Achieving Neuroplasticity in Artificial Neural Networks through Smart Cities

摘要: Through the Internet of things (IoT), as promoted by smart cities, there is an emergence big data accentuating use artificial intelligence through various components urban planning, management, and design. One such system that neural networks (ANNs), a component machine learning boasts similitude with brain neurological its functioning. However, development ANN was done in singular fashion, whereby processes are rendered sequence unidimensional perspective, contrasting functions to which similitude, particular concept neuroplasticity encourages unique complex interactions self-learning thereby encouraging more inclusive render coherence. This paper takes inspiration from Christopher Alexander’s Nature Order dwells complexity theory; it also proposes theoretical model how can be same plastic properties multidimensional interactivity context cities emerging networks. By doing so, this caters creation stronger, richer, patterns support “wholeness” connection overlapping aimed toward engineers interdisciplinary interest looking at creating intricate models, planners theorists working on contemporary cities.