Optimal Crop Selection Using Gravitational Search Algorithm

Abstract

For the economic growth of the crop, the optimal utilization of soil is found to be an open area of research. An efficient utilization includes various advantages such as watershed insurance, expanded biodiversity, and reduction of provincial destitution. Generally, soils present synthetic confinements for crop improvement. Therefore, in this paper, a novel diversified crop model is proposed to predict the suitable soil for good production of the crop. The proposed model utilizes a quantum value-based gravitational search algorithm (GSA) to optimize the best solution. Various features of soil are required to be investigated before crop selection. These features are refined further by applying quantum optimization. The crop selection based upon the soil requirement does not require any additional fertilizers which will reduce the production cost. Thus, the proposed model can select the optimal crop according to the soil components using the gravitational search algorithm. Therefore, the gravitational search algorithm is applied to the quantum values obtained from the crop and soil dataset. Extensive experiments show that the proposed model achieves an optimal selection of crops.

Application of big data optimal selection algorithm in project bidding scheme selection

“…It takes 17.84 s to use the optimal bidding scheme selection algorithm based on OSCK; It takes 22.21s to use the optimal bidding scheme selection algorithm based on intuitionistic fuzzy sets. The experimental results show that it takes a short time to select the optimal bidding scheme by using this algorithm, and it has a certain speed advantage [7][8].…”

Adolescent Identity Search Algorithm Based on Fast Search and Balance Optimization for Numerical and Engineering Design Problems

“…end if (20) end if (21) Boundary constraint process; (22) Apply the updating mechanism: (23) for i � 1 to Ndo (24) iffit…”

“…Meta-heuristic algorithms are based on physics or chemistry and formed by observing some physical or chemical phenomena and using their laws including gravity, potential energy, ecosystem, and motion. Simulated annealing (SA) [ 20 ], gravitational search algorithm (GSA) [ 21 ], noisy intermediate-scale quantum algorithms (NISQ) [ 22 ], chemical reaction optimization (CRO) [ 23 ], charged system search (CSS) [ 24 ], black hole (BH) [ 25 ], ions motion algorithm [ 26 ], multiverse optimizer (MVO) [ 27 ] and vortex search (VS) [ 26 ] are some optimizers in this category.…”