Cause Effect Analysis of Ecological Pollutants on Internal Physique of Human Subjects Using Radial Recurrent Neural Network Approach

Globally, ecosystems are changing at an unprecedented rate. Ecosystem management include natural resources and the biophysical environment, but it also requires consideration of all anthropogenic aspects, including social, economic, and cultural factors. Environmental factors are thought to be respo...

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Veröffentlicht in:Journal of physics. Conference series 2022-08, Vol.2327 (1), p.12066
Hauptverfasser: Pimpale, Y, Gupta, S, Kanday, R
Format: Artikel
Sprache:eng
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Zusammenfassung:Globally, ecosystems are changing at an unprecedented rate. Ecosystem management include natural resources and the biophysical environment, but it also requires consideration of all anthropogenic aspects, including social, economic, and cultural factors. Environmental factors are thought to be responsible for almost half of the worldwide burden of disease. Ecosystem changes are increasingly recognized as having an impact on human health and playing an important part in the onset and re-emergence of an expanding variety of diseases. Ecological and environmental Imbalances negatively affect on human health, food security and global economic geopolitical stability. In this study, a cohort-based data set of Ecological pollutants and Physiological signals such as ECG and anthropogenic data of human subjects were extracted from Maharashtra. A hazard ratio based on neural networks was developed and found to be deplorable in both the unhealthy and healthy categories of human individuals. This research is crucial in shedding insight on the influence of interactions between natural and anthropogenic variables on human health. Such initiatives might contribute to a better knowledge of the human health consequences of accelerated environmental change, as well as better decision-making in the fields of environmental conservation, public health policy, and new management framework designs.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2327/1/012066