Integrated Mining of Multi-Modal Data for Decision Making in Agrometeorology

• Grant number: 11/15017-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: March 01, 2012
• End date: February 28, 2014
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Agma Juci Machado Traina
• Grantee: Daniel Yoshinobu Takada Chino
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

This project aims at developing a new mining system for agrometeorological and climatological data. Its goal is to integrate diversified sources of data (time series of climate indexes extracted from satellite images and time series of different resolutions gathered from agrometeorological sensor data), in order to build a new software level of the SatImageExplorer system. Thus, the new software will be able to symbiotically mine relevant information from patterns leading to extreme events, or the seasonal ones, following the specialists´ specifications. We intend to employ new ways of measuring time series, for example, following the variation of their intrinsic behavior features, by employing their fractal, or intrinsic dimensionality. The relationship between multi-dimensional time series will be assessed by a new extension of the Dynamic Time Warping distance, to be developed in this project. By doing so, it will be possible to tune the correlation between the series´ control points, as well as to adjust their displacement in a more effective way.

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

CHINO, Daniel Yoshinobu Takada. Mining frequent patterns in time series to support decision-making in agrometeorology. 2014. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.