FORECASTING AND OPTIMIZATION OF THE IMPACT OF WEATHER CONDITIONS ON BLOOD PRESSURE-RELATED DISEASES USING THE MLP MODEL
Keywords:
MLP (Multilayer Perceptron), yurak qon bosimi kasalliklari,ob-havo sharoitlari, chuqur o‘rganish (deep learning), yashirin qatlamlar, epoxlar, bashorat qilish, profilaktika choralar, neyron tarmoq.Abstract
This article describes the use of a Multilayer Perceptron (MLP) neural network to study and predict the impact of weather conditions on blood pressure-related diseases. It has been determined that weather elements such as temperature, atmospheric pressure, humidity, wind speed, and geomagnetic storms significantly influence blood pressure-related diseases. During the study, the effectiveness of the MLP model was enhanced by optimizing parameters such as the number of hidden layers and the number of epochs. Experimental results demonstrated that a model with 2 hidden layers and 100 epochs achieved the highest accuracy and reliable predictions.
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Copyright (c) 2024 Giyos Pulatov, Aleksandr Kabildjanov, Gulxayo Pulatova
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