Improved Feature Selection Method for the Identification of Soil Images Using Oscillating Spider Monkey Optimization
subject: Feature selection; Perturbation rate; smart agriculture; Soil prediction; Spider monkey optimization
description: Precision agriculture is the process that uses information and communication technology for farming and cultivation to improve overall productivity, efficient utilization of resources. Soil prediction is one of the primary phases in precision agriculture, resulting in good quality crops. In general, farmers perform the soil prediction manually. However, the efficiency of soil prediction may be enhanced by using current digital technologies. One effective way to automate soil prediction is image processing techniques in which soil images may be analyzed to determine the soil. This paper presents an efficient image analysis technique to predict the soil. For the same, a robust feature selection technique has been incorporated in the image analysis of soil images. The developed feature selection technique uses a new oscillating spider monkey optimization algorithm (OSMO) for the selection of features that are relevant and non-redundant. The new oscillating spider monkey optimization algorithm increases precision and convergence behavior by using an oscillating perturbation rate. A set of standard benchmark functions was deployed to visualize the performance of the new optimization technique (OSMO), and results were compared based on mean and standard deviation. Furthermore, the soil prediction approach is validated on a soil dataset, having seven categories. The proposed feature selection method selects the 41% relevant features, which provide the highest accuracy of 82.25% with 2.85% increase. 2013 IEEE.
creator: Agarwal R.; Shekhawat N.S.; Kumar S.; Nayyar A.; Qureshi B.
source: IEEE Access, Vol-9, pp. 167128-167139.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2021-01-01
rights: All Open Access; Gold Open Access
relation: ISSN: 21693536
format: Online
language: English
type: Article
coverage: Agarwal R., Department of Computer Science and Engineering, Engineering College Bikaner, Bikaner, 334004, India; Shekhawat N.S., Department of Computer Science and Engineering, Engineering College Bikaner, Bikaner, 334004, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Bengaluru, Karnataka, 560074, India; Nayyar A., Graduate School, Duy Tan University, Da Nang, 550000, Viet Nam, Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Viet Nam; Qureshi B., Department of Computer Science, Prince Sultan University, Riyadh, 11586, Saudi Arabia