Implementation of Intelligent Elderly Care System Based on Cloud Platform and NNB Algorithm

This paper discusses how to apply advanced machine learning technology and cloud platform to the smart elderly care service system, aiming to provide more accurate and personalized service recommendations for the elderly. With the acceleration of the aging process of society, smart elderly care has become one of the key ways to solve the aging problem, and efficient service matching for the diversified and personalized needs of the elderly is particularly critical. In this study, a set of service demand prediction model based on artificial neural network (ANN) was first constructed. Through in-depth mining of multidimensional data of elderly users, a detailed portrait of users was formed, so as to accurately predict their potential service demand. However, a single ANN model may be limited by overfitting or underfitting when dealing with complex and nonlinear relationships. Therefore, AdaBoost algorithm is introduced to improve the overall model performance and is deployed on the cloud platform. A powerful and efficient Neural Network Boost Model (NNB) for intelligent decision system is constructed. As an ensemble learning method, AdaBoost can combine multiple weak learners into a strong learner, strengthen the learning ability of hard-to-learn samples by dynamically adjusting sample weights, and effectively reduce overfitting. Through seamless docking with cloud computing platform, NNB model not only makes full use of elastic computing resources of cloud services to conduct large-scale parallel training, greatly shortening model training time, but also realizes real-time processing and analysis of massive data. In the design process of personalized recommendation system for intelligent elderly care service, AdaBoost algorithm not only optimizes the training process of neural network model, but also improves the accuracy and stability of recommendation results. In summary, the implementation of the intelligent elderly care system based on cloud platform and NNB proposed in this paper effectively promotes the scientific and accurate intelligent elderly care service by deeply mining user needs, optimizing model performance and intelligent scheduling service resources, and provides innovative solutions and technical support for addressing the challenges of population aging.