybersecurity , The Scientific Temper: Vol. 16 No. 08 (2025): 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
- Temesgen Asfaw, Customer churn prediction using machine-learning techniques in the case of commercial bank of Ethiopia , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Deepika S, Jaisankar N, A novel approach to heart disease classification using echocardiogram videos with transfer learning architecture and MVCNN integration , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
<< < 8 9 10 11 12 13 14 15 16 17 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Lavkush Pandey, Trilokinath, Convergence of Bisection Method , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper

