Indian Journal of Science and Technology

Abstract

Objectives: The main objective of this study is to forecast the number of fire for the years 2016 to 2020 that is possible to occur in the Philippines and to find the best fit multiple linear regression models for the said variable. Methods/Statistical analysis: The secondary data of Electrical Connections, Electrical Appliances, Spontaneous Combustion, Open Flame due to Unattended Cooking/Stove, Open Flame due to Torch, Open Flame due to Lighted Candle, Liquefied Petroleum Gas (LPG) Explosion due to Direct Flame Contact/Static Electricity, Lighted Cigarette Butt, Lighted Matchstick/Lighter, Under Investigation, and Others that was used in the study were gathered from Philippine bureau of fire protection. The data were analyzed by the use of statistical software such as EViews7 and MATLAB. Findings: In this paper, we showed that the independent variables namely, Electrical Connections, Electrical Appliances, Spontaneous Combustion, Open Flame due to Unattended Cooking/Stove, Open Flame due to Torch, Open Flame due to Lighted Candle, LPG Explosion due to Direct Flame Contact/Static Electricity, Lighted Cigarette Butt, Lighted Matchstick/Lighter, Under Investigation, and Others significantly affect the dependent variables which is the number of fire accidents. A normal estimation equation was derived to be the model that is best fit in predicting the number of fire for the year 2016 to 2020 through Multiple Linear Regression. Application/Improvements: This paper will be of help in raising the awareness of the citizen and the local government unit that is concerned in this matter to be prepared and allocate more effort in preventing a great damage caused by fire accidents.

Keywords: Fire Accidents, Forecasting, Multiple Linear Regression, Normal Estimation Equation, MATLAB