TY  - CONF
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097546130&doi=10.1109%2fICCI51257.2020.9247733&partnerID=40&md5=354d3023e1c1df9e062d2524f98abc9b
EP  - 222
N2  - In the traditional hypotheses test, hypotheses are crisp. In this paper, we consider the hypotheses test for unknown mean in normal populations with fuzzy data when the standard deviation of the population is known. This paper aims to distinguish various parameter effects on clinical Heart Patients with Two-way Anova, and in this fuzzy test, we will make a fuzzy decision for rejection or acceptance null hypothesis on various parameters of clinical data of Heart Patients with Fuzzy p-value and compared the results with the conventional hypothesis test results. These results will be a benchmark for new patients (same characteristics as the old patients) to treat them in a better way. © 2020 IEEE.
ID  - scholars12632
AV  - none
N1  - cited By 0; Conference of 2020 International Conference on Computational Intelligence, ICCI 2020 ; Conference Date: 8 October 2020 Through 9 October 2020; Conference Code:164916
Y1  - 2020///
TI  - Comparison between Conventional and Fuzzy Hypotheses Test Results for Parameter Treatment Effect for Heart Patients
KW  - Acceptance tests; Intelligent computing; Population statistics
KW  -  Fuzzy decision; Fuzzy hypothesis; Heart patients; Hypothesis tests; Null hypothesis; Parameter effects; Standard deviation; Treatment effects
KW  -  Patient treatment
PB  - Institute of Electrical and Electronics Engineers Inc.
SP  - 217
A1  - Gandikota, N.S.K.
A1  - Hasan, M.H.
A1  - Jaafar, J.
SN  - 9781728154473
ER  -