Analysis of Artificial Neural Network: Architecture, Types, and Forecasting Applications

The artificial neural network reduces humanity and society’s burden to solve complex problems highly efficiently. Artificial networks resemble brain activities based on the acquired training samples used for various applications such as classification, regression, prediction, smart grid, natural language processing, image medical diagnosis, so on. This paper illustrates different architectures, types, merits, demerits, applications. Therefore, this provides valuable information students researchers enrich their knowledge about an research it. also proposed a multilayer-perceptron-neural-network-based solar irradiance forecasting model, improved backpropagation network-based rainfall Elman temperature model. performances of models are analyzed with hidden neurons validated using real-time meteorological data. achieve rigorous results reduced errors considered aid sustainability.