An Android Application Using Machine Learning Algorithm for Clique Detection in Issues Related to Transportation

Abstract

This paper presents the development of a new variant mobile application with a local search algorithm that has been designed to detect routes in school transportation. The School bus routing problem relates to designing the optimum distribution/collection routes for the school buses serving geographically scattered students, and has been the focus of many academics for a long time. The proposed application system selects the best route for the buses to pick up the students from their houses. The system determines the optimal route for designated locations using google maps endings in efficient use of time and fuel. In order to meet the tremendous distance and the complex geographic structure, the proposed method divide the geographic regions into cliques that contain close houses to each other. The application is implemented on Android operating system since android is currently broadly utilized. The proposed framework is integrated with Google API to handle access to map display, data downloading and Google Maps servers. To evaluate the proposed application a survey was conducted. The findings from the reviews were impressive and substantial. The proposed solution of the school bus routing problem can be applied to solve problems related to the vehicles of institutions and organizations

Sentiment Analysis for People’s Opinions about COVID-19 Using LSTM and CNN Models

“…It is one of NLP applications that needs machine learning algorithms as the classification process [49]. It is considered a complex process with five steps, which begins with collecting data and continues with preprocessing text, detecting sentiment, and classifying text into positive, negative, and other categories.…”