International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 05 | May 2023
p-ISSN: 2395-0072
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Integrated Water Resources Management Using Rainfall Forecasting With Artificial Neural Networks In Solapur District, Maharashtra Mr. Dara Pradeep S. 1, Prof. Mrs. Ghadge C.A. 2 , Prof. D.C. Poul 3,Prof. S.C.Wadne 4 1 Student Shri Tuljabhavani Engineering College, Tuljapur. Tuljapur,Osmanabad, Mahrashtra, India 2,3,4 Professor Shri Tuljabhavani Engineering College, Tuljapur, Osmanabad, Mahrashtra, India
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Abstract - In India, agriculture plays an important role in
variety of supervised, unsupervised, and ensemble learning classifiers that are used to predict and detect accuracy on a given dataset. This knowledge can be useful for many people and can be used in a Rainfall forecast system project. Find the most accurate model by comparing various machine learning algorithms such as logistic regression, decision trees, K nearest neighbors, and random forest. We will use the Rainfall data set from the UCI repository.
the Indian economy. Rainfall is important for agriculture, but rainfall forecasting has become a major issue in recent years. A good rain forecast provides knowledge and knowledge in advance to take precautions and develop better strategies for crops.Also, global warming is having a major impact on nature and humans, causing changes in climate conditions. I am accelerating. As temperatures rise and sea levels rise, flooding occurs and farmlands turn into drought. Due to unfavorable climate change, there is unseasonable and unsuitable rainfall. Rainfall forecasting is one of the best ways to learn about Rainfall and climate.
In this study, existing classification techniques are discussed and compared. The paper also mentions the scope of future research and various avenues for further development. The goal of this research effort is to predict Rainfall for a location based on user-provided input parameters. Parameters include date, location, maximum temperature, minimum temperature, humidity, wind direction, evaporation, etc.
The main purpose of this study is to provide customers with a correct climate account from various perspectives such as agriculture, research, power generation, etc., in order to grasp the need for climate transformation and its parameters such as temperature, humidity, etc. . , Rainfall and wind speed lead to Rainfall forecasts. Rainfall is difficult to predict as it also depends on geographic location. Machine learning is an evolving subset of AI that helps predict Rainfall. This research paper uses the UCI repository dataset with multiple attributes to predict Rainfall. The main purpose of this research is to develop a Rainfall forecasting system and use machine learning classification algorithms to predict Rainfall more accurately.
2. STUDY AREA The Solar Pools area is bounded by 17°05'N to 18°32'N and 74°42'E to 76°15'E. The total geographical area of Solapur district is 14895 km². It is divided into 11 tasirs. The district has a dry climate. Average daily highs range from 30°C to 35°C and lows from 18°C to 21°C. The highest temperature in May is 47 degrees. Average annual rainfall is 510 mm. The soil in this area is primarily from Deccan traps. The soils in the area can be broadly divided into three groups: shallow, medium and deep. The district consists of 11 tesils that fall under areas affected by drought and water scarcity. According to the 2011 census, Solapur has a population of 43,17,756.
Key Words: Rainfall Forecasting system, Machine Learning, Dataset, Classification algorithms etc.
1.INTRODUCTION Rainfall forecasts are the most important worldwide and play an important role in human life. Analyzing Rainfall frequencies with uncertainty is a tedious task for meteorological departments. Rainfall is difficult to predict accurately under different atmospheric conditions. It is believed to predict Rainfall for both summer and rainy seasons. This is the main reason why we need to analyze algorithms that can be customized for Rainfall forecasting. One of these proficient and effective technologies is machine learning. “Machine learning is a way of manipulating and extracting known, implicit, previously unknown and potentially useful information about data”.Machine learning is a huge and deep field, the scope and implementation of which is It's expanding day by day. Machine learning includes a
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