scholarly journals A Weather Forecasting Model using the Data Mining Technique

2021 ◽  
Vol 9 (VI) ◽  
pp. 2378-2383
Author(s):  
Tanvi Patil
Keyword(s):  
Data Mining ◽  
Data Model ◽  
Historical Data ◽  
Weather Forecasting ◽  
Weather Condition ◽  
Weather Conditions ◽  
Weather Data ◽  
Forecasting Model ◽  
Data Mining Technique ◽  
Mining Technique

The weather conditions are changing continuously and the entire world is suffers from the changing Clemet and their side effects. Therefore pattern on changing weather conditions are required to observe. With this aim the proposed work is intended to investigate about the weather condition pattern and their forecasting model. On the other hand data mining technique enables us to analyse the data and extract the valuable patterns from the data. Therefore in order to understand fluctuating patterns of the weather conditions the data mining based predictive model is reported in this work. The proposed data model analyse the historical weather data and identify the significant on the data. These identified patterns from the historical data enable us to approximate the upcoming weather conditions and their outcomes. To design and develop such an accurate data model a number of techniques are reviewed and most promising approaches are collected.

scholarly journals Design and Implementation of Rainfall Prediction Model using Supervised Machine Learning Data Mining Technique s

2021 ◽  
Vol 1 (2) ◽  
pp. 20-26
Author(s):  
Deepak Sharma ◽  
◽  
Dr. Priti Sharma ◽  
Keyword(s):  
Data Mining ◽  
Prediction Model ◽  
Missing Values ◽  
Market Analysis ◽  
Supervised Machine Learning ◽  
Weather Data ◽  
Complex Data ◽  
Data Mining Technique ◽  
Rainfall Prediction ◽  
Mining Technique

Data mining is a rapidly developing technology that has enriched a lot of field such as business analysis, market analysis, weather forecasting, stock market analysis and many more. It starts with collecting data sets from reliable sources and pre-processing that data. There are some anomalies associated with data collected in large volumes such as outliers, missing values, and duplicated values. Remove these kinds of anomalies is teamed as pre-processing of data. In this paper, collection of weather data and pre-processing it for rainfall prediction model using Rapid Miner tool has been discussed. Also, artificial neural network data mining techniques is used to design a rainfall prediction model. ANN classification techniques is a complex data mining technique results in high accuracy in prediction of rainfall.

scholarly journals A Data Mining Approach for Parameter Optimization in Weather Prediction

2020 ◽  
Vol 1 (1) ◽  
pp. 1-13
Author(s):  
Thushika N ◽  
Premaratne S
Keyword(s):  
Data Mining ◽  
Web Mining ◽  
Weather Forecasting ◽  
Weather Prediction ◽  
Weather Data ◽  
Quality Model ◽  
Data Mining Technique ◽  
Related Data ◽  
Time To Build ◽  
Effective Manner

More than two decades, there is a number of weather-related websites are available which approximately predict the weather and climate. By extracting essential data from the websites, a predictive data pattern can be produced to show the next day’s weather is with rain or not.  By applying different types of web mining and analyzing techniques those extracted weather-related data can be visualized to a typical pattern for weather forecasting with the main deciding factors of weather. With the use of these approaches, reasonably precise forecasts can be made up to about four to five days in advance. For the weather prediction analysis, we need to discover deciding factors of the next day’s weather. Particularly, common weather dependent factors and the relationship of the prediction to the particular phenomenon. The solution proposed by this research can be used to analyze a large amount of weather data which are in different forms in each source. By using predictive mining task our solution allows us to make predictions for future instances according to the model what we have created. Evaluation measurements for the selected data mining technique such as accuracy percentage, TP & FP Rate, Precision, F-Measure, ROC area, SSE, and loglikelihood for classification and clustering leads to create a high-quality model of prediction. Knowledge flow interface provides the data flow to show the processing and analyzing data with precise association rules. In order to evaluate the model, SSE values and time to build the model, are considered in an effective manner.

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