The Academic Resources Recommender System (ARReS) includes collection of Theses and Dissertations available in the Camarines Sur Polytechnic Colleges Library.
Due to its geographic location, the Philippines is a flood-prone country. According to the Asian Disaster Reduction Center, the Philippines is one of the most flood-prone countries in the world. With limited resources and a major portion of the population living below the poverty line, flood impacts are severe. Deaths, malnutrition, widespread diseases, damage to infrastructure, and disruption in the economy are some of the aftereffects of this cataclysm. To put a flood management system into effect, it is essential to predict flooding events ahead of time. In this work, the researchers applied different correlation coefficients for feature selection and the k-Nearest Neighbors (kNN) algorithm for the prediction of the flood. The kNN model was implemented using the Philippine historical weather data such as rainfall, flood risk, and flood average which was gathered from the Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA). This study has determined 54 stations, which is annually and monthly data to predict floods and have presented the flood-prone areas in the Philippines based on the data gathered. The flood prediction using k-NN Algorithm can low, moderate, intensity and high intensity flood category. The detailed result analysis shows that the study has achieved a high testing accuracy of 98% and above. With this, it can be concluded that identifying rainfall data, flood risk and flood average that have a relationship to flooding is the best way to mitigate and control floods.
Ryan C. Villaflor; John Lloyd P. Dayupay; Judy Ann H. Obero; Roselyn A. Sales; Maria Dulce Ll. Ciano
2022 Computer ScienceAn accident at one spot may occur more frequently than at other locations on the same road due to the irrepressible road or environmental circumstances; these locations are called accident-prone areas. With these, the study was conducted to develop a system that will optimize accidental prone area a...
Elena Clarexe R. Gulane; Jan Marc P. Culas; Albert P. Aquilino; Manny C Miñolas
2022 Computer ScienceData mining techniques are used to generate significant patterns, then to build data models for prediction. In this connection, this thesis aimed to utilize Educational Data Mining to mine Grade 10students' Grade Point to select a Senior High School Strand using student data from the target school. ...
Cyrene R. Cerillano; Melbert B. Hallare; Kenneth Ryan L. Solera; Mary Joy P. Tañamor
2022 Information TechnologyThe COVID-19 pandemic faced several challenges and had a significant impact on world public health, particularly in the Philippines. It led to a significant change in information storage and retrieval, specifically in each COVID-19 patient's health records. Thus, a study has been conducted to devel...
Nelson H. Credo; Norman Bryan D. Belmonte; Renz Marrion G. Basilan; Rodny N. Fermiza
2022 Computer ScienceAmidst the pandemic, education has remained an important sector that must continue for the children are the hope of the nation. With this, the government launched an online learning modality with the support and cooperation of the responsible government agencies allowing the students and teachers to...