5
(3)
TABLE 1.The cost h was configure with
(VY - 0 : 01 + 0 : 950%-1 it set high at the stant,
then decreased with cach reputation, mentioned here with h.
Reputation was then performed for optimization. The global
extreme rates E obtained by this algorithm are considered
the optimal parameters for the SBGC-LSTM model. to avoid habit of usage smoking. The proposed method able
to control the discase by taking these values and minimise the
severity of disease using fuzzy rule-based system. The noral
and abnormal values are provided below table 1. The table
also shows its consequences. D. FUZZY LOGIC AND FUZZY RULES
In this phase, we discuss the use of fuzzy rulcs and the
proposed multi-ncural network in the classilication process in
detail. First, it explores fuzzy rules and justifications. Fuzzy
logic, which contains a varicty of data types, is used to handle
the ambiguity of healthcare records. In fuzzy logic, language
terms are utilized to help dccide between the various types
of records. The fuzzy rules are created by using the language
words and distances from 0 to 1 for cach term. In this study. trapczoidal fuzzy mcmbership was used. The malc paticnt
described the severity of his symptoms using the language
temms in Table 1. ""Action-2." Here, the pain level of the supra-public
is thought of as "Action-l." and ""Action-3"
because the scriousness of the experience is not known. In this
study, five different methods of identifying a condition based
on the amount of pain were examined (29]. Furthermore, the
results for cach object are not the same as the results for
any other object. The fuzzy rules are fine-tuned by using
fuzzification on the input factors. The prompted fuzzy rules
can be used to determine the fuzzy sct of the output. 3) chd prevention system through diabetes DiSEASe
To maintain.Different parameter normal/ abnormal values and some effects
in abnormal conditions.-
Ba
bra +aM
(9)
SNo Parameter Normal Abnormal Complications
Glucose
90-110
140-200
Damage normal
mg/di mg/dl
functionality of
organs
Cholesterol 140
150 mg/dl l increase
the
mg/ll
CHD
risk
percentage
30-35
20-25
BMI
Afiects the daily
kg/m2 kg/m2
activities
Blood
120/80 140190
Feill
abnormal
condition
Pressure mmHg mmHg
like
and
dizziness
stroke
Smoking
Falure of lugs
pac/week pac/week and and its its normal
functionality
i= l; 2: ....n. d = 1, 2.the model having sell-repon
to estimate a probability of disease with outcome variables as
a binary estimated in cq (25 and 26).The value of migration is expressed as #, which was obtained
from the antennae of Eurygaster.were assigned.Subsequently.... . 26).