GAS, a concept on modeling species in genetic algorithms
Artificial Intelligence
Swarm intelligence
A condensed polynomial neural network for classification using swarm intelligence
Applied Soft Computing
A Case-Driven Ambient Intelligence System for Elderly in-Home Assistance Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Information Technology in Biomedicine
Detection of Abnormal Living Patterns for Elderly Living Alone Using Support Vector Data Description
IEEE Transactions on Information Technology in Biomedicine
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This paper proposes a machine learning based prognosis for rehabilitating the COPD patients to be monitored from home in real time. Wearable sensor Technology (WST) is utilized to collect the physiological status of the pulmonary patient from home dynamically and communicated to the healthcare centre. The proposed approach applies a comprehensive predictive model employing a time series forecasting using condensed polynomial neural network with swarm intelligence. Discrete particle swarm optimization (DPSO) filters out the relevant neurons and continuous particle swarm optimization (CPSO) reduces the computational overheads. The time series prediction is further strengthened by using multimodal genetic algorithm. Control measures such as sensitivity, specificity and reliability are applied meticulously to validate the predicted state of the patient.