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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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Published Paper Details:
An Innovative Method for Classifying Iris Plants Using an Artificial Neural Network and the Particle Swarm Optimization Algorithm
Authors
Mr. DARA MURALI KRISHNA,Mr. ALAMANDA GOPI CHAITANYA,Mr. BODDA ARYA,Mr. KATIPAMU DURGA SAI RAM,Mr. KONDAKA TARUN SAI , Mr. SINGUPURAPU UDAY KIRAN
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Keywords
Biota, Fauna, Classification, Artificial Neural Network, Plant Species, Predicate Logic
Abstract
The study and analysis of biological data using information technology applications and computer technology techniques is known as bioinformatics. Bioinformatics represents biological data in a more effective and efficient way so that non-biologists can interpret it. A species is one of the fundamental components of biological classification and a taxonomic rank in biology. The biggest collection of organisms in which two individuals are capable of producing fertile offspring, often through sexual reproduction, is referred to as a species. The term "fauna" is equivalent to "flora" for plants, which refers to a stage of the plant life cycle that takes place in a certain place or period of time. Biota is the general term for flora, faun, and other life forms like fungus. In this research, our major goal is to identify the plant species using the IRIS dataset. We primarily employ the performance of the Artificial Neural Network Algorithm (ANN) in order to identify the plant species from a collection of IRIS plants. First, we focus on categorizing IRIS plants according to the size and type of flower leaves. Predicate logic is mostly used to accomplish this utilising a concept called neural network exploitation. We are aware that ANN is frequently used to solve pattern classification issues and produce outcomes that are optimized. In order to evaluate the taught exploitation back propagation learning algorithmic programme, we constructed a multilayer feed-forward network mechanism in this paper. We ultimately came to the conclusion that the proposed method, Particle Swam Optimization (PSO), is the best choice for determining the species name of a plant using the width and height of the sepal and petal of a plant after conducting several experiments on the given model. We have selected a set of petal and sepal width and length values from the IRIS data collection for this purpose. A new notion, such as the type of soil needed to fertilize the plant based on species and the PH value detected for the current paper, has also been added as an expansion.
IJCRT's Publication Details
Unique Identification Number - IJCRT2302680
Paper ID - 242096
Author type - Indian Author
Page Number(s) - f482-f491
Pubished in - Volume 11 | Issue 2 | February 2023
DOI (Digital Object Identifier) -
No Of Downloads - 114
Author Country - India, -, -, -, -, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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Mr. DARA MURALI KRISHNA,Mr. ALAMANDA GOPI CHAITANYA,Mr. BODDA ARYA,Mr. KATIPAMU DURGA SAI RAM,Mr. KONDAKA TARUN SAI , Mr. SINGUPURAPU UDAY KIRAN, "An Innovative Method for Classifying Iris Plants Using an Artificial Neural Network and the Particle Swarm Optimization Algorithm", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 2, pp.f482-f491, February 2023, Available at :http://www.ijcrt.org/papers/IJCRT2302680.pdf
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