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Evolutionary Intelligence

Erschienen in:

10.11.2018 | Special Issue

Automated soil prediction using bag-of-features and chaotic spider monkey optimization algorithm

verfasst von: Sandeep Kumar, Basudev Sharma, Vivek Kumar Sharma, Ramesh C. Poonia

Erschienen in: Evolutionary Intelligence | Ausgabe 2/2021

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Abstract

A proper soil prediction is one of the most important parameters to decide the suitable crop which is generally performed manually by the farmers. Therefore, the efficiency of the farmers may be increased by producing an automated tools for soil prediction. This paper presents an automated system for categorization of the soil datasets into respective categories using images of the soils which can further be used for the decision of crops. For the same, a novel Bag-of-words and chaotic spider monkey optimization based method has been proposed which is used to classify the soil images into its respective categories. The novel chaotic spider monkey optimization algorithm shows desirable convergence and improved global search ability over standard benchmark functions. Hence, it has been used to cluster the keypoints in Bag-of-words method for soil prediction. The experimental outcomes illustrate that the anticipated methods effectively classify the soil in comparison to other meta-heuristic based methods.

Vorheriger Artikel An application of artificial neural network classifier to analyze the behavioral traits of smallholder farmers in Kenya

Nächster Artikel Particle swarm optimization with adaptive inertia weight based on cumulative binomial probability

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Titel: Automated soil prediction using bag-of-features and chaotic spider monkey optimization algorithm
verfasst von: Sandeep Kumar
Basudev Sharma
Vivek Kumar Sharma
Ramesh C. Poonia
Publikationsdatum: 10.11.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Evolutionary Intelligence / Ausgabe 2/2021
Print ISSN: 1864-5909
Elektronische ISSN: 1864-5917
DOI: https://doi.org/10.1007/s12065-018-0186-9

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