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Introduction: The wind is used for solar energy, and solar energy is used for wind energy. Without each other, electricity cannot be made. Then based on the components, the generator, and the inverter-related electricity can be saved later. Problem formulation: One of the main problems with solar and wind energy is that they make non-concentrated and dilute energy from vast lands. Also, generating the variability and the cost factors is the problem in wind and solar power. To solve this, the installation of solar panels has been enabled for the energy done. The production of the batteries in some of the solutions can be stimulated for the analysis is done. One technique used in this paper is the Artificial neural networks-based expert system and the crop production system. Techniques: Artificial Neural Network-Based Expert Systems are used to predict the plant response in the environment, which is the response to the humidity, light radiation, and temperature. The crop production system is used for performing the plant performance, and the fertilizer follows the resources of the plants and other arrangements related to the plants. Result: The results from the working of the wind and solar energy are equally proportional to the analysis’s 50% -the 50s. Then, the suggested model explains 96.9% of the variation in the dependent variable (plant growth and development) based on the input variables (temperature, CO2, humidity, and light radiation), according to the Coefficient of Determination of 0.969. Overall, the suggested ANN-ES model anticipates plant growth and development based on the input variables and is regarded as dependable for this purpose.
Kumar et al. (Mon,) studied this question.