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    Prediction of Parkinson’s Disease Using Improved Radial Basis Function Neural Network

    Rajalakshmi Shenbaga Moorthy1,*, P. Pabitha2

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3101-3119, 2021, DOI:10.32604/cmc.2021.016489

    Abstract Parkinson’s disease is a neurogenerative disorder and it is difficult to diagnose as no therapies may slow down its progression. This paper contributes a novel analytic system for Parkinson’s Disease Prediction mechanism using Improved Radial Basis Function Neural Network (IRBFNN). Particle swarm optimization (PSO) with K-means is used to find the hidden neuron’s centers to improve the accuracy of IRBFNN. The performance of RBFNN is seriously affected by the centers of hidden neurons. Conventionally K-means was used to find the centers of hidden neurons. The problem of sensitiveness to the random initial centroid in K-means degrades the performance of RBFNN.… More >

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