[HTML][HTML] A Novel WD-SARIMAX model for temperature forecasting using daily delhi climate dataset
Forecasting is defined as the process of estimating the change in uncertain situations. One
of the most vital aspects of many applications is temperature forecasting. Using the Daily …
of the most vital aspects of many applications is temperature forecasting. Using the Daily …
A machine learning-based model for predicting temperature under the effects of climate change
Regarding the climatechange, importance of forecastingweather conditions, especially
temperatures, is necessary to avoid climate change conditions and recommend precautions …
temperatures, is necessary to avoid climate change conditions and recommend precautions …
[HTML][HTML] Data-driven models for atmospheric air temperature forecasting at a continental climate region
Atmospheric air temperature is the most crucial metrological parameter. Despite its influence
on multiple fields such as hydrology, the environment, irrigation, and agriculture, this …
on multiple fields such as hydrology, the environment, irrigation, and agriculture, this …
Deep learning model for temperature prediction: an empirical study
VK Shrivastava, A Shrivastava, N Sharma… - Modeling Earth Systems …, 2023 - Springer
Planning the daily routines of human life depends heavily on the weather. Knowing the
weather ahead of time substantially aids in better planning for aviation, agriculture, tourism …
weather ahead of time substantially aids in better planning for aviation, agriculture, tourism …
Fuzzy rule–based weighted space–time autoregressive moving average models for temperature forecasting
In an agriculturally dependent country like India, efficient and reliable forecasting techniques
for various climatic parameters are essential. Temperature is one of the most significant …
for various climatic parameters are essential. Temperature is one of the most significant …
A Machine-Learning Approach to Time Series Forecasting of Temperature
In the modern world, weather forecasting is an essential application. The forecasts can help
us reduce weather-related losses. The need for a massive data and highly computationally …
us reduce weather-related losses. The need for a massive data and highly computationally …
[HTML][HTML] Forecasting of monthly relative humidity in Delhi, India, using SARIMA and ANN models
Relative humidity plays an important role in climate change and global warming, making it a
research area of greater concern in recent decades. The present study attempted to …
research area of greater concern in recent decades. The present study attempted to …
Temperature prediction using machine learning approaches
T Anjali, K Chandini, K Anoop… - 2019 2nd International …, 2019 - ieeexplore.ieee.org
Weather prediction is one of the most important research areas due to its applicability in real-
world problems like meteorology, agricultural studies, etc. We propose a method for …
world problems like meteorology, agricultural studies, etc. We propose a method for …
[HTML][HTML] Comparative study of wavelet-ARIMA and wavelet-ANN models for temperature time series data in northeastern Bangladesh
Time-series analyses of temperature data are important for investigating temperature
variation and predicting temperature change. Here, Mann–Kendall (M–K) analyses of …
variation and predicting temperature change. Here, Mann–Kendall (M–K) analyses of …
[HTML][HTML] Application of advanced optimized soft computing models for atmospheric variable forecasting
Precise Air temperature modeling is crucial for a sustainable environment. In this study, a
novel binary optimized machine learning model, the random vector functional link (RVFL) …
novel binary optimized machine learning model, the random vector functional link (RVFL) …