The application of machine learning techniques in the field of tourism is experiencing a
remarkable growth, as they allow to propose efficient solutions to problems present in this …

Introduction Atmospheric temperature affects the growth and development of plants and has
an important impact on the sustainable development of forest ecological systems. Predicting …

This study is based on temperature prediction in the capital of India (New Delhi). We have
adopted different ML models such as (MPR and DNN) which are designed and implemented …

The primary motivation for this study is the recent growth and increased interest in artificial
intelligence (AI). Despite the widespread recognition of its critical importance, a discernible …

We compare three machine learning models—artificial neural network (ANN), random forest
(RF), and convolutional neural network (CNN)—for spatial downscaling of temperature at 2 …

Abstract The United States' agricultural sector depends heavily on production to
continuously supply the country's enormous demand for milk and dairy products. Despite its …

The flavour of tea as a worldwide popular beverage has been studied extensively. This
study aimed to apply established flavour analysis techniques (GC–MS, GC-O-MS and APCI …

The digital images can easily be manipulated using Software tool or mobile application
these days. Dispersal of forgery images in social media is one of the prime threats and it has …

Food crops are important for nations and human survival. Potatoes are one of the most
widely used foods globally. But there are several diseases hampering potato growth and …

The efficacy of generalized sugarcane yield prediction models holds significant implications
for global food security. Given that machine learning algorithms often surpass the precision …