scholarly journals Weather Forecasting and Climate Changing Using Data Mining Application

IJARCCE ◽  
2015 ◽  
pp. 19-21 ◽  
Author(s):  
Ankita Joshi ◽  
Bhagyashri Kamble ◽  
Vaibhavi Joshi ◽  
Komal Kajale ◽  
Nutan Dhange
Keyword(s):  
Data Mining ◽  
Weather Forecasting ◽  
Using Data ◽  
Data Mining Application

scholarly journals CREDIT ANALYSIS USING DATA MINING: APPLICATION IN THE CASE OF A CREDIT UNION

2014 ◽  
Vol 11 (2) ◽  
pp. 379-396 ◽  
Author(s):  
Marcos de Moraes Sousa ◽  
◽  
Reginaldo Santana Figueiredo ◽  
Keyword(s):  
Data Mining ◽  
Credit Union ◽  
Using Data ◽  
Credit Analysis ◽  
Data Mining Application

Rules Extraction using Data Mining in Historical Data

2016 ◽  
pp. 263-279
Author(s):  
Manish Kumar ◽  
Shashank Srivastava
Keyword(s):  
Data Mining ◽  
Weather Forecasting ◽  
Satellite Communications ◽  
Building Blocks ◽  
Predictive Analysis ◽  
Rule Based ◽  
Using Data ◽  
Rules Extraction ◽  
The Impact ◽  
Expected Outcomes

Rules are the smallest building blocks of data mining that produce the evidence for expected outcomes. Many organizations like weather forecasting, production and sales, satellite communications, banks, etc. have adopted this mode of technological understanding not for the enhanced productivity but to attain stability by analyzing past records and preparing a rule-based strategy for the future. Rules may be extracted in different ways depending on the requirements and the dataset from that has to be extracted. This chapter covers various methodologies for extracting such rules. It presents the impact of rule extraction for the predictive analysis in decision making.

Analysis of Climate Prediction and Climate Change in Pakistan Using Data Mining Techniques

2020 ◽  
pp. 321-338
Author(s):  
Soobia Saeed ◽  
N. Z. Jhanjhi ◽  
Mehmood Naqvi ◽  
Vasaki Ponnusamy ◽  
Mamoona Humayun
Keyword(s):  
Climate Change ◽  
Data Mining ◽  
Weather Forecasting ◽  
Point Of View ◽  
Weather Data ◽  
Maximum Temperature ◽  
Sufficient Information ◽  
Climate And Environmental Change ◽  
Environment Variables ◽  
Using Data

Weather forecasting is a significant meteorological task and has arisen in the last century from a rational and revolutionary point of view among the most difficult problems. The authors are researching the use of information mining techniques in this survey to measure maximum temperature, precipitation, dissipation, and wind speed. This was done using vector help profiles, decision tree, and weather data obtained in Pakistan in 2015 and 2019. For the planning of workbook accounts, an information system for meteorological information was used. The presentations of these calculations considered using standard implementing steps as well as the estimate that gave the best results for generating disposal rules for intermediate environment variables. Likewise, a prophetic network model for the climate outlook program, contradictory results, and true climate information for the projected periods have been created. The results show that with sufficient information on cases, data mining strategies can be used to estimate the climate and environmental change that it focuses on.

Optimal Water Allocation Using Data Mining Techniques- A Survey

2018 ◽  
Vol 6 (8) ◽  
pp. 225
Author(s):  
Sara Kutty T K ◽  
Hanumanthappa M
Keyword(s):  
Water Management ◽  
Data Mining ◽  
Water Resources ◽  
Water Allocation ◽  
Optimal Allocation ◽  
Weather Forecasting ◽  
Theoretical Background ◽  
Survey Paper ◽  
Using Data ◽  
Optimal Water Allocation

Water is one of the most precious resources on earth. All living beings depend on water and it is used for agriculture, environment, household, power generation, industries, navigation, recreation etc. The volume of water resources data in the world is increasing day by day and various studies are carried-out on these data for decision making process. To handle this enormous volume of water data, many methods are available, but the most adequate and suitable method for optimal allocation of water data is data mining. It can be used to predict the results for future action related to weather forecasting, climate change, water management, flood controlling, optimal water allocation etc. This survey paper elaborates the theoretical background of data-mining models and highlights the applications in knowledge data discovery from a water resources database, in particularly on optimal water allocation. Application of data-mining to water management is at a developmental stage and very few research works have been carried out on this domain.

scholarly journals A Survey of using Data Mining Techniques for Soil Fertility

2018 ◽  
Vol 7 (2.7) ◽  
pp. 917
Author(s):  
Madhuri Kommineni ◽  
Someswari Perla ◽  
Divya Bharathi Yedla
Keyword(s):  
Data Mining ◽  
Soil Fertility ◽  
Weather Forecasting ◽  
Large Data ◽  
Soil Biology ◽  
Weed Detection ◽  
Nutrient Analysis ◽  
Data Mining Techniques ◽  
Development Data ◽  
Using Data

Data Mining is a technique which focuses on large data sets to extract information for prediction and discovery of hidden patterns.  Data Mining is applicable on various areas like healthcare, insurance, marketing, retail, communication, agriculture. Agriculture is the backbone of country’s economy. It is the important source of livelihood. Agriculture mainly depends on climate, topography, soil, biology. Agricultural Mining is a technology which can bring knowledge to agriculture development. Data Mining in agriculture plays a role in weather forecasting, yield prediction, soil fertility, fertilizers usage, fruit grading, plant disease and weed detection. The current study presents the different data mining techniques and their role in context of soil fertility, nutrient analysis. 

Rules Extraction using Data Mining in Historical Data

2014 ◽  
pp. 89-106
Author(s):  
Manish Kumar ◽  
Shashank Srivastava
Keyword(s):  
Data Mining ◽  
Weather Forecasting ◽  
Satellite Communications ◽  
Building Blocks ◽  
Predictive Analysis ◽  
Rule Based ◽  
Using Data ◽  
Rules Extraction ◽  
The Impact ◽  
Expected Outcomes

Rules are the smallest building blocks of data mining that produce the evidence for expected outcomes. Many organizations like weather forecasting, production and sales, satellite communications, banks, etc. have adopted this mode of technological understanding not for the enhanced productivity but to attain stability by analyzing past records and preparing a rule-based strategy for the future. Rules may be extracted in different ways depending on the requirements and the dataset from that has to be extracted. This chapter covers various methodologies for extracting such rules. It presents the impact of rule extraction for the predictive analysis in decision making.

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