Prevalence of Depression among Medical and Engineering students, Bellary, Karnataka,India

K, Ramesh K Dr. Ramesh; Goud, T. Gangadhara

doi:10.15373/22778179/apr2014/187

IJSR

2012

DOI: 10.15373/22778179/apr2014/187

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Prevalence of Depression among Medical and Engineering students, Bellary, Karnataka,India

Ramesh K Dr. Ramesh K¹,

T. Gangadhara Goud²

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“…In the past, forest fire detection was mainly done through human observation or satellite imagery [3]. Unfortunately, these methods have their drawbacks, such as being inaccurate, slow, and expensive.…”

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A Machine Learning Based System to Classify Forest Fire Prediction for Forest Safety

Teja

2024

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Forecasting forest fires requires the application of different techniques and instruments to evaluate the likelihood and potential seriousness of a fire starting in a forested region. Elements like drought, extreme temperatures, and human behaviors like bonfires, cigarettes, and pyrotechnics can all play a role in sparking forest fires. Various methods such as statistical examination, AI algorithms, and satellite pictures are employed to gather and dissect data on climate conditions, moisture levels, topography, and other factors that may heighten the chance of a forest fire. Models for predicting forest fires can furnish advanced caution systems to inform officials and locals of potential fire hazards. Predicting forest fires in the future is expected to decrease the impact of fires. This study focuses on developing a system for predicting forest fires, which calculates the likelihood of a fire starting based on various meteorological factors such as location (latitude and longitude) and temperature. The Random Forest regression algorithm was utilized to create this predictive model. Key Words: Forest Fire, Machine Learning, Temparature, Random Forest, Regression

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A Machine Learning Based System to Classify Forest Fire Prediction for Forest Safety

Teja

2024

IJSREM

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Prevalence of Depression among Medical and Engineering students, Bellary, Karnataka,India

Cited by 1 publication

References 0 publications

A Machine Learning Based System to Classify Forest Fire Prediction for Forest Safety

A Machine Learning Based System to Classify Forest Fire Prediction for Forest Safety

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