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Agriculture Data Feature Extraction Using Sequential Pattern Mining and Random Forest (SPM-RF) Data Mining Method
Feature extraction assumes a critical part in analyzing agricultural datasets and acquiring experiences for decision-making. In this paper we propose a methodology that consolidates Sequential Pattern Mining (SPM) and Random Forest (RF) techniques for…
Analysis and Survey on Fruit Disease Identification in Agriculture Using Data Mining
Rathamani, M.; Kanjana Devi, P.
Diseases in fruit cause wrecking issue in economic misfortunes and production in agricultural industry around the world. Disease management by physically is a challenging task. A large portion of the diseases are seen on…
Crop Yield Prediction Using With the Simulated Annealing Convolutional Neural Networks (SACNNS) Optimization Algorithm
This paper introduces an innovative approach for precise crop yield prediction in Tamil Nadu, India, a region with diverse agricultural conditions. The Simulated Annealing Convolutional Neural Networks (SACNNs) optimization algorithm is employed to enhance…
Data Preprocessing Using Enhanced Principal Component Analysis (EPCA) for Agricultural Datasets
Data pre-processing is considered as the core stage in core and data mining. Standardization, discretization, and dimensionality decrease are notable strategies in data pre-processing. In this paper proposed Enhanced Principal component Analysis (EPCA) the…
Educational Data Mining
Data mining methods and techniques are applied to educationally related data as part of the burgeoning field known as educational data mining (EDM). Education data mining is the name of an emerging multidisciplinary research…
Enhanced Back Propagation Neural Network for Fruit Disease Prediction and Classification
Rathamani, M.; Kanjana Devi, P.
Data mining assumes an essential part in the dynamic cycle in numerous application territories. Information mining is essential for data handling and the executives. Plant sicknesses bargain efficiency which impacts public activity and economy…
Fruit Disease Identification Using Feature Extraction and Data Mining
Rathamani, M.; Kanjana Devi, P.
Agriculture is one of the fields which produce data continually ensuring each of the four characteristics with fantastic development. There are various difficulties in preparing farming records which manages assortment of organized and unstructured…
Fruit Grade Classification Using Improved Convolutional Neural Network
Rathamani, M.; Kanjana Devi, P.
Machine learning is the recent research topic which attracts the attention of researchers worldwide. Automation of fruit grading and fruit detection system lays a vital role in field of agriculture and also in the…
Fruit Grade Verification Using Image Processing Techniques
Rathamani, M.; Kanjana Devi, P.
Most of the Indian population depend on agriculture. GDP contribution is high by agricultural sector when compared to the other sectors. The agricultural products serve the purpose of economic contribution. The products that are…
Hybrid Artificial Neural Network and Case Based Reasoning (Hanncbr) Classification Model for Classification of Agriculture Data in Different Area
Lately the erratic weather conditions changes have prompted different polemics. The utilization of cropping designs that have been done from generation to generation regardless of environmental change and the environment is the reason. The…
Image Segmentation K-Means Clustering Algorithm for Fruit Disease Detection Image Processing
Rathamani, M.; Kanjana Devi, P.
Fruit diseases are always considered as a remarkable issue in the cultivating business carried out across the globe. This arises the need for manual checking framework. In this way, agriculturists require the manual analysis…
Implementation of Different Approaches Using Enhanced Algorithms for Fruit Disease Identification
Rathamani, M.; Kanjana Devi, P.
The utilization of computers to investigate images has numerous possible applications for mechanized agricultural tasks. However, the fluctuation of the agricultural objects makes it hard to adjust the current industrial algorithms to the agricultural…
Prediction and Classification of Textural Properties on Fruits During Ripening Using Convolutional Neural Network
Rathamani, M.; Kanjana Devi, P.
Non-destructive quality detection and automatic grading are significant in fruit industry. The customary way separates fruits into four level ripening stages dependent on color. The assurance of the ripeness condition of fruits is a…
A Review on Datamining in Agriculture
In this paper the makers present irrefutably the most used data mining strategies in the field of agriculture. A bit of these strategies, for example, the k-means, the k nearest neighbor, artificial neural networks…
A Survey on Datamining in Agriculture
Agriculture assumes an essential part in the life of an economy. It is the backbone for creating nations like India as over 70% of populace relies upon agriculture. To expand crop production numerous components…
Survey on Fruit Disease Identification in Agriculture Using Data Mining
Rathamani, M.; Kanjana Devi, P.
The field of agriculture needs to manage a lot of data and processing and recovery of significant data from this abundance of agricultural information is necessary to support the farmers. In this way, proper…
Intelligent Phishing Detection: Integrating Generative AI with Machine Learning
In latest years, improvements in Internet and cloud technology have brought about a huge boom in digital buying and selling wherein customers make on-line purchases and transactions. This increase results in unauthorized get admission…
Design and Development of a Scalable Online Food Ordering Platform Using the MERN Stack
Online food delivery services have proliferated in recent years, and this has led to an increased demand for platforms that can handle large volumes of traffic while delivering a seamless user experience. As more…
Digital Transformation in Agriculture: Role of Digital Tools in Modernizing Agriculture in India
This paper explores the impact of digital transformation on modernizing agriculture, emphasizing the role of digital tools such as IoT, AI, drones, and blockchain. These technologies enhance precision farming, improve supply chain management, and…
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