Analyzing Traffic Problem Model With Graph Theory Algorithms

This paper will contribute to a practical problem, Urban Traffic. We will investigate those features, try to simplify the complexity and formulize this dynamic system. These contents mainly contain how to analyze a decision problem with combinatorial method and graph theory algorithms; how to optimize our strategy to gain a feasible solution through employing other principles of Computer Science.Comment: 7 pages, 5 figures, Science and Information Conference (SAI), 201

Introduction to Graph Polynomials

With graph polynomials being a fairly new but intricate realm of graph theory, I will begin with a brief historical background and progress to elucidate each polynomial’s unique characteristics and mathematical underpinnings. Through illustrative examples, the paper elucidates the practical applications of these graph polynomials, showcasing their efficacy in real-world scenarios. My research contributes to the broader understanding of graph polynomials and inspires further research in the intersection of mathematics and technology

Natural Disaster Detection Using Wavelet and Artificial Neural Network

Indonesia, by the location of its geographic and geologic, it have more potential encounters for natural disasters. This nation is traversed by three tectonic plates, namely: IndoAustralian, the Eurasian and the Pacific plates. One of the tools employed to detect danger and send an early disaster warning is sensor device for ocean waves, but it has drawbacks related to the very limited time gap between information/warnings obtained and the real disaster event, which is only less than 30 minutes. Natural disaster early detection information system is essential to prevent potential danger. The system can make use of the pattern recognition of satellite imagery sequences that take place before and during the natural disaster. This study is conducted to determine the right wavelet to compress the satellite image sequences and to perform the pattern recognition process of a natural disaster employing an artificial neural network. This study makes use of satellite imagery sequences of tornadoes and hurricanes