ABSTRACT
This chapter describes how Computational Intelligence in the agricultural domain is constantly increasing to innovate new approaches for improving and protecting crop fields. Computational intelligence can overcome many factors like climate change, population growth, uncertainty in crop production, inadequacy in crop maintenance, incomplete food security, etc., which is not adequate for the proper nourishment of the crops. Implementation of the four main techniques of computational intelligence will set the new beginning of an intelligent agriculture system, by increasing crop productivity and crop quality. The first technique is fuzzy sets in agriculture, which can manage the uncertainty of crops and provide solutions for the issues like land degradation, unpredictable climate change, soil erosion, etc., helping the farmer to take the correct decision for their crop cultivation. The second is using an artificial neural network (ANN), a very powerful tool for modelling and prediction of how to improve the efficiency of the crop. Using ANN, the suitable crop is predicted based on various parameters of soil and atmosphere like pH, nitrogen, potassium, depth, rainfall, temperature, phosphate, etc. Third, this technique is a combination of evolutionary computing such as Genetic algorithms and the agricultural system. Fourth, how the swarm intelligence in the annual crop planning provides the optimal solution for the various competing crop required to be grown on the agricultural land by its various metaheuristics like cuckoo search (CS), Glow-worm swarm optimization (GSO), and firefly algorithm (FA).
