Cognitive-inspired computational systems play a crucial role in designing intelligent health monitoring systems which help both patients and hospitals.It also helps in early and consistent decision-making for various ...Cognitive-inspired computational systems play a crucial role in designing intelligent health monitoring systems which help both patients and hospitals.It also helps in early and consistent decision-making for various health issues including human psychological health.Water fountains built in parks and public spaces are used as decorative instruments which not only give appealing visuals but also provide a relaxing environment to the visitors.These natural sounds have a direct effect on the psychological health of visitors.Very few research works are reported on developing the relationship between water sounds and their corresponding psychological impact.This assessment needs trained manpower and a lot of experimental time which is costly and may not be always available.In this paper,to access the from the pleasantness from human health-friendly water fountain sounds,a perceptually weighted functional link artificial neural network(P-FLANN)model is developed.To reduce the computational complexity of training and for faster convergence,swam intelligence-based optimization algorithm is used for updating the weights.It is observed from the comparative simulation results that the proposed P-FLANN model can effectively perform prediction tasks which is not only cost-effective but also 95%accurate and can play a crucial role in designing human health-friendly water fountains in smart cities.展开更多
文摘Cognitive-inspired computational systems play a crucial role in designing intelligent health monitoring systems which help both patients and hospitals.It also helps in early and consistent decision-making for various health issues including human psychological health.Water fountains built in parks and public spaces are used as decorative instruments which not only give appealing visuals but also provide a relaxing environment to the visitors.These natural sounds have a direct effect on the psychological health of visitors.Very few research works are reported on developing the relationship between water sounds and their corresponding psychological impact.This assessment needs trained manpower and a lot of experimental time which is costly and may not be always available.In this paper,to access the from the pleasantness from human health-friendly water fountain sounds,a perceptually weighted functional link artificial neural network(P-FLANN)model is developed.To reduce the computational complexity of training and for faster convergence,swam intelligence-based optimization algorithm is used for updating the weights.It is observed from the comparative simulation results that the proposed P-FLANN model can effectively perform prediction tasks which is not only cost-effective but also 95%accurate and can play a crucial role in designing human health-friendly water fountains in smart cities.
