[HTML][HTML] Understanding the potential applications of Artificial Intelligence in Agriculture Sector
Artificial Intelligence (AI) has been extensively applied in farming recently. To cultivate
healthier crops, manage pests, monitor soil and growing conditions, analyse data for …
healthier crops, manage pests, monitor soil and growing conditions, analyse data for …
Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting
Accurate forecasting of rainfall is extremely important due to its complex nature and
enormous impacts on hydrology, floods, droughts, agriculture, and monitoring of pollutant …
enormous impacts on hydrology, floods, droughts, agriculture, and monitoring of pollutant …
[HTML][HTML] An advanced intelligence system in customer online shopping behavior and satisfaction analysis
Online shopping or internet shopping is increasing day by day. With the advancement of
modern technology, the online market is growing in a vast way. People nowadays prefer …
modern technology, the online market is growing in a vast way. People nowadays prefer …
[HTML][HTML] Effects of co-curricular activities on student's academic performance by machine learning
The study project named" Effects of Co-Curricular Activities on Student's Academic
Performance Through Machine Learning" examines the effect of co-curricular activities on a …
Performance Through Machine Learning" examines the effect of co-curricular activities on a …
Predicting satisfaction of online banking system in Bangladesh by machine learning
Online banking refers to using your smartphone, tablet, or another internet-connected
computer to browse and access your bank account. It is quick and free, and it usually allows …
computer to browse and access your bank account. It is quick and free, and it usually allows …
Enhancing weather forecasting integrating LSTM and GA
Several sectors, such as agriculture and renewable energy systems, rely heavily on weather
variables that are characterized by intermittent patterns. Many studies use regression and …
variables that are characterized by intermittent patterns. Many studies use regression and …
A Review on Machine Learning and Deep Learning based Rainfall Prediction Methods
N Srinu, BH Bindu - … Conference on Power, Energy, Control and …, 2022 - ieeexplore.ieee.org
Water for farming and storage capacity in dams are both affected by the quantity of
precipitation that falls. Predicting when and how much rain will fall is challenging because of …
precipitation that falls. Predicting when and how much rain will fall is challenging because of …
Rainfall variability over multiple cities of India: analysis and forecasting using deep learning models
India being an agrarian economy, rainfall is an essential component that directly or indirectly
influences agricultural produce. With the increasing impacts of the changing climate …
influences agricultural produce. With the increasing impacts of the changing climate …
[HTML][HTML] Machine learning approach to predict the depression in job sectors in Bangladesh
Depression is a significant and growing issue that substantially affects an individual's way of
life, interrupting typical functioning and blocking viewpoints. At the same time, they may be …
life, interrupting typical functioning and blocking viewpoints. At the same time, they may be …
Machine learning approach to predict SGPA and CGPA
The prediction of SGPA and CGPA is beneficial to university students. Students will easily
get an estimate of their final outcome from this project. As a result, the students will be able …
get an estimate of their final outcome from this project. As a result, the students will be able …