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Predictive Analytics In Weather Forecasting Using Machine Learning Algorithms

Aastha Sharma, Vijayakumar V
2018 EAI Endorsed Transactions on Cloud Systems  
For Predicting weather forecasting we will use machine learning Algorithms like Linear Regression, Decision tree.  ...  In a country like India, which has ever increasing demand of food due to rising population, advances in agriculture sector are required to meet the needs.  ...  Predictive Analytics In Weather Forecasting Using Machine Learning Algorithms 3 Methodology Data Preprocessing The more you preprocess the data set, the more accurate result you will get. basically  ... 
doi:10.4108/eai.7-12-2018.159405 fatcat:cfjnz6kla5gxphb3qzuthmdv7a


V. M. Sineglazov, M. O. Omelchenko, V. P. Hotsyanivskyy
2018 Electronics and Control Systems  
It is considered the creation of intelligent weather forecast system in traditional statement as the prediction of time series For the solution of this problem it is chosen a random forest algorithm.  ...  Examples of program implementation of the algorithm are given using libraries for the python programming language, namely Pandas and Skicit-learn.  ...  PROBLEM STATEMENT Within the field of data analysis a methods of machine learning used for a finding of algorithms that serve prediction.  ... 
doi:10.18372/1990-5548.55.12778 fatcat:bbkolrfmlned7fkzrdpzjugf5e

Machine learning amalgamation of Mathematics, Statistics and Electronics

Trupti S. Gaikwad, Snehal A. Jadhav, Ruta R. Vaidya, Snehal H. Kulkarni
2020 International Research Journal on Advanced Science Hub  
Why we use machine learning? Because it plays an influential role in prediction of data.  ...  Machine learning adopts different algorithms and each algorithm performs different functionality.  ...  Smart sensors are also used along with machine learning for developing number of applications like weather forecast system, in healthcare instruments, in smart home systems etc.  ... 
doi:10.47392/irjash.2020.72 fatcat:tthyajj6d5bf5idubxxzq7qo5i

Big Data Analytics to Increase the Agricultural Yield by Using Machine Learning Approaches

V. Sudha, S. Mohan, S. Arivalagan
2018 Asian Journal of Computer Science and Technology  
A study of machine learning algorithms for big data Analytic is also done and presented in this paper.  ...  It provides a methodology for facing challenges in agricultural production, by applying this Algorithm, using machine learning techniques.  ...  Machine learning algorithms were implemented for zip data sets. Machine learning is an approach used to improve scheduled models for prediction.  ... 
doi:10.51983/ajcst-2018.7.s1.1799 fatcat:w47at3qonjaunf4f6v7frwwqtu

Operational Demand Forecasting In District Heating Systems Using Ensembles Of Online Machine Learning Algorithms

Christian Johansson, Markus Bergkvist, Davy Geysen, Oscar De Somer, Niklas Lavesson, Dirk Vanhoudt
2017 Energy Procedia  
This paper presents the current status and results from extensive work in the development, implementation and operational service of online machine learning algorithms for demand forecasting.  ...  This paper presents the current status and results from extensive work in the development, implementation and operational service of online machine learning algorithms for demand forecasting.  ...  For Blekinge Institute of Technology this work is part of the research project "Scalable resource-efficient systems for big data analytics" funded by the Knowledge Foundation (grant: 20140032) in Sweden  ... 
doi:10.1016/j.egypro.2017.05.068 fatcat:qfy7manwsbepphymz46gpkuzqu

Load Forecasting In Microgrid Systems With R And Cortana Intelligence Suite

F. Lazzeri, I. Reiter
2017 Zenodo  
components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft  ...  Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and  ...  This ensures drive a long term and continues business value generation from machine learning and predictive analytics technologies.  ... 
doi:10.5281/zenodo.1131257 fatcat:jldk732tgjfgpdqbsl7nrkuwtq

Predicting Weather Forecasting State Based on Data Mining Classification Algorithms

Fairoz Q. Kareem, Adnan Mohsin Abdulazeez, Dathar A. Hasan
2021 Asian Journal of Research in Computer Science  
With the recent development in technology, especially in the DM and machine learning techniques, many researchers proposed weather forecasting prediction systems based on data mining classification techniques  ...  In this paper, we utilized neural networks, Naïve Bayes, random forest, and K-nearest neighbor algorithms to build weather forecasting prediction models.  ...  Extreme machine learning was used to aid meteorologists in their weather predictions.  ... 
doi:10.9734/ajrcos/2021/v9i330222 fatcat:rueo7wn6irggpeh2hhtmmo5eqi


Nguyen Phuc Tran, Thi Thuy Nga Duong, Duy Thanh Tran
2019 Zenodo  
Along with the development of computer science, mathematical models are built and applied to machine learning techniques that help to build accurate and more reliable predictive models.  ...  Therefore, it's hard to collect data for the construction of predictive models to make accurate simulations. In Viet Nam, the research for weather forecast models have been applied recently.  ...  In the past decade, many researchers in the world have been trying to solve the forecast of weather by using a statistical model, including machine learning techniques that has been reported to reach many  ... 
doi:10.5281/zenodo.6190226 fatcat:x5msg5g4mfghjejehxh4pitpp4

Preface [chapter]

2021 Machine Learning for Sustainable Development  
The book has compressive studies regarding the energy demand prediction, agriculture, weather forecasting and medical applications using models of ML that have profoundly contributed.  ...  Preface Machine learning (ML) is a part of computerized reasoning which comprises algorithms and artificial neural networks and displays qualities firmly connected with human insight.  ...  The analysis of Alzheimer's disease using support vector machine, and ML in agriculture are the two contextual investigations presented in the chapter.  ... 
doi:10.1515/9783110702514-202 fatcat:ldzvtdqe3vfyrbgb5f4wilqex4

Data Science and Machine Learning for hurricane forecasting

Stefan Schmainta
2022 Zenodo  
During times of a continued increase in global temperatures, it more important than ever to further improve today's forecasting and prediction methods.  ...  Two possible Data Science approaches are being demonstrated and proveen to add value to the traditional statistics based forecasting methods.  ...  In a study, the researchers used machine learning to remove certain groups of hurricane predictions from ensembles -sets of predictions from weather models that are based on a range of weather possibilities  ... 
doi:10.5281/zenodo.5932784 fatcat:7ezi2i7gordgzmgha6m7cprvqa

Big Data Analytics Using Swarm-Based Long Short-Term Memory for Temperature Forecasting

Malini M. Patil, P. M. Rekha, Arun Solanki, Anand Nayyar, Basit Qureshi
2022 Computers Materials & Continua  
To forecast weather conditions, researchers have utilized machine learning algorithms, such as autoregressive integrated moving average, ensemble learning, and long short-term memory network.  ...  These techniques have been widely used for the prediction of temperature.  ...  [3] surveyed different machine learning approaches in forecasting the weather conditions in a region. These techniques require more time for learning the data during prediction. Sawaitul et al.  ... 
doi:10.32604/cmc.2022.021447 fatcat:ekyoumqjw5fpplxsm3pugfu2py

An Autonomic Approach to Real-Time Predictive Analytics Using Open Data and Internet of Things

Wassim Derguech, Eanna Bruke, Edward Curry
2014 2014 IEEE 11th Intl Conf on Ubiquitous Intelligence and Computing and 2014 IEEE 11th Intl Conf on Autonomic and Trusted Computing and 2014 IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops  
This work has been evaluated in real settings using IoT sensors and open weather data.  ...  The main challenge in this context is the dynamic selection of open data and IoT sources to support predictive analytics.  ...  The main pillar of this component is the machine learning algorithm that it uses. We identified a set of requirements for choosing the right machine learning algorithm.  ... 
doi:10.1109/uic-atc-scalcom.2014.137 dblp:conf/uic/DerguechBC14 fatcat:2kg5ebkslzb5xglmjwi4bxwm3q

Farmer Buddy-Weather Prediction and Crop Suggestion using Artificial Neural Network on Map-Reduce Framework

Manali Joshi, Saminabano Shaikh, Prachi Waghmode, Padma Mali
2017 International Journal of Computer Applications  
Weather condition analysis and its prediction has always been a task of great efforts. It is tedious to predict the weather accurately.  ...  This paper proposes an approach of using Hadoop for processing such Big volumes, variety and velocity of weather data.  ...  Since, data analysis will be the major task in weather forecasting within the field of data analysis, Machine learning is method used to device complex models and algorithms that lend themselves to predictions  ... 
doi:10.5120/ijca2017912985 fatcat:xyfqez32mnemhcz3ws4kyimzuu

Rainfall Predictions Using Data Visualization Techniques

Kaushal Kailas Sarda
2022 International Journal for Research in Applied Science and Engineering Technology  
Index Terms: Data Visualisation, Weather Prediction, Machine Learning Techniques, Data Analytics, Rainfall Pattern  ...  in the collection of weather data.  ...  By doing the algorithm makes a strategy to predict the weather .Various Machine learning models can also help to predict the useful insights from the large datasets III.  ... 
doi:10.22214/ijraset.2022.42151 fatcat:nry5t5t3yjekfceb36u5dib6lq

Machine Learning in Agriculture

Matthew N. O. Sadiku, Chandra M. M Kotteti, Sarhan M. Musa
2018 International Journal of Advanced Research in Computer Science and Software Engineering  
Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.  ...  Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  ...  Machine learning in agriculture allows for more accurate disease diagnosis than the traditional method of visual examination [4] .  Weather Forecasting: An accurate and reliable forecast of weather can  ... 
doi:10.23956/ijarcsse.v8i6.713 fatcat:iy3zfx2olfh3bcf3t4w2spa5py
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